 
  
Supervisor: Kevin Cullinane 
Master Degree Project No. 2016:83 
Graduate School 
 
 
 
 
 
 
 
Master Degree Project in Logistics and Transport Management 
 
 
 
 
 
 
The Competitiveness of the Port of Gothenburg 
as an E-Business Distribution Centre in Scandinavia 
 
 
 
 
 
Achille Loce- Mandes 
ABSTRACT 
________________________________________________________________________
Title:             The Competitiveness of the Port of Gothenburg as an E-Business 
Distribution  Centre in Scandinavia.
Final version:   2016-06-16
University: Gothenburg University, Handelshogskolans 
Master: Master in Science in Logistics and Transport Management. 
Master Thesis, 30 hp 
Tutor University:  Kevin Cullinane
Tutor PoG: Claes Sundmark
Author: Achille Giovanni Stefano LOCE-MANDES
Author’s Email: a.locemandes@gmail.com
________________________________________________________________________
The research is focused on the competitiveness of the Port of Gothenburg, as a future 
destination for online retailers, when investing in a new warehouse; emphasis is dedicated 
to those warehouses locate in ports area (port-centric logistics). 
Several topics are discussed in order to provide some fundamentals for a future e-retailer’s 
investment choice. 
The literature discussed focus on supply chain, general characteristics, the network 
planning, logistics strategies, and logistics factors related to the performance.
A background in warehousing is provided, to better clarify several elements such as 
warehouse adoption, and appropriate location. Necessary elements affecting the facility 
location strategy. 
The maritime background where the major players are ports and shipping lines. Particular 
focus is placed on port operations, port efficiency, port services, port-centric activities, and 
the choice of shipping lines when calling a port. 
Certainly, some information about retailers and online retailers characteristics, represent 
some basic knowledges to provide. Several parameters are taken into consideration when 
retailers select e-consumers in the most profitable country. 
E-buyers characteristics are considered to identify the Scandinavian potential buyers.
The thesis conclude specifying the country and the port that better satisfy (time-miles) the 
Scandinavian e-consumers. 
Key words
Scandinavia, warehousing, supply chain, maritime, port, port performance, port-centric, e-
commerce, e-buyers. 
Pag.  I
ACKNOWLEDGEMENT 
This master thesis has been advanced during the spring term of 2016 with the continuous 
support of my tutors Kevin Cullinane and Claes Sundmark. 
Thank you Kevin for the time you spent assisting me in this research. Many thanks for your 
dedication, inspiration and all the good advices that you gave me during this process. 
I also thank Claes who gave me the opportunity to learn more about ports characteristics, 
voyages, berths, shipping companies voyage preferences and costs; certainly our 
conversations inspired me to write this extensive research. 
Many thanks to my family.
A profound thank is for Hannah G. for proofreading during the nights this extensive 
research in a field totally unknown. 
And finally, a particular thank is dedicated to Marcus Lange, from Gothenburg University, 
for the last two years of patience dealing with me.
Pag.  II
To My mother Emilia, 
 my brother Fabrizio, 
and my girlfriend Hannah G.  
Pag.  III
TABLE OF CONTENTS 
Abstract I
Acknowledgement II
List of Images VIII
List of Figures IX
List of Tables XI
Abbreviations XIV
Definitions XV
1. INTRODUCTION 1
1.1 Background 1
1.2 Problem Discussion 3
1.3 Purpose of the Study 4
1.3.1 Study Steps 7
1.4 Comparison of the Port’s Competitors 8
1.5 Scope and Limitation - Problems Related to the Research 9
1.6 Expected Results 10
2. BACKGROUND - SUPPLY CHAIN 11
2.1 Supply Chain 11
2.1.1 Supply Chain Network 13
2.2 Logistics Strategy 14
2.3 Logistics Costs Breakdown 16
2.4 Transport Strategy and Network 16
3. BACKGROUND - WAREHOUSING 20
3.1 Warehousing 20
3.2 Warehouse Facility Location Background 22
3.3 Facility Location Strategy 23
3.4 Strategic Issues Affecting Warehousing 27
3.5 Warehouse Vs DC 29
3.6 The Warehouse of the Future 30
4. BACKGROUND - MARITIME 31
4.1 Ports as a Valuable Step in the Logistics Chain 31
Pag.  IV
4.2 Port as a Logistics Centre 33
4.3 Port-centric Logistics 34
4.3.1 Examples from the United Kingdom 37
4.4 Port Hinterland 39
4.5 Logistics HUB 39
4.6 Port Services 40
4.7 Port Choice and Shipping Lines 41
4.8 Port Competition and Measurements 41
4.8.1 Interport Competition 42
4.8.2 Port Competitiveness 43
4.8.3 Indicator Port Performance 43
4.8.4 Port Efficiency 44
4.9 Freeport Zone 45
5. BACKGROUND E-COMMERCE  47
5.1 E-Commerce Overview 47
5.2 E-Retailers Market Evolution 49
5.3 Online Retailers 50
5.4 Online Purchase and Distribution 51
6. BACKGROUND - E-BUYERS 55
6.1 E-Buyer Evolution 55
6.2 E-buyer Characteristics 56
6.3 The Components of Customer Service 58
6.4 The Importance of Customer Service 59
6.5 Online Environmental Impact 61
7. METHODOLOGY 62
7.1 Classifying Research 62
7.2 Paradigm 63
7.3 Literature Collection 64
7.4 Data Collection 66
7.5 Modeling 66
8. ANALYSIS - TRADE 68
8.1 Total Import-Export by the Selected Countries 69
Pag.  V
8.2 Denmark Trade 72
8.3 Finland Trade 74
8.4 Norway Trade 76
8.5 Sweden Trade 78
8.6 Comparing the Average Value 80
8.7 Comments 80
9. ANALYSIS - MARITIME 82
9.1 Maritime Freight by Country 82
9.1.1 Denmark 82
9.1.2 Norway 83
9.1.3 Sweden 84
9.1.4 Comparing the Freight Results 84
9.2 Ports Overview 85
9.3 Container Traffic for Selected European Ports 88
9.4 Ports’ Traffic Data 90
9.5 Ports Characteristics Overview 91
9.5.1 Berth descriptions 95
9.6 Ports’ Characteristics Analysis 102
9.7 Port’s Latest Developments 106
9.7.1 Port of Copenhagen-Malmo (CMP) 106
9.7.2 Port of Oslo 106
9.7.3 Port of Stockholm 107
9.7.4 Port of Gothenburg 107
9.8 Voyage Calculation 110
9.9 Comments 111
10. ANALYSIS - POPULATION - E-BUYERS 113
10.1 Country’s Economy and Population Overview 113
10.2 Denmark 117
10.3 Finland 117
10.4 Norway 118
10.5 Sweden 119
10.6 E-buyers Characteristics and Retailing 120
Pag.  VI
10.7 Comments 124
11. ANALYSIS - WAREHOUSE LOCATION 125
11.1 Scandinavian Centre of Gravity 125
11.2 Centre of Gravity and City’s Distance 128
12.3 Time range 132
11.4 Road-Rail and Emissions calculation 135
11.5 Investment Considerations 139
12.4 Comments 141
12. CONCLUSIONS 144
12.1 Future Research 147
REFERENCES 148
Appendix “A” - HS Codes 163
Appendix “B” - Overview Trade Countries 166
Appendix “C” - Detail trade Denmark 168
Appendix “D” - Detail trade Finland 174
Appendix “E” - Detail trade Norway 180
Appendix “F” - Detail trade Sweden 186
Appendix “G” - Ports Characteristics 192
G.1 Port description 196
G.1.1 General Overview 196
Appendix “H” - containerships by Port 200
Appendix “I” - Voyage Costs 206
Appendix “L” - Population details 210
Pag.  VII
LIST OF IMAGES 
Image 1.2 European Ports and Corridors 5
Image 1.3: Warehouses Location 6
Image 1.0 Research Steps 7
Image 1.1 Topics Covered in this Research 8
Image 2.1 Supply Chain Literature Investigation 11
Image 2.2 Immediate SC for an Individual Firm 12
Image 2.3 Centripetal and Centrifugal Structure (Rodrigue, 2016a) 18
Image 2.4 Point-to-Point Vs Hub-and-Spoke (Rodrigue, 2016b) 18
Image 2.5 Type of Networks (Rodrigue, 2016c) 19
Image 3.1 Warehousing Literature Investigation 20
Image 3.2 The Triangle of Decision making 24
Image 4.1 Maritime Literature Investigation 31
Image 5.1 E-commerce Literature Investigation 47
Image 5.2: Evolution of retail freight distribution 52
Image 6.1 E-Buyers’ Literature Investigation 55
Image 6.2 The Constituent Parts of Total Order Fulfilment Cycle Time 59
Image 6.3 Core Product Versus Product ‘Surround’: 59
Image 6.4 The "Right" Service 60
Image 7.1 Study process - Methodology 62
Image 8.1 Study Process - Trade Analysis 68
Image 9.1 Study Process Maritime Secto 82
Image 9.2 New PoG Logistics Park 108
Image 10.1 Study process - E-buyers Analysis 113
Image 10.2 Population Concentration by Country 116
Image 11.1 Study process - Warehousing 125
Image 11.2 Centres of Gravity in Scandinavia 127
Image 12.1 Summary Research 144
Pag.  VIII
LIST OF FIGURES
Figure 8.1  Import-Export Value Selected Countries 2015 59
Figure 8.2 Export - Selected HS Category by Country 2015 60
Figure 8.3 Import - Selected HS Category by Country 2015 61
Figure 8.4 Denmark - Top 5 Import Countries 62
Figure 8.5 Denmark - Top 5 Export Countries 62
Figure 8.6 Denmark, Import/Export 2015 Neighbours Countries 63
Figure 8.7 Finland Top 5 Import Countries 2015 64
Figure 8.8 Finland Top 5 Export Countries 2015 64
Figure 8.9 Finland Import/Export 2015 Neighbours Countries 65
Figure 8.10 Norway - Top 5 Import Countries 2015 66
Figure 8.11 Norway - Top 5 Export Countries 2015 66
Figure 8.12 Norway Import/Export 2015 Neighbours Countries 67
Figure 8.13 Sweden - Top 5 Import Countries 2015 68
Figure 8.14 Sweden - Top 5 Export Countries 2015 68
Figure 8.15 Sweden Import/Export 2015 Neighbours Countries 69
Figure 8.16 Average Analysis - Import/export Countries 70
Figure 9.1 Comparing the Freight Results 75
Figure 9.2 Gross Tonnage by Country and by Port 76
Figure 9.3 Number of Containerships in Specified Ports (inwards) (2014) 77
Figure 9.4 Containers Traffic for Selected Scandinavian Ports (2014) 79
Figure 10.1 Internet & Devices Users 110
Figure 10.2 Devices by Country 111
Figure 10.3 Social Classes by Country 111
Figure 10.4 Population by Segment 112
Figure 10.5 Retailing and Internet 113
Figure C.1 Import Denmark selected HS codes 2015 160
Figure C.2 Export Denmark selected HS codes 2015 162
Figure D.1 Finland Import Data 2015 by HS category 166
Figure D.2 Finland Export Data 2015 by HS Category 168
Figure E.1 Norway Import Data 2015 by HS category 172
Figure E.2 Norway Export Data 2015 by HS category 174
Pag.  IX
Figure F.1 Sweden Import Data 2015 by HS category 178
Figure F.2 Sweden Export Data 2015 by HS category 180
Pag.  X
LIST OF TABLES
Table 2.1 SC Strategies 19
Table 5.1: Logistics Facilities Supporting E-commerce 52
Table 9.1 Denmark Maritime Freight 83
Table 9.2 Norway Maritime Freight 83
Table 9.3 Sweden Maritime Freight 84
Table 9.4 Containers Traffic by Country and Index 88
Table 9.5 Ports’ Traffic Throughput-Containers 2015 90
Table 9.6 Port’s Characteristics 91
Table 9.7 Facilities Available in Ports 93
Table: 9.8 Equipment Available in Ports - Cranes 94
Table 9.9 Port of Stockholm Berth 95
Table 9.10: Port of Malmo Berth 96
Table 9.11 Port of Copenhagen Berth 97
Table 9.12 Port of Oslo Berth 98
Table 9.13 Port of Gothenburg Berth 99
Table 9.14 Extra info 101
Table 9.15 Port’s Crane Tonnes Efficiency Indicator 102
Table 9.16 Performance Indicators 104
Table 9.17 Voyage Calculation 111
Table 10.1 Country Economic Overview 114
Table 10.2 Population Characteristics 115
Table 10.3 Population in Denmark 117
Table 10.4 Population in Finland 117
Table 10.5 Population in Norway 118
Table 10.6 Population in Sweden 119
Table 11.1 Cities Coordinates, Population, and COG 126
Table 11.2 Euclidean Distances from Ports and COG to Cities 129
Table 11.3 Percentage of Customers Covered by Destination 130
Table 11.4 Population Within Specified Range (Euclidean Distance) 131
Table 11.5 Maximum Number of Customers in a Specified Range (Euclidean Distance)
131
Table 11.6 Coordinates Ports and COG 132
Table 11.7 Travel Distances from Ports/COG to Cities 133
Table 11.8 Distances by Time range Single Category 134
Table 11.9 Distances by Time Multiple Categories 134
Pag.  XI
Table 11.10 Energy consumption from Ports/COG to Cities 136
Table 11.11 New Scenario with Container Transport from Ports to COG 1 to Cities137
Table 11.12 Emissions and KM from Shanghai to Dedicated Points (ports and COG 1)
137
Table 11.13 Emissions and KM Merged 138
Table 11.14 Comparing three countries 140
Table A.1 Selected HS Codes by Range (macro category) and by Description (sub-
category) 164
Table B.1 Import-Export Value Selected Countries 166
Table B.2 Export - Selected HS Codes by Country 166
Table B.3 Import - Selected HS codes by Country 167
Table C.1 Denmark Import - Export 2015 168
Table C.2 Denmark - Top 5 Import Countries (Value in USD) 168
Table C.3 Denmark - Top 5 Export Countries (Value in USD) 168
Table C.4 Denmark, Import/Export 2015 Neighbours countries 169
Table C.5.1 Denmark Import Data 2015 by HS category 169
Table C.5.2 Denmark Import Data 2015 by HS Category (Detail) 171
Table C.6.1 Export Denmark selected HS codes 2015 (value in USD) 172
Table C.6.2 Export Denmark selected HS Codes 2015 (value in US$) 173
Table D.1 Finland Import - Export 2015 174
Table D.2 Finland - Top 5 Import Countries (Value in USD) 174
Table D.3 Finland - Top 5 Export Countries (Value in USD) 174
Table D.4 Finland, Import/Export 2015 Neighbours countries 175
Table D.5.1 Finland Import Data 2015 by HS Category 175
Table D.5.2 Finland Import Data 2015 by HS Category (detail) 177
Table D.6.1 Finland Export Data 2015 by HS Category 178
Table E.1 Norway Import Export 2015 180
Table E.2 Norway - Top 5 Import Countries (Value in USD) 180
Table E.3 Norway - Top 5 Export Countries (Value in USD) 180
Table E.4 Norway Import/Export 2015 Neighbours Countries 181
Table E.5.1 Norway Import Data 2015 by HS Category 181
Table E.5.2 Norway Import Data 2015 by HS Category (detail) 183
Table E.6.1 Norway Export Data 2015 by HS Category 184
Table E.6.2 Norway Export Data 2015 by HS Category (detail) 185
Table F.1 Sweden Import/Export 2015 186
Table F.2 Sweden - Top 5 Import Countries (Value in USD) 186
Table F.3 Sweden - Top 5 Export Countries (Value in USD) 186
Pag.  XII
Table F.4 Sweden Import/Export 2015 Neighbours Countries 187
Table F.5.1 Sweden Import Data 2015 by HS Category (value in USD) 187
Table F.5.2 Sweden Import Data 2015 by HS category (value in USD) (detail) 189
Table F.6.1 Sweden Export Data 2015 by HS category (value in USD) 190
Table F.6.2 Sweden Export Data 2015 by HS category (value in USD) detail 191
Table G.1 Ports’ Characteristics a General Overview 192
Table G.2 Ports’ Characteristics Details 194
Table G.3 Berth Length - Depth Analysis 198
Table H.0 Gross Tonnage by Country and by Port 200
Table H.1 Number of Containerships in Specified Ports (inwards) (2014) 200
Table H.2 Containerships by GT Calculus 201
Table H.3 Port’s Calls Performance 202
Table H.4 Port's performance by GT category 203
Table H.5 Total port performance - calls by GT category 204
Table H.6: Port TEUs flows and performance on total 204
Table I.1 Voyage Costs Shanghai - Copenhagen 206
Table I.2 Voyage Costs Shanghai - Oslo 207
Table I.3 Voyage Costs Shanghai - Stockholm 208
Table I.4 Voyage Costs Shanghai - Gothenburg 209
Table L.1 Digital Users 210
Table L.2 Social Classes, Population and median income 210
Table L.3 Retailing Analysis 211
Table L.4 Sales by Sector 211
Pag.  XIII
ABBREVIATIONS 
3PL: Third Party Logistics 
B/L: Bill of Lading 
CMP: Copenhagen-Malmo Port
COG: Centre of Gravity
CUF: Common User Facility
DK: Denmark
DMA : Distribution Management Association 
DWT: Dead Weight Tons 
DPW: Dubai Port World
ETF: Empty Run Factor 
FTL: Full Truck Load 
 FTZ: Foreign Trade Zone
   GSC: Global Supply Chain 
   GRT: Gross Register Tonnage
 LF: Load Factor 
LSP: Logistics Service Providers 
LSCI: liner shipping line index
LSBC: liner shipping bilateral connectivity index
LTL: Less Than Truck Load 
NEP: Northamptonshire Enterprise Partnership
NO: Norway 
OOS: Out of Stock
PoG: Port of Gothenburg 
QR: Quick Response 
RDC: Regional Distribution Centre
ROB: Remaining on Board 
SC: Supply Chain 
SCM : Supply Chain Management 
SCND: Supply Chain Network Design
SE: Sweden 
SHEX: Sunday and Holidays Excluded
TEUs: Twenty-Foot Equivalent Unit
TPC: Tons per Centimeters 
JIT: Just in Time
J4U: Just for You
Pag.  XIV
DEFINITIONS
Corridor, a sequence of nodes and links supporting modal flows of passengers or 
freight. They are generally concentrated along a communication axis, have a linear 
orientation and usually serve a gateway.
Cross-dock warehouse, referred to the meeting place for products to move from 
inbound trucks to outbound trucks. 
D time, ‘Demand and delivery time’ that the customer experiences between placing 
the order and getting the goods. See also P time. 
Euclidean distance represents the distance as a simple function of a straight line 
between two locations where distance is expressed in geographical units such as 
kilometers (or miles). Commonly used to provide an approximation of distance, but 
rarely has a practical use (Ballou, 1999).
Feeder, a node that is linked to a hub. It organizes the direction of flows along a 
corridor and can be considered as a consolidation and distribution point.
Flow, the amount of traffic that circulates on a link between two nodes and the 
amount of traffic going through a node.
Gateway, a node that is connecting two different systems of circulation that are 
usually separate networks and that acts as compulsory passage for various flows. 
An intermodal function is performed so that passengers or freight are transferred 
from one network to the other.
Green Logistics, “Supply chain management practices and strategies that reduce 
the environmental and energy footprint of freight distribution. It focuses on material 
handling, waste management, packaging and transport.” It is characterised by 
Reduction of costs; Integrated supply chains (JIT and DTD); Increasing system-
wide efficiency of the distribution system through network changes (Hub-and-spoke 
structure); Reliable and on-time distribution of freight and passengers; Increased 
business opportunities and diversification of the supply chains (Rodrigue, 2016c).
Hub, a node that is handling a substantial amount of traffic and connects elements 
of the same transport network, or different scales of the network (e.g. regional and 
international).
Hub Warehouse or Central Warehouse, refers to a warehouse that consolidates 
products to be shipped to other warehouses in the system before moving on to 
Pag.  XV
customers. The other warehouses in the network are typically called spokes or 
regional warehouses. 
Link, Physical transport infrastructures that enable connection between two nodes.
Liner Shipping Connectivity Index captures how well countries are connected to 
global shipping networks (UNCTAD) (see appendix “H” for details).
Liner shipping bilateral connectivity index: indicates a country pair's integration 
level into global liner shipping networks (UNCTAD) (see appendix “H” for details).
Logistical distance includes physical flows, but also a set of activities necessary 
for the management of these flows. For freight movements, among the most 
significant tasks are order processing, packing, sorting and inventory management. 
Geographical distance units are less relevant in this assessment, but the factors of 
costs and time are very significant (Ballou, 1999).
MHE, Materials handling equipment, e.g. forklift truck
  NCFRP, National Cooperative Freight Research Program
NRI, Networked Readiness Index measures, on a scale from 1 (worst) to 7 (best), 
the performance of 143 economies in leveraging information and communications 
technologies to boost competitiveness and well-being (World Economic Forum, 
2016)
Node, Any location that has access to a transportation network.
Plant Attached Warehouse, it refers to a warehouse that is attached to a 
manufacturing plant. When the company has a plant-attached warehouse, the 
standalone warehouse is sometimes called forward warehouse, meaning it is 
placed “forward” or out closer to customers.
P Time, ’Procurement and Production’ time is the real time that it takes to produce 
a customer order. In general, this is much greater than the D time that the customer 
experiences. The higher the P:D ratio, the more stock will there be in the system 
and the more will be the reliance on the forecast. 
Scandinavia refers to the following countries: Denmark, Finland, Norway an 
Sweden. Nordic Countries is used to refer to the same geographic area. 
Transport Distance is suggested to be used for the existing structure of the 
transport network. In a simple form involving only one mode, it is a routing exercise 
Pag.  XVI
considering the shortest path between two points. In a more complex form, it 
concerns the set of physical activities related to transportation, such as loading, 
unloading and transshipment, are considered (Ballou, 1999).
Transportation nodes, they serve as access point to a distribution system or as 
transshipment/intermediary locations within a transport network. 
Transportation networks, the spatial structure and organization of transport 
infrastructures and terminals.
Pag.  XVII
1. INTRODUCTION 
This section starts with a presentation of the background of the study, and it conducts the 
reader through the general idea of the research. The investigation concerns the analysis of 
the global supply chain, and in particular from the maritime point of view. Ports, in a 
modern era, play a key role in transport due to the higher number of TEUs managed and 
transported by intermodal transport.
1.1 Background 
The traditional concept of ports, effectively refers to a border crossing for international 
carriers. Cargo and ships coming to and crossing the border are assessed charges for 
their use of port facilities and services. The port logistics chain consists of a variety of 
nodes through which the ship and cargo move. The chain starts at the entrance to the 
harbour and usually ends as the cargo passes through the port gate after it is nationalised 
and claimed by the consignee. 
Ports have been playing an increasingly important role in our trading system. Trade 
liberalization and the development of land infrastructure have abolished national 
(economic) borders and captive hinterlands, obliging ports to compete fiercely for custom, 
particularly transshipment cargo transported in containers through marine terminals. 
Greater carrier choice in routing cargo and parallel advances in logistics and supply chain 
management have thus changed competition from one between ports to one between 
supply chains (Cullinane, 2011, p. 363). 
The new expectations of ports are today clearly felt by port administrations who realize, 
often painfully, that the benefits of fine-tuning supply chains can be easily withered away 
by bottlenecks in inefficient ports (Haralambides et al, 2002). This realization has led to a 
global restructuring of the port industry. 
Ports, in order to be competitive in the global maritime supply chain, have started 
improving the core business elements and, furthermore, identifying new business 
opportunities to achieve better economical performances. To deal with these requirements, 
shipping companies have integrated horizontally through mergers, acquisitions and 
strategic alliances, and vertically through operating dedicated terminals and by providing 
integrated logistics and intermodal services (Notteboom, 2004). Additionally, shipping 
companies have rearranged service networks with the dual aim of global coverage and 
diversification. The reactions of shipping companies ultimately affect every facet of the 
maritime industry, especially port operations (Slack et al, 2001).
The main challenges ports face from this structural change is that their main customers, 
the shipping lines, are becoming more powerful with stronger bargaining power, and that 
competition between ports is getting more intense both at inter-port and intra-port levels. 
Pag.  1
Many studies suggest that ports have had to evolve across the range of their activities to 
cope with the challenges (Notteboom and Winkelmans, 2001; Robinson, 2002; Carbone 
and De Martino, 2003).
From the external perspective of the performance model “Service”, particular attention is 
focused on the relationship with customers; Notteboom and Winkelmans (2001) confirm 
that the seaports likely to succeed in the twenty-first century are those that are customer-
led, which understand customer needs, and which can offer best-in-class performance. 
With this focus on adopting a customer-oriented philosophy, ports are expected to provide 
a high quality service at the lowest cost possible, satisfying customers’ increasingly 
complicated requirements (Marlow and Paixao Casaca, 2003). 
Offering lower service price is one of the inevitable strategies used to attract lines that are 
themselves under huge pressure to reduce total shipping costs. In reality, many port 
authorities and individual terminals attempt to secure footloose transshipment cargo by 
lowering port charges for container lines using their terminals as load centres. However, 
sustainable competitive advantage cannot be achieved by becoming the lowest-cost 
service provider (Notteboom and Winkelmans, 2001). Delivering service quality and 
customer-oriented practices, such as flexible and responsive service provision, is essential 
for success and survival in today’s competitive port industry.
Logistical performance models deal with issues of vertical and horizontal integration of 
ports along supply chain and transport channels. Several researchers demonstrate that 
ports compete not simply on the basis of operational efficiency or location, but on the basis 
that they are embedded in chains that offer shippers greater value (Robinson, 2002). 
Additionally the seamless, door-to-door philosophy has transformed terminal operators into 
logistics organizations (Notteboom and Winkelmans, 2001). It is also suggested that port 
networking with overseas and neighbouring ports improves a port’s functioning in the 
global transport system through the exchange of knowledge and ideas and helps prevent 
port authorities from wasting scarce resources on inter-port competition. 
It has been demonstrated that manufacturing companies have realized the necessity of 
managing supply chains effectively in response to the globalization of the economy and 
intensifying competition, and therefore adopted new strategies such as supply chain 
management (SCM), global sourcing and outsourcing of certain functions, for example 
logistics (Lambert and Cooper, 2000; Cho and Kang, 2001; Rabinovich et al, 1999). Such 
new strategies require transportation companies both to cover a wider geographical area 
and to provide a wider range of services to meet increasingly diversified demand patterns 
with lower price and higher quality than before (Heaver, 2001; Slack et al, 1996).
The focus of this thesis is the discussion of the role of ports, and the (changing) role of 
ports in supply chains, a role which can vary from that of simple transshipment hub to 
important logistics node, and which in turn is heavily dependent upon the supply chain 
strategies of those who use these ports. A better supply chain integration can be achieved 
Pag.  2
through greater collaboration and coordination of functions across supply chains. This 
means partnerships, alliances and networks that are created within and between 
organizations. This research focuses on e-retailers’ use of port infrastructures and the role 
that warehouse location can play in satisfying customer demand through shorter lead 
times, with positive consequences for e-consumers.
E-retailers’ warehouse location strategy is one of the main focal points of this research. 
Retailers and online retailers manage a global supply chain, because they are searching 
for low-cost production, ability to distribute products effectively from far-spread points of 
production to multiple locations for purchase and then consumption. Retailers now refer to 
global supply rather than global production and they are aware of the need to manage 
business globally; in some cases this means repatriating some production to meet the 
consumer ‘speed’ challenge. (Fernie and Sparks 2015, p. 28)
1.2 Problem Discussion 
The world of e-commerce is booming. China’s primary online marketplace, Taobao, sells 
more today than the top five brick-and-mortar retailers in the country combined. 
The marketplace now offers some 800 million different products online. Significant 
increases in online sales are expected in most parts of the world, but especially in 
developed countries and emerging countries. The forecast for Europe is an 85 per cent 
increase in the next few years. Global supply chain will feel the pressure to be part of the 
value-added solution to the market (Hult, Closs, and Frayer, 2014, p. 41).
Consumers are increasingly demanding the best at a good price. Global SCs are a major 
part of the solution. Specifically, companies need to have a well-working global supply 
chain infrastructure available to them to distribute their products to a larger number of 
potential customers than ever before. Customers want new products with more features 
and better quality - all costly propositions. Using global supply chains helps offset these 
costs through potentially larger market coverage involving more customers (Hult, Closs, 
and Frayer, 2014, p. 48).
Watson (2013, p. 64-65) refers to supply chain service design, where he considers the 
relevance of minimising the average transport distance, and maximising the percentage of 
customers within a certain distance.
The best way to think about network design is that it gives you the opportunity to meet 
your service promises.
Mallard et al (2008, p. 38-39), specify that when analysing the demand for a certain 
product there are several determinants to take into consideration: 
- the price, availability and quality of substitute products; 
- the price, availability and quality of complementary products; 
Pag.  3
- income changes; population changes; popularity effects; speed; reliability; bureaucracy 
and security.
The problem the author is trying to solve is the reduction of lead time for e-buyers in the 
Scandinavian market, through locating warehouses in the port area (port-centric activities 
benefits). Several distribution centres across Europe (e.g. Germany and the Netherlands) 
dispatch products to Sweden, Denmark, Finland and Norway, causing long delivery time. 
The consequences of DCs being located outside Scandinavia are higher costs, 
inefficiencies, customer dissatisfaction, higher greenhouse emissions due to transport and 
congestion, with consequences across the entire supply chain (even in reverse flow).  
1.3 Purpose of the Study 
The purpose of this study is to analyse the factors influencing e-retailers in their choice of 
warehouse (or DC) location, potentially within ports, with the ultimate goal of better 
satisfying demand within a specific geographic area or market. 
Locating the warehouse within the port itself has certain benefits, such as influencing lead 
time and operations of the players involved in the supply chain. 
In this study, the author aims to determine the best-possible location of warehouse to 
satisfy the Scandinavian market, for a specific client. With this in mind, the investigation 
starts with supply chain characteristics, warehouse location strategies (from the investor’s 
point of view), the maritime sector, e-commerce and e-buyers/population. Container ships 
will prefer to call at a specific port when it has a certain level of efficiency and 
competitiveness.
By selecting several research themes that stem from the literature review and are patterns 
across the data analysis, this study helps us to construct an extensive investigation across 
multiple topics in order to answer the central research question. 
This analysis, conducted independently, pays particular attention to the Scandinavian 
ports, and specifically to the Port of Gothenburg (PoG), Port of Oslo, Port of Copenhagen-
Malmo and Port of Stockholm.
The study the author intends to carry out is the analysis of port-centric logistics 
(warehouses) in Gothenburg. This investigation concerns the satisfaction, in primis, of the 
final warehouse users (online retailers), and the relative attractiveness of the PoG 
compared to its competitors.
The research question is this: assuming that all four ports included in the research provide 
warehouses to e-retailers, which location has the most convenient distribution (e.g. short 
lead time and large e-buyer customer base)? How can the Port of Gothenburg (PoG) 
Pag.  4
contribute to the success of online retailers? Which factors create a competitive advantage 
for e-retailers? Which factors influence the choice of location for a warehouse/DC?
The project was jointly developed with the PoG, who selected the main ports. 
Image 1.2 shows a map of trans-european core ports and corridors, including the key 
ports in this research. 
Image 1.2 European Ports and Corridors
How can the Port of Gothenburg (PoG) contribute to the success of online retailers? This 
study focuses on the possibility of the PoG satisfying the growing demand for dedicated 
warehouses and particularly for e-commerce businesses.
The Port of Gothenburg, geographically located in the west of Sweden, represents one of 
the access points to the Scandinavian market. It is the largest port in the Nordic countries. 
The port’s proximity to the market and its physical conditions contribute to its penetration 
of Scandinavia and the Baltic Region (with considerable potential for growth); and the rail 
shuttles and the inland terminals in Sweden and Norway are a major strength. The port 
has the infrastructure and traffic to move goods quickly and conveniently to and from the 
Pag.  5
Oslo
Stockholm
Gothenburg
CMP
Source: personal elaboration, based on EU TEN-T corridors. 
port by rail. Also, there are large areas of space that can be used, both for quays and other 
terminal operations, to support the port’s growth.
The PoG owns approximately 60 hectares of land, strategically located nearby the 
highway and the railway line (Image 1.3 Warehouses Location, point B). The area is 1km 
(ca.) from the container terminal (Image 1.3, point A). In this case the containers are able 
to move rapidly and directly to the warehouse/DC with positive consequences across the 
SC. 
Image 1.3: Warehouses Location
The project the PoG intends to realise is the construction of new warehouses (ca. 30 
hectare), located nearby the port, with proper connections to the railway network, highway 
and Scandinavian hinterland. The warehouses have different dimensions (from 15 to 35 
metres high), in order to satisfy different customers’ demands; several international 
investors are co-financing the project, already. The total investment in the project to date is 
SEK 4 billion = $490 million US = 430,1 million Euros, including SEK 1 Billion from PoG). 
These investors are NCC Property Development, Prologis Nordic, Eklandia Fastighets, 
and Bockasjo. (Sea-web.com, 2015b)
Pag.  6
Source: personal elaboration, based on Gothenburg Google Maps. 
The PoG identified large online retailers as the final users of the warehouses, those with 
large throughput and adequate market share. Large online retailers that trade in apparel, 
fashion, electronics, sports equipment, household goods and books (for example), with 
high value products may be interested in the infrastructure; such retailers as Amazon, 
Alibaba, Zalando, Decathlon, XXL, Zara, H&M, Intersport and Team Sportia.
Those companies, according to their business strategies, will consider the possibility of 
investing in a new warehouse or distribution centre (DC) in Gothenburg, in order to 
penetrate the Scandinavian market, satisfying customer’s demands.  
1.3.1 Study Steps
Image 1.0 (Research Steps) shows the main steps undertaken in this research. The 
starting point is E-business Distribution Centre in Scandinavia & Port Competitiveness, 
followed by a review of the relevant literature to support the research, the methodology 
applied to the research, an analysis in line with the literature review and conclusions, 
where the author’s findings in relation to the research questions are summarised.
Image 1.0 Research Steps
In order to have an appropriate method of study and research, several sections have been 
identified and merged in main categories. 
The research topic is the E-business distribution centre in Scandinavia & Port 
competitiveness; the literature review include the section no. 2-3-4-5-6; the 
methodology in section 7; the analysis in sections 8-9-10-11; and the conclusions and 
in section 13.
Pag.  7
In order for the reader to have an understanding of supply chain and the entire research, 
some important assumptions must be introduced, to better view the big picture about the 
warehouses/DC located in a port’s logistics park, and the benefits for the entire SC and its 
network. Image 1.1 shows the main idea, the literature background (main topics) 
considered for this investigation and the key areas (specific topics) relating to the main 
idea. 
Image 1.1 Topics Covered in this Research 
1.4 Comparison of the Port’s Competitors
The empirical analysis compares the characteristics of the following Scandinavian ports: 
Oslo, Gothenburg, Copenhagen-Malmo and Stockholm. 
The study includes a shipping cost analysis (from Asia to Europe; voyage, port charges, 
etc.), port performances, to better identify the more efficient port. 
Afterwards a port’s warehouse simulation location is conducted to “compare” the 
Scandinavian distribution system. 
Pag.  8
Source: personal elaboration
The main purpose of the study is to conduct an independent analysis about the attraction 
of big online retailers in Gothenburg, and using the new warehouses to satisfy online 
retailing markets in Norway, Sweden, Finland, and Denmark. 
1.5 Scope and Limitation - Problems Related to the Research
The author’s goal is to guide the reader through the general concepts of supply chain, 
maritime infrastructure, warehousing, e-retailers and e-buyer characteristics. 
The analysis comprises the following areas: 
1. The trade flow (for specific products) in the Scandinavian countries 
2. The maritime sector
3. Population characteristics (e-buyers) 
4. The identification of the warehouse location that better satisfies the Scandinavian 
market. 
The analysis is quite extensive and due to restriction in length (by the University) the 
author tried to summarise all data in the main section; the supporting analysis is presented 
in the Appendix. 
The most recent data was selected, dating from 2015 where available. Due to data 
availability, some data is from 2014 and 2013. 
Regarding trade flow, the following elements are not considered: the grocery market, fresh 
food, frozen food, flowers and all products not part of the online retailing business; 
appendix “A” identifies the selected categories (categories chosen in accordance with the 
PoG). 
Regarding the maritime sector, port characteristics are taken into consideration, as are the 
ports’ locations. It was necessary to combine information from multiple sources to carry out 
a comprehensive analysis. This thesis will not to take global port operators (GPOs) into 
consideration. 
Regarding e-buyers and Scandinavian population characteristics, one limitation was the 
availability of data across all ports, such as the income by age group, income by 
educational level and number of children per adult.
Regarding warehouse location analysis, the investigation does not cover the type of 
infrastructure to build, nor the dimensions or internal facility layout, nor traffic flow from/to 
the warehouse to the customer; only the location. Centralised and decentralised 
warehouses are not part of this investigation. 
The identification of the retailers and their market shares was not considered. 
Pag.  9
The study will not take into consideration the reverse flow analysis (reverse logistics); 
transportation costs are not analysed either.
Considering that there are many aspects to take into consideration, from the most general 
to the most specific, this research focuses only on what is presented in the previous 
paragraphs (in Section1) and in the methodology section; all the rest that wasn’t 
mentioned is part of future research (see last section).  
1.6 Expected Results 
The result of the study is to understand the most appropriate location where set-up a new 
warehouse for online retailers, when investing in the Scandinavian market, in order to 
satisfy the higher number of e-customer in the shortest range time/distance. Another 
expected result is the show the ports and countries’ performances (economics, population, 
income, etc.) and supporting the investment “localisation” in the most appropriate country/
city. 
The aim is to set up a ranking, among the ports, for the considered parameters.
Considering the transport system, the positive effects on the environment are also 
considered, in order to build a more sustainable world and sustainable e-shopping system.
The facility location is influenced by the trade flows and population characteristics (e.g. 
income), and the final ranking will sum up the results. 
Pag.  10
2. BACKGROUND - SUPPLY CHAIN 
This section presents the supply chain theoretical framework, which begins with describing 
the general characteristics and the network planning, and different definitions are provided. 
The section continues with the logistics strategy, and logistics factors related to the 
performance. Image 2.1 shows the sub topics investigated in this section. 
Image 2.1 Supply Chain Literature Investigation 
2.1 Supply Chain
According to Ballou (1999) there are different activities that make up business logistics 
(SCM). These vary from firm to firm, depending on a firm’s particular organisational 
structure, management’s honest differences of opinion about what constitutes logistics, 
and the importance of individual activities to its operations.
 
The Council of Logistics Management (CLM) gives this definition: 
“Logistics is the process of planning, implementing, and controlling the efficient, cost-
effective flow and storage of raw materials, in-process inventory, finished goods and 
related information from point of origin to point of consumption for the purpose of 
conforming to customer requirement”.
Consider also the following definition provided by “The Council of Supply Chain 
Management Professional” (2016): logistics management is part of supply chain 
management that plans, implements, and controls the efficient, effective forward and 
reverses flow and storage of goods, services and related information between the point of 
origin and the point of consumption in order to meet customers' requirements.”
Ballou (1999) suggests the typical steps for a general supply chain of an Individual Firm 
(Image 2.2).  
Pag.  11
Source: personal elaboration
Image 2.2 Immediate SC for an Individual Firm 
The same CLM (Oak Brook) states: 
“The components of a typical logistics systems are customer service, demand forecasting, 
distribution, communications, inventory control, material handling, order processing, parts 
of service support, plant and warehouse site selection (location analysis), purchasing, 
packaging, return goods handling, salvage and scrap disposal, traffic and transportation, 
warehousing and storage.”
According to Ballou (1999), logistics costs increase in proportion to the level of customer 
service provided, such that setting the standards for service  also affects the logistics costs 
to support that level of service. Setting very high service requirements can force logistics 
costs to exceedingly high levels. For instance transportation and inventories are the 
primary cost-absorbing logistics activities. Experience has shown that each will represent 
one-half to two-thirds of total logistics costs. It is transportation that adds place value to 
product and services, whereas inventories add time value. 
Transportation is essential because no modern firm can operate without providing for the 
movement of its raw materials and/or finished products. 
Ballou (1999), mention the importance of logistics and it is about creating value - value for 
customers and suppliers of the firm, and value for the firm’s stakeholders. Value in logistics 
Pag.  12
Note Image 2.2: source Ballou (1999) image 1.1, and adapted)
is expressed in terms of time and place. Products and services have no value unless they 
are in the possession of the customers when (time) and where (place) they wish to 
consume them. Logistics add significant value to customer value; by moving the product 
toward the customer or making an inventory available in a timely manner value has been 
created for the customer that was not there previously. 
Logistics is important to the company’s strategy because most firms invest time in finding 
new ways to differentiate their products from their competitors, but when management 
recognise that logistics impacts on a significant portion of a firm’s costs and that the result 
of decisions made about the supply chain yields different levels of customer service, it is in 
a position to use this effectively to penetrate new markets, to increase market share, and 
to generate profits. (Ballou, 1999, 13)
According to Fernie and Sparks (2015, p. 2), the stock itself contains value and might not 
sell or could become obsolete. Warehouses and distribution centres (DCs) are generally 
expensive to build, operate and maintain. Vehicles to transport goods between 
warehouses and shops are not cheap, both in terms of capital and, increasingly, running 
costs. There is thus a cost imperative to make sure that logistics is carried out effectively 
and efficiently, through the most appropriate allocation of resources along the supply 
chain.
Retailers are one part of the supply system; they are involved in selling goods and 
services to the consumer. For this they draw upon manufacturers to provide the necessary 
products. They may outsource certain functions, e.g. transport, warehousing, to specialist 
logistics services providers. Retailers therefore have a direct interest in the logistics 
systems of their suppliers and other intermediaries. (Fernie and Sparks 2015)
Sparks (1998, 2010), refers to the concept of logistics mix as an integrated part in retailer 
supply chain, because these are the essential elements of logistics management.
Being aware of consumer demands and requirements is vital for all players involved in the 
system. By contrast, if company “X” is highly focused on consumer demands and the 
provision of  excessively high service levels, this will cause cost problems for retailers. If 
the system is too responsive at any price, then the operation is likely to be unsustainable. 
The transformation in retail supply chains is thus about appropriate balances and activities 
and the right approach to supply and demand.
2.1.1 Supply Chain Network 
According to Watson et al (2013) supply chain network design should consider the 
geography and business strategy of the company; several elements influence the SC 
network planning and require the player to make  trade-offs: 
- Transportation costs: because the company is interested in moving product from its 
original source to the final destination; by contrast, the location of the facilities 
Pag.  13
determines access to transport infrastructure such as highways, ports, airports, 
railheads; and different locations may have different transportation rates. 
- Service Level: the location of the company infrastructure affects the customer’s delivery 
time 
- Local Labor: Skills, Materials and Utilities: the location of facilities is influenced by the 
labor sector, ability to find required skills, cost of local material, and cost of utilities 
- Taxes: facilities can be taxed directly according to their location and to the operations 
performed. Taxes have to be considered when shipping a product to and from the 
company’s locations
- Carbon Emissions: the location of facilities in certain areas, minimise distance traveled 
and/or transportation costs, with reduced CO2 emissions; on the other hand if the facility 
requires a high level of electricity, the appropriate location is near low-emission power 
plants - with reduction in emissions.
According to Hult, Closs, and Frayer (2014, p. 42), the infrastructure for global supply 
chain is becoming much better, with numerous options for global and regional channels in 
most parts of the world. Shipping routes are being reconfigured, leverage points in the 
world are being reformulated, and value is being added to global supply chains.The 
forecast is that the infrastructure for global supply chains will improve by 11 per cent in the 
next five years. 
Global firms are experiencing several issues, such as global sourcing, including sourcing 
from foreign markets. Firms now source globally to achieve the best combination of quality, 
cost, and ultimately value. (Hult, Closs, and Frayer (2014, p. 41)
2.2 Logistics Strategy 
The primary goal of logistics is to “minimize" firms’ costs and maximise customer 
satisfaction by coordinating flow of materials and information in the most efficient way, and 
by providing a service to customers in a timely fashion and at a reasonable price (Coyle et 
al, 2009; OLeary-Kelly and Flores, 2002). 
Retailing and logistics are concerned with product availability. Many have described this as 
‘getting the right products to the right place at the right time’. Unfortunately, however, that 
description does not do justice to the amount of effort that has to go into a logistics supply 
system and the multitude of ways that supply systems can go wrong. 
Retailers must be concerned with the flows of product and information both within the 
business and in the wider supply chain. In order to make products available retailers have 
to manage their logistics in terms of product movement and demand management. They 
need to know what is selling in (and through) their stores and their websites and both 
anticipate and react quickly to changes in this demand. At the same time they need to be 
able to move less demand-volatile products in an efficient and cost-effective manner 
(Fernie and Sparks 2015, p. 3). The real management ‘trick’ is in making product 
availability look easy. 
Pag.  14
Innovative approaches to logistics strategy can give competitive advantages; It has been 
suggested that a logistics strategy has three objectives 1) cost reduction,  2) capital 
reduction and, 3) service improvement. 
1. Cost reduction is a strategy directed towards minimising the variable costs associated 
with movement and storage. The best strategy is usually formulated by evaluating 
alternative courses on auction, such as choosing among different warehouses 
locations or selecting among alternative transport modes. Certainly a profit 
maximisation is the primary goal to achieve. 
2. Capital reduction, is the strategy directed toward minimising the level of investment in 
the logistics system.  Maximising the return on investment is the motivation for this 
strategy. Shipping direct to customers to avoid warehousing, choosing public 
warehouses over privately owned warehouses, selecting just in time supply approach 
rather than stocking to inventory, or using third party providers of logistics services are 
examples. 
3. Service improvement strategies usually recognise that revenues depend on the level of 
logistics service provided. Although costs increase rapidly with increased levels of 
logistics customer service, the increased revenues may more than offset the higher 
costs. To be effective, the service strategy is developed in contrast with that provided 
by competition. 
A proactive logistics strategy often begins with business goals and customer service 
requirements. These have been referred to as ”attack strategies” to meet competition 
(Ballou, 1999). 
As mentioned earlier, “time” plays a key role in the entire supply chain, and particularly in 
efficient distribution. According to Christopher and Peck (2003) there are three dimensions 
to keep to consider if an organization is interested in being responsive to market changes 
(time-based competition): 
1. Time to market: the speed of bringing a business opportunity to market; 
2. Time to serve: the speed of meeting a customer’s order; and 
3. Time to react: the speed of adjusting output to volatile responses in demand. 
According to Christopher and Peck (2003), the three time-based competition elements are 
used to develop strategies for lead time management. 
Refer to Christopher and Peck (2003) for more information. 
Fernie and Sparks (2015, p. 28-29) are concerned with availability, supply chain 
competition, and relationship matters. Availability is meeting the customers’ demand, and 
retailers are concerned about availability of products in store and online. 
Supply chain compete: in the past competition was mainly between retailers, at the 
horizontal level only. In the modern era, competition pass by the supply chains, between 
production and consumption. The retail store and website are the recipients of both 
changing demand and supply. Nowadays retailers are competing not only horizontally but 
Pag.  15
also vertically, in terms of the efficiency and effectiveness of their supply systems; retailers 
need to expand their customer’s penetration, delivering products in customer’s hands. 
Relationship matter: in order to focus mainly on their core business (companies), they 
have utilized logistics services providers to carry out many logistics activities (coordination, 
management and control). The number of direct partners and activities have in many 
cases been reduced considerably. 
2.3 Logistics Costs Breakdown
According to Rodrigue (2016a), total logistic costs reveal much about the locational 
dynamics of logistics activities, particularly distribution centers, since they indicate the 
weight of most important factors. Transportation costs remain the dominant consideration 
as they account for about half of the logistic costs (50.3 per cent). Inventory carrying costs 
are also significant with a share of about one fifth of total costs (21.8 per cent). They 
include the costs of holding goods in inventory (capital costs, warehousing, depreciation, 
insurance, taxation, and obsolescence) and are commonly expressed as a share of the 
inventory value. Labor costs involve the physical handling of goods, including tasks such 
as packaging and labeling (9.5 per cent). Customer service encompasses receiving and 
processing orders from customers (7.8 per cent). Rent location account for 4.3 per cent (of 
logistics costs), administration for 2.7 per cent, and supplies represent 2.2 per cent of 
logistics costs. 
Under such circumstances, distributors are willing to pay higher rents to take advantage 
of a logistics site that offers co-location with an intermodal terminal since this strategy 
enables them to reduce transportation costs, such as drayage, as well to improve their 
time responsiveness (lead time). Therefore, while transportation costs remains the most 
important element of logistics costs, non-spatial components such as inventory carrying 
and labor costs, are significant components that will influence locational choice 
depending on the supply chain.
2.4 Transport Strategy and Network
Transport decisions can involve mode selection, shipment size, and routing and 
scheduling. These decisions are influenced by the proximity of warehouses to customers 
and plants, which, in turn, influence warehouse location. Inventory levels also respond to 
transport decision through shipment size (Ballou, 1999, p.35). 
From a customer service point of view, several elements must be considered in order to 
offer a proper service such as inventory availability, speed of delivery, and order-filling 
speed and accuracy. The costs associated with these factors increase as the level of 
customer service level is raised. Therefore, distribution costs will be quite sensitive to the 
level of customer service provided, especially if it is already at the high level. Customer 
service levels such as facility location, inventory and transportation are major planning 
Pag.  16
areas because of the impact that decisions in these areas have profitability, cash flow, and 
the firm’s return on investment, as aforementioned. Each aspect of the decision is 
interrelated and should not be planned without at least some consideration of the trade-off 
effect (Ballou, 1999, p.35-37). 
 
Ballou (1999) mentioned that another way to look at the logistics planning problem is to 
view it in the abstract as a network of links and nodes. Logistics planning is a design 
problem. The network is to be constructed as a configuration of warehouses, retail outlets 
factories, deployed inventories, transportation services, and information processing 
systems that will achieve an optimum balance between the revenues resulting from the 
level of customer service established by the network design and the costs associated with 
the creation and operation of the network. 
The term network refers to the framework of routes within a system of locations, identified 
as nodes. A route is a single link between two nodes that are part of a larger network. It 
can refer to tangible routes such as roads and rails, or less tangible routes such as air and 
sea corridors (Rodrigue, 2016b). 
In transport geography, it is common to identify several types of transport structures that 
are linked with transportation networks with key elements such as nodes, links, flows, hubs 
or corridors (see “definitions” section). Network structure ranges from centripetal to 
centrifugal in terms of the accessibility they provide to locations (Image 2.3). A centripetal 
network favors a limited number of locations while a centrifugal network tends not convey 
any specific locational advantages (Rodrigue, 2016a). 
According to Rodrigue (2016b), the recent decades have seen the emergence of transport 
hubs, a strongly centripetal form, as a privileged network structure for many types of 
transport services. Evidence underlines that the emergence of hub-and-spoke networks is 
a transitional form of network development rationalizing limited volumes through a limited 
number of routes. When traffic becomes sufficient, direct point-to-point services tend to be 
established as they better reflect the preference of users.
Pag.  17
Image 2.3 Centripetal and Centrifugal Structure (Rodrigue, 2016a)
Image 2.4 Point-to-Point Vs Hub-and-Spoke (Rodrigue, 2016b)
Rodrigue (2016c) points out that hubs, as a network structure, allow a greater flexibility 
within the transport system, through a concentration of flows. For instance, as illustrated in 
image 2.4, a point-to-point network involves 16 independent connections, each to be 
serviced by vehicles and infrastructures. By using a hub-and-spoke structure, only 8 
connections are required. The main advantages of hubs are:
Economies of scale on connections by offering a high frequency of services. For 
instance, instead of one service per day between any two pairs in a point-to-point network, 
four services per day could be possible.
Economies of scale at the hubs, enabling the potential development of an efficient 
distribution system since the hubs handle larger quantities of traffic.
Economies of scope in the use of shared transshipment facilities. This can take several 
dimensions such as lower costs for the users as well as higher quality infrastructures.
Pag.  18
Rodriguez (2016c), (Image 2.5), specifies the difference between centralized, 
decentralised and distributed networks, according to their level of service which is related 
to their structure. 
Centralised is referred to one centre has privileged accessibility and thus represents the 
dominant element of the network and the spatial structure it supports.
Decentralized refers to a network where the centre is still the point of highest accessibility, 
but the network is structured so that sub-centers also have significant levels of 
accessibility.
Distributed,  No centre has a level of accessibility significantly different from the others.
Image 2.5 Type of Networks (Rodrigue, 2016c)
Christopher et al (2006) suggest that ports can have various different roles in the context 
of different supply chain strategies and, building upon the work of Fisher (1997) and 
others, have put forward a taxonomy for selecting global supply chain strategies, where 
two main elements are considered: predictability of demand for products and 
replenishment lead times. It also incorporates lean and agile philosophies as appropriate 
(Mangan, Lalwani, and Fynes, 2008) (table 2.1).
Table 2.1 SC Strategies 
Predictable Demand Unpredictable Demand
Long Lead Time Lean (Plan and Execute) 
Leagile 
(Postponement) 
Short Lead Time Lean (Continuous Replenishment)
Agile 
(Quick Response) 
Source: Christopher et al (2006)
Pag.  19
3. BACKGROUND - WAREHOUSING 
From the author’s point of view, a deeper investigation of warehouses is required, to better 
clarify several elements influencing the choice of this infrastructure adoption, and 
appropriate location. The reader will understand the elements affecting facility location 
strategy and elements (or factors) to consider, the difference between a warehouse and 
DC; another consideration is the flexibility and agility required of modern warehouses, over 
and above their role as simple storage facilities. 
Image 3.1 Warehousing Literature Investigation
Warehousing is an integral part of every logistics system. It plays a vital role in providing 
the desired level of customer service at the lowest possible total cost. Warehousing activity 
is the link between the producer and the customer. Warehousing is defined by Lamber and 
Stock (1993) as that part of a firm’s logistics system that stores products (raw materials, 
parts, goods-in-process, finished goods) between point-of-origin and point-of-consumption, 
and provides information to management on the status, condition, and disposition of items 
being stored. The term distribution centre is also used. However, warehouse is the more 
the generic term. The Transportation-Logistics Dictionary defines a distribution centre as “a 
warehouse of finished goods; also applied to facility from which wholesale and retailer 
orders may be filled; a material warehouse would also be distribution centre for the buyers 
of its stock.” (Lamber and Stock, 1993, p.263).
3.1 Warehousing
According to Lamber and Stock (1993), the importance of warehousing is characterised by 
two basic type of inventories: 1) raw materials, components and parts (physical supply); 
and 2) finished goods (physical distribution). In general it is necessary to hold inventories 
for the following reasons: to achieve transportation economies, to achieve production 
economies, to take advantage of quantity purchase discounts and forward buys, to 
Pag.  20
Source: personal elaboration
maintain a source of supply, to support the firm’s customer policies, to meet changing 
market conditions (e.g. seasonality, demand fluctuations, competition), to overcome the 
time and space differentials that exist between producers and consumers, to accomplish 
least total logistics commensurate with a  desired level of customer service. 
Croucher, Baker, and Rushton (2014), specify the importance of warehouses as an 
integral part of the supply chains in which companies operate. Recent trends, such as 
increasing market volatility, product range proliferation and shortening customer lead 
times, therefore all have an impact on the roles that warehouses are required to perform. 
Warehouses need to be designed and operated in line with the specific requirements of 
the supply chain as a whole. They are therefore justified where they are part of the lowest-
cost supply chain that can be designed to meet the service levels that need to be provided 
to the customers.
The nature of warehouses within supply chains may vary tremendously, and there are 
many different types of classification that can be adopted, for example:
- by the stage in the supply chain: materials, work-in-progress, finished goods or returned 
goods
- by geographic area: for example, a global warehouse may serve the whole world, a 
regional warehouse may serve a number of countries, a national warehouse may serve 
just one country, or a local warehouse may serve a specific region of a country
- by function: for example, inventory holding or sortation (e.g. as a ‘hub’ of a parcel 
carrier);
- by product type, ownership, company usage, area, height, and equipment. 
Ballou (1999) specifies that companies use storage spaces for four basic reasons: 1) to 
reduce transportation-production costs, 2) to coordinate supply and demand, 3) to assist in 
the production process, and 4) to assist in the marketing process 
From a marketing perspective, companies are frequently concerned about the availability 
of products in the marketplace; it means that warehousing is used to put value into a 
product. Where warehousing is adopted to provide the product as close as possible to 
customers, delivery time can often be reduced or supply made readily available. This 
improved customer service through faster delivery can increase sales (Ballou, 1999). 
Another change is the demand for reduction in lead times, shorter product lives, and 
increased inventory turnover, which are linked to such management philosophies as Quick 
Response (QR) and Just in Time (JIT) (Tompkins and Smith 1998, 6-7).
Warehouses are no longer viewed as independent operations but as an important part of a 
firm’s overall logistics strategy, where the goal is to minimise the cost of product delivery 
while still providing excellent customer service. Because of this heightened emphasis on 
the importance of warehousing, third parties (3PL) have increased their role in this part of 
the logistics chain. The 3PL may organise the entire logistics system for a company as well 
as running its warehouses and DCs (Tompkins and Smith 1998, p. 6-7).
Pag.  21
According to Watson et al (2008, p.7), several functions are typical of warehouse such as: 
Consolidation of Products; Production Lot Sizes; Inventory Pre-Build; and 
a) Buffer Lead Time, in this case the warehouse holds products at a location closer to the 
customer in order to provide the next day transport promised each time an order is 
placed;
b) Service Levels, where the product is stored and its proximity to the market where it will 
be consumed (it is also a measure of the service the company can provide). Overall 
cost versus service level is a trade-off in SC network design;
c) Transportation Mode Trade Offs, economies of scale in transportation; allowing the 
shipment of products for long distance with an efficient (and lower cost) mode of 
transportation and then facilitating the changeover to a less efficient (and usually more 
expensive) mode of transportation for shorter trip to the final destination.
Warehouses can be used to support manufacturing, to mix products from multiple 
production facilities for shipment to a single customer, to break bulk or subdivide a large 
shipment of product into many smaller shipments to satisfy the needs of many customers, 
and to combine or consolidate smaller shipments of products into a higher-volume 
shipment. (Lamber and Stock, 1993, p. 265).
Ports can add value to supply chains by 1) sharing information with upstream and 
downstream supply chain partners, 2) undertaking long-term planning with supply chain 
partners, e.g. shipping lines, inland transportation carrier, and shippers, 3) providing the 
flexibility to accommodate changes in the needs of port users, e.g., to launch new 
tailored services, and 4) planning and organising activities beyond their boundaries that 
improve the performance of the supply chain as a whole (Panayides and Song, 2006).
3.2 Warehouse Facility Location Background
As mentioned in the aims of the project, the author is interested in identifying the best 
location for a warehouse/DC for online retailers. Several models have been identified, with 
pros and cons. A short summary is presented: 
The site selection decision can be approached from a macro and micro perspectives. The 
macro perspective examines the issue of where to locate warehouses geographically (in a 
general area) to improve the sourcing of materials and the firm’s market offering (improve 
service and/or reduce cost). The micro perspective examines factors that pinpoint specific 
locations within the larger geographical areas. 
In his macro approach, Edgar Hoover identified three types of location strategies: 
1) market positioned: it locates warehouses nearest to the final customer
2) production positioned : it locates warehouses in close proximity to source of supply or 
production facilities 
3) intermediately positioned:  it locates warehouses at a midpoint between the final 
customer and the producer.
Pag.  22
Weber also developed a model of facility location based on cost minimisation; the optimal 
site was the location that minimised “total transportation costs - the costs of transferring 
raw materials to the plant and finished goods to the market” (Weber, 1929). 
Other geographers included the factors of demand and profitability in the location decision. 
Hoover examined both cost and demand elements of location analysis. His approach 
stressed cost minimisation in determining an optimal location. Additionally, he identified 
that transportation rates and distance were not linearly related; that is, rates increased with 
distance but at a decreasing rate. 
Greenhut (1956) expanded the work of his predecessors by including factors specific to 
the company (e.g., environment, security) and profitability elements in the location choice. 
According to Greenhut, the optimal facility location was the one that maximised profits. 
(Lambert and Stock, 1993) 
Distribution worldwide (1976) magazine published one of the most comprehensive 
overviews of the warehouse site selection decision. The publication identified three 
primary considerations that needed to be examined when determining the site of 
warehouses: marketing aspects, traffic (transportation economics), and location or 
consolidation objectives. (Lambert and Stock, 1993)
Network models, are similar to planar models, with one important exception: possible 
locations are constrained in that they must be on or near a transport network. While planar 
models identify optimal facility locations anywhere in the plane, network models only locate 
facilities on various transport networks such as roads, shipping lines, rail lines, and air 
corridors. Therefore, the number of potential sites is more limited, although the sites 
determined by the model are more realistic (Lambert and Stock, 1993).
3.3 Facility Location Strategy
Facility location background represents the base for analysing in detail the potential 
warehouse/DC; several elements will be investigated and analysed. 
According to Richards (2014), the selection of a warehouse location requires multiple 
criteria to be assessed, including both quantitative and qualitative data.
Richards (2014) states that “Locating a warehouse strategically and in the most cost-
effective geographic location is one of the most important decisions a company will make.”
The geographic placement of the stocking points and their sourcing points create an 
outline for the logistics plan. Fixing the number, location, and size of the facilities and 
assigning market demand to them determines the paths through which products are 
directed to the marketplace.  The proper scope for the facility location problem is to include 
all product movement and associated costs as they take place from plant, vendor, or port 
location through the intermediate stocking points and on to customer locations. Assigning 
customer demand to be served direct from plants, vendors, or ports, or directing it through 
selected stocking points, affects total distribution costs. Finding lowest-cost assignments, 
Pag.  23
or alternatively the maximum profits assignments is the essence of facility location strategy 
Ballou (1999, p. 34).
Image 3.2 The Triangle of Decision making 
For example, in a firm’s fulfillment centres, because of the nature of deliveries, an 
important criterion is the need to be located near to the motorway network to delay the 
latest collection time from the parcel companies and therefore enable companies to 
introduce a later order cut-off time for next day delivery (Richards, 2014).
For instance, in the case of the Inland Empire, Los Angeles port, the location decision for 
distribution centres depends on the availability of relatively low-cost land as well as skilled 
and relatively low-cost labor; easy access to transportation in terms of delivery, so that 
proximity to the ports is a consideration; good means of transportation (roads, railroads, 
airports) from the DCs to the destinations for delivery; and proximity to population centres 
where large proportions of the goods are to be delivered. (Bonacich and Wilson, 2008, 
135). 
Mulcahy (1994) specifies that here are three basic types of site selection project: 
1) International 
2) Macro (national, state region or major city)
3) Micro (within a state, region, or major city) 
International applies when an evaluation of the international site is conducted, because 
the company is looking to determine the best foreign country’s new operation. 
Pag.  24
Source: Ballou, 1999, p. 34 and re-elaborated by the author 
Five major economic factors are considered when selecting the international site: 
transportation, labor, energy and utilities costs, taxes and incentives. 
On the other hand, the international site selection factors are 1) Value of the U.S. dollar 
and the host country’s currency, 2) Stability of the host (foreign) government, 3) Stability of 
the host (foreign) currency, 4) Ability to take profits out the host country and availability of 
barter agreements, 5) Population attitude toward a foreign company, 6) Government 
attitude toward a foreign company, 7) Import and export regulations, 8) Availability of 
required materials handling equipment, 9) Free trade or most-favoured-nation status, 10) 
Culture and customs of the host country. 
Macro site
The Macro (national, state, regional, or major city) site selection project reviews the quality 
of the factors for a region of the country or a particular state or city. The followings are 
considered: 1) Transportation costs: in a particular state or major city site selection project, 
identify the various metropolitan cities of interest to the company; 2) Census information; 
3) Local government and business development agencies; 4) Professional associations 
and business in the area; 5) Labor availability and cost; 6) Taxes and Incentives; 7) 
Availability and costs of energy and utilities; 8) Building and land requirement costs. 
Micro Site 
Mulcahy (1994) suggests that if a company is in the retail business distribution, it must 
focus on a site selection process that includes a micro site selection project. In this case 
the company will identify the site that best serves all retail customers within a small 
geographic area. Several factors must be considered, such as store delivery transportation 
cost and time and land costs. Other site selection factors are considered fixed because the 
potential sites are within the same geographic area. These are labor, taxes, and utility and 
energy. The site selection project covers a 150-200 miles (241-321km) radius of a major 
city. Exact land size, building size, and the geographic location for the new operation are 
considered. 
Mulcahy (1994) suggests several micro site selection methods, in order to determine the 
exact delivery time to all customers: 1) Serve a cluster of customers method, 2) Centre of 
gravity (demand pull or weighted average) method. Explained briefly the different methods: 
- Serve-a-cluster-of-customer method: the project team choose a site that is reasonably 
close to most of the company’s customers (delivery) locations. Ideally, the site is chosen 
is in the centre of the store (customer) cluster. This location rude the delivery trucks 
traveling time and miles from the distribution centre to various customer locations within 
the cluster. 
- Centre-of-gravity (demand pull or weighted average) method: it is a systematic and 
detailed site selection method. This site location is at the centre of gravity and is ideal 
for the distribution centre. 
Pag.  25
According to Watson et al (2013), in order to estimate the distance in miles between any 
two latitude and longitude points the following equation is considered: 
F 3.1)
Dist(mile)ab is the distance from point a to point b. Longa, Lata, Longb, and Latb are the 
longitudes and latitudes expressed as decimal numbers of point a and point b, 
respectively. (to calculate in km, simply change 69 to 111) (Watson et al, 2013, p. 26). 
Instead the mathematical formula for physics centre of gravity (or the weighted average 
location) are the followings F3.2 and F3.3. 
Here Lon represents a city’s longitude, Lat represents its latitude, and P represents a city’s 
population (Watson et al, 2013, p.27). In the analysis section the population is used as the 
weighting factor (also suggested by Watson et al, 2013) because in network problems, 
customer demand is the most common. In other cases, the authors suggest that the  many 
different weighting factors can be used. 
It is confirmed by Watson et al (2013, p.31) that the alternative centre of gravity (COG) is 
the point that minimise the average distance traveled, among the selected points. The 
choice of selecting alternative centres of gravity is due to the fact that the first one might 
be located in shark-infested waters offshore from a mountainous and desert region 
(probably not practical). (Watson et al, 2013)
Reinforcing the elements mentioned by Mulcahy (1994), Richards (2014) confirms, first of 
all, that many companies look at the location and size of customers; then the environment 
will also play a part in the decision-making process. The decision making process about 
warehouse location is influenced by the following factors:
- goods traffic flows
- travel minimisation
- cost of land, rent and rates
Pag.  26
F3.2)
F3.3)
- access to transport networks
- proximity to ports and airports
- availability and cost of utilities
- labor availability, availability of affordable skilled labor
- the potential neighbours (e.g. proximity to oil storage depots can be a negative factor).
A report by DTZ (2013) stated that the global top five least expensive markets for 
warehousing are dominated by the Chinese Tier II cities of Wuhan, Shenyang and 
Chengdu, with Atlanta and Marseille completing the top five. Meanwhile, London Heathrow 
remains the most expensive area globally – at US $313 per square metre per annum, 
followed by Hong Kong, Zurich, Singapore and Oslo.
According to Savills (2013) survey, the top nine requirements for e-retailing operations in 
terms of location were as follows:
- land/rent/lease costs
- access to affordable labor
- expansion space available
- close proximity to parcel hub
- close to motorway network
- central location
- close proximity to consumers
- government incentive
- close proximity to higher skilled labor.
3.4 Strategic Issues Affecting Warehousing
NCFRP (2013) highlights that Freight facilities will only consider locations that fulfill the 
primary objective of moving goods in the most efficient manner from point of origin to 
destination.
Companies and carriers rarely base location decisions on personal relationships, 
government incentives, or regional promotions. These factors are only a consideration 
after a location meets the required criteria for the business to be successful.  
Local officials can make their communities more attractive to freight facilities by providing a 
hospitable climate through appropriate zoning, compatible land use, transportation 
infrastructure, and community support.  
When companies evaluate sites, some criteria are far more important than others. The 
ability to access key markets, availability of efficient transportation, sufficient qualified 
labor, and total costs are considered key criteria.  
Proximity and/or access to markets is the most important driving factor that determines the 
region or community in which a freight facility will locate.  
Freight location decisions rarely respond to a “build it and they will come” approach by the 
public sector, yet it is also true that having the necessary support infrastructure in place 
can be a great incentive if the location is a good one and other factors are positive. 
Pag.  27
Companies will first examine their current and future needs internally and then develop a 
planning framework to determine how best to address these needs externally. 
Site selection decisions typically involve at least the following four steps: 
- Defining the company’s business strategy and the success parameters for the new (or 
relocated) facility. 
- Developing the site selection criteria, usually phased in such a way as to allow a 
progressive evaluation from broad to specific, region to community. 
- Examining the communities and sites directly through on-site visits. 
- Involving three to four sites and communities in detailed discussions and negotiations. 
As noted above, location planning is methodical and iterative. Factors will vary in 
importance throughout the process. For example, access to specific markets, costs, and 
population trends may drive the early stages. 
A secondary screening may involve examining highway and rail networks to determine 
areas with service advantages. 
The location selection process for any freight facility begins with the identification of a 
need. This need may arise from the desire to serve a new market, to merge facilities 
acquired from another company, or to respond to a change in market conditions. 
Furthermore, proximity and/ or access to markets, especially supply chain networks, is the 
single most important factor in determining the location of a freight facility. Most of the 
other site selection factors are used to refine the site selection process to specific, 
sometimes competing, sites. 
Access is expected to accomplish two things: 1) delivery service with speed, predictability, 
and precision that matches or exceeds the competitive standards in the market and 2) 
costs that are as low as possible. 
Retail companies often establish their distribution networks on a concept of overlapping 
circles, each with a radius of approximately 500 miles. Beginning with the factory, this 
builds a supply chain that allows for a one-day drive to the regional distribution centre, 
then the local distribution centre, and finally to stores located in major consumption areas. 
The ability to service a particular customer within a one-day drive is a common service 
expectation and location consideration. This requires both physical proximity to the 
customer and a location within the transportation network, which permits ready movement 
to the customer’s facilities. For a city terminal being operated for pickup and delivery by a 
truck fleet, customer proximity is substantially shorter and the density of customers in the 
region greater. These facilities are situated to minimize total miles within a few-hour 
service radius and require an investment in trucks as well as terminals. 
Depending on the facility type and the markets to be served, access to more than one 
mode of transportation may be required. Communities that successfully attract freight 
facilities are able to efficiently connect points of production or ports of entry to consumers. 
Freight facilities are located near key transportation channels such as: 
- Areas or sites on major highways.  
- Areas where multiple interstate highways converge.  
- Railroad terminals at the edges of their network or at key consumption markets.  
Pag.  28
- Major sea and airports. 
Distribution centres usually need to operate on a 24-hour basis, yet a community may 
have regulations that restrict hours of operation or prohibit truck traffic on a strategically 
located route. Decisions about what mode to use for goods movement are unique to each 
shipper, receiver, and carrier but generally reflect direct transportation costs, reliability, and 
travel time. These factors can vary greatly by mode and region depending on 
transportation infrastructure, available freight carriers, size of the market, and quality of 
freight service. 
Third-Party Shippers 
Instead of co-locating or locating near specific freight infrastructure, some freight 
businesses will rely upon and perhaps locate near third-party shippers or third-party 
logistics (3PL) companies. For example, large retailers who ship most of their own 
merchandise through their distribution centers may also rely upon commercial carriers 
such as FedEx or UPS to ship small packages, such as jewelry, directly from central 
distribution to their stores.
3.5 Warehouse Vs DC
A classification and explanations of warehouses is due, in order to better understand the 
type of infrastructure and its utilisation by the most appropriate player in the supply chain. 
Watson et al (2013, p.8) identify the classification for “warehouse” infrastructure by 
different needs: 
- Distribution centre (DC), typically refer to a warehouse where product is stored and from 
which customer orders are fulfilled. For instance when a customer order a product, the 
DC will pick the items from the inventory and ship to the customer. This type of facility is 
also called mixing centre because it “mix” products from many locations, so the 
customer can place an order form one single location. 
- Cross-dock warehouse
- Plant Attached Warehouse
- Hub Warehouse or Central Warehouse
Rodrigue (2016f), specifies the Distribution Centre as the facility or a group of facilities 
that perform consolidation, warehousing, packaging, decomposition and other functions 
linked with handling freight. The main purpose is to provide value-added services to 
freight, which is stored for relatively shorts periods of time (days or weeks). DCs are often 
in proximity to major transport routes or terminals. They can also perform light 
manufacturing activities such as assembly and labeling. A warehouse on the other hand is 
a facility designed to store goods for longer periods of time. Therefore, a distribution centre 
tends to focus on demand while a warehouse is more driven by supply.
From a locational standpoint, distribution centers mainly rely on trucking, implying a 
preference for suburban locations with good road accessibility supporting a constant 
Pag.  29
traffic. They service regional markets with a 48-hour service window (lead time) on 
average, implying that replenishment orders from their customers are met within that time 
period. Another trend has been the setting of freight distribution clusters where distribution 
activities agglomerate to take advantage of shared infrastructures and accessibility. This 
tends to expand the added-value performed by logistics.
3.6 The Warehouse of the Future
Richards (2014) refers to future warehouses and the forces affecting them as: 
- The Global growing and ageing population 
- The growing economies of not only the BRICS countries (Brazil, Russia, India, China 
and South Africa) but also those of the developing world where consumerism and the 
growth of the internet will put even greater pressure on consumer product 
manufacturers and their warehouses. Consumer awareness and demand for new 
products and services will continue to increase
- As economies grow and the population gets older there will be greater competition for 
staff
- Sustainability will play a significant role in supply chain operations in the future. The 
green lobby will look to the supply chain for initiatives in terms of alternative energy use, 
reduction in CO2 emissions, reduction in waste, reduction in water usage and the use of 
alternative forms of transport. This will include intermodal transport initiatives as well as 
fuel-efficient MHE. Consumers and retailers will also be encouraged to source local 
products, leading to an increase in demand for neighbourhood warehouses
- Fuel and energy costs will continue to rise as fossil fuels continue to decline. 
Companies will look to warehouse automation and the use of greener vehicles whilst 
developers and warehouse operators will be encouraged to consider solar panels, wind 
turbines and the use of waste product for energy production
- The potential introduction of government taxation initiatives to encourage companies to 
reduce their impact on the environment
- An increasing pressure on companies to collaborate and share resources
- Technology will continue to improve, evolve and become more affordable
- With the growth in e-retailing there will be more fulfillment and returns centres as 
opposed to warehouses
- The current trend seems to be towards greater centralization of warehousing, with 
retailers building bigger sheds with more automation, replacing smaller regional centres.
Pag.  30
4. BACKGROUND - MARITIME 
This section focuses on the maritime sector, where the major players are Ports and 
shipping lines. Particular focus is placed on port operations, port efficiency, port 
effectiveness, port hinterland, port services, port-centric logistics, and the choice of 
shipping lines to select the most appropriate port according to several conditions. 
Image 4.1 Maritime Literature Investigation
4.1 Ports as a Valuable Step in the Logistics Chain
Ports have become the most important logistics link in the production, distribution and 
consumption chains of economies worldwide (Sanchez, 2006) and parts of intermodal 
networks, with competition increasingly taking place between complete logistics chains 
instead of between ports (De Lange and Chouly, 2004). The competitiveness of ports 
within logistics chain is thus a much higher priority than it was before. 
The developments in the logistics and port environment have created the need for ports to 
be part of wider logistics networks and to provide value-added services (Verhoeven, 2010). 
In an era of economic globalisation ports are evolving rapidly from being traditional land-
sea interfaces to providers of complete logistics network (UNESCAP and KMI, 2005), a 
value-added logistics services (Bichou and Gray, 2004) and their pre-eminent role in 
international distribution is unlikely to be challenged in the foreseeable future (Notteboom 
and Winkelmans, 2001).
Seaports can evolve from a pure import/export and transshipment centre to a complex of 
trade and industrial functions within a logistics system (IAPH, 1996; UNESCAP and KMI, 
2005). They are the value-adding transfer points (Notteboom, 1998) and central links in 
complex supply and logistics (Banister et al, 1995) and transport chains, providing 
seamless transport facilities (Branch, 1986) with a strong interface with other modes of 
transport services (Branch, 2007; Song, and Panayides, 2012). According to de Langen 
Pag.  31
Source: personal elaboration
(2004) seaports should be regarded as logistics centres, industrial zones and centres of 
trade. Branch (2007) and Nottemboom and Rodrigue (2005) state that the free trade 
zone, the inland clearance depot, the freight village, container freight stations and 
“distriparks” are the components of ports as trading and industrial centre with an 
increasing role in global supply chain management and logistics network structures 
(UNESCAP and KMI, 2005). Woo and Pettit (2009, p. 3) redefine port-supply chain 
integration as “a strategy undertaken by a seaport terminal to integrate various functions 
and organization in a supply chain to become an integral part of the supply chain. 
Panayides (2006) for example notes that: [. . .] the demand for maritime transport nowadays 
cannot be solely considered to be a derived demand emanating from the need for products, 
but rather as an integrated demand emanating from the need to minimise costs, improve 
reliability, add value, and a series of other dimensions and characteristics pertaining to the 
transportation of goods from the point of production to the point of consumption. 
Bichou and Gray (2004), propose a channel approach and conceptualise the role of ports 
from three perspectives: logistics channel perspective, where the port serves as an 
intermodal transport intersection and operates as a logistics centre; trade channel 
perspective, where the port acts as a key location where channel control and ownership 
can be identified and trading take place; and supply channel perspective, where the port 
not only links outside flows and process but also creates patterns and process of its own 
(Song, and Panayides, 2012, p. 237).
Botha and Ittmann (2008) describe the role of seaports as major components in 
determining the competitiveness of a nation’s economy, and there is a close relationship 
between development and expansion of seaports and economic growth. Ports constitute a 
critical link in the supply chain, with their level of efficiency and performance influencing a 
country’s competitiveness (Cullinane and Song, 2002). Tongzon (2007) provides nine key 
determinants to be a successful port (and also logistics hub): port operations efficiency 
level, cargo handling charges, reliability, port selection preferences of carriers and 
shippers, the depth of the navigation channel, adaptability to the changing market 
environment, landslide accessibility, product differentiation, and government role (including 
government support, and law/regulation). Compared to the past, today’s port authorities 
are focusing on efficiency rather than effectiveness.
In order to develop maritime transport as an integrated part of the logistics and supply 
chain management system, ports have to simultaneously work in several directions 
simultaneously, by taking into account the requirements of the sender and receiver of 
goods (such as physical accessibility from land and systematic organisation of the 
information flow, which affect the choice of seaport) as they become their business 
partners in addition to the traditional ones (such as shipping companies, terminal 
operators, and forwarding companies) (Song, and Panayides, 2012, p. 201). 
Pag.  32
There are cases worldwide where some ports have plenty of idle land-side space available 
which in the absence of other uses can be used for container storage; others ports, rather, 
with limited space and good land-side transport linkages may choose to maximise the 
available space for warehousing, distribution and light manufacturing.
Ports have evolved from being simple transshipment points and can provide a range of 
services and activities to support the wider supply chain. This can benefit supply chains by 
making them both more efficient and effective, while allowing ports to become more 
profitable (Mangan, Lalwani, and Fynes, 2008). 
Cullinane (2011, p. 323-324) clarifies that choice of port corresponds to the choice of 
alternative logistic chains or routings. The level of decision-making can be distinguished: 
1. The level of locations (trade generation) concerns: 
a. location of industries, number of goods produced
b. total of imported and exported goods per firm or region
2. The level of relations (trade distribution) concerns: 
a. the choice of trade partners 
b. the assessment of trade relations between regions 
3. The level of operations concerns: 
a. the choice of transport mode, scheduled versus non-scheduled, choice of transport 
route and vehicles size.
Chen (2001) also points out that modern ports depend upon the availability of efficient 
infrastructure and inland connections, as a part of global transport system. Chen (2001) 
highlights the ability of logistics and transport operators to contribute to value creation  and 
moreover to accomplish the qualitative attributes of customer demand (such as reliability, 
frequency, availability of information, security, etc.) (Song and Panayides, 2012, p. 201).
4.2 Port as a Logistics Centre 
Johnson and Wood (1996) view a logistics centre as a cost reduction centre, defined as a 
facility where commodities move constantly to the end of circulation and the warehousing 
other relevant costs are reduced as much as possible (Song, and Panayides, 2012: 196). 
An UNESCAP report (2002) states that a logistics centre should be equipped with all the 
public facilities necessary to carrying out all logistics-related activities. Logistics centres 
serve a variety of purposes including cargo transshipment, production synchronisation and 
facilitating business and trade, and others aiming to strengthen the logistics capability for 
transforming a region into a more attractive or competitive market. However, fundamental 
requirements for a logistics centre include being on a nodal point of the transport network, 
common infrastructures, inter-modality, and logistics and transport services (Bhutta et al, 
2003). Over time there have been changes to how things are stored, produced and 
moved, which have been significant for the development. The logistics facilities concept 
could, however, be derived from three different perspectives such as a traditional logistic 
Pag.  33
and supply chain perspective (distribution centre or warehousing), a freight transport 
perspective (load centre, freight village and transport node point), and a foreign direct 
investment perspective (international logistics zone and international free trade zone) 
(Song, and Panayides, 2012, p. 196). 
Different definitions of a distribution centre are provided by Bowersox (1968), and by 
Reynaud and Gouvernal (1987). Firstly, Bowersox define it as a physical facility used to 
complete the process of product line adjustment in the exchange channel, and its primary 
function is placed upon product flown contrast to storage. Reynaud and Gouvernal, by 
contrast, expand its simple warehousing function into transportation that is defined as a 
place where the consignments from different origins are grouped or split, and is above all 
transportation organisation centre, located at a nodal point in the logistics system. Riming 
and Grundey (2007) define the freight village as the defined area within which all 
activities relating to transport, logistics and distribution of goods, both for national and 
international transit, are carried out by various operators. 
It is claimed that there are four requirements for a freight village: it must allow access to all 
companies involved in the logistics activities in order to comply with free competition rules; 
it must be equipped with public facilities including staff and equipment; it should be 
preferably be served by a multiplicity of transport modes (e.g. intermodal transportation); 
and it is imperative that a freight village be run by a single body, either public or private 
(Europlaform, 2004).
4.3 Port-centric Logistics
Referring to the latter part of the previous paragraph, Robinson (2002) introduces the 
concept of value chains in the port environment and discusses the notion that competition 
takes place along the value chain (logistics chains) and not between individual ports. 
Song, and Panayides, (2012, p. 240) argue that ports contribute to the supply chain 
through the creation of competitive advantage and value-added delivery. 
Mangan et al (2008) define port-centric logistics as ‘the provision of distribution and other 
value-adding logistics services at a port’ (p. 36); they specify that higher profit margins can 
be made by the provision of non-core port activities in port-centric logistics services. 
Ports are increasingly recognising that higher profit margins can be made on some non-
core port activities and this is driving them to engage in activities beyond simply providing 
berths for ships and other core port services (Falkner, 2006; Wall, 2007; Analytiqa, 2007). 
Carbone and De Martino (2003, p. 306) define value added service as “an activity along 
the chain that adds value to the product or service and which the final customer is willing 
to pay”; these services vary from simple processes such as packaging, labelling and bar-
coding to more complicated processes such as inventory management and quality control 
(UNESCAP, 2002). By offering value-added logistics services, ports aim to attract a large 
portion of the value-added creation within product and logistics chain (Notteboom and 
Winkelmans, 2001; Paixao and Marlow, 2003). 
Pag.  34
Mangan, Lalwani, and Fynes, (2008), refer “[…] ports can be quite heterogeneous in terms 
of their traffic mix and the potential for port-centric logistics activities is likely to vary 
significantly among ports; […] the potential for port-centric logistics activities is not just 
limited to container terminals at ports located close to end customers.”
It is now generally accepted that supply chains, and not individual firms or products, are 
the basis of much marketplace competition (Christopher, 1992). Transport services (links 
in supply chains) and transport infrastructure (nodes in supply chains) are key elements in 
efficient logistics systems. Maritime transport (comprising ports as nodes and shipping 
services as links) is the dominant mode for international freight movements and is thus 
crucial to international trade and a vital component of many supply chains (Marshall, 
2005).
Notteboom and Rodrigue (2005) argue that current patterns of (inland) distribution centre 
location ignore the fact that most of the freight that passes through these distribution 
centres first passes through a port. Therefore, they argue that it is logical (and often times 
easier in terms of land cost, lack of congestion, etc.) to locate such distribution centres at 
ports. The approach in-port distribution centres is not in conflict with the regionalisation 
approach (connections to inland distribution centres) advocated by Notteboom and 
Rodrigue (2005). It has also been recognised that the gateway position of major seaports 
offers opportunities for the development of value-added logistics and other activities 
proximate to ports. Port clusters (de Langen, 2002) have thus evolved which Haezendonck 
(2001) defines as: [. . .] the set of interdependent firms engaged in port related activities, 
located within the same port region and possibly with similar strategies leading to 
competitive advantage and characterised by a joint competitive position vis-a`-vis the 
environment external to the cluster.
Pettit and Beresford (2009) refer to the potential benefits of port-centric operations in order 
to earn extra revenue from activities carried out on port’s land; and, moreover, and 
element in considering the port’s attractiveness is how much land is available and the 
quality of hinterland connections. 
Port-centric strategy users highlight the opportunity to cut supply chain costs, reduce 
carbon footprints and improve customer service. (NEP, 2012)
Browne (2010), specifies that port-centric logistics eliminate the costs of double handling; 
and the recent recession, has forced companies to rethink their freight-handling and 
transport strategies, simplifying the complex supply chain, adopting a port-centric logistics 
approach.
According to Paul Barker, PD Ports development director “Port-centric logistics works on 
the principle that it is faster, more cost-effective and certainly more environmentally friendly 
to set up a distribution centre at the port(s) and distribute directly to the local region from 
there.” (Brown, 2010); the positive effects of port-centric activities, eliminate the fuel and 
labor costs of double-handling - carrying goods from port to distribution centre and from 
Pag.  35
distribution centre to end user (ibid). 
Monios (2011) states “Now that the majority of products come through ports, it may not be 
efficient to haul containers to a central location and then send the contents outward again.”
Certainly, the port might incur in conflicting strategies, as affirmed by Monios (2011), 
between inland intermodal terminals and port-centric logistics, because when an inland 
intermodal terminal is used, containers are transloaded from rail to truck then taken to 
RDCs for stripping, then trucked empty back to the depot at the inland terminal (or maybe 
another depot); by contrast, if the customer is located within warehousing/logistics areas 
adjacent to the terminal, the container can be stripped and the empty container can return 
immediately to the onsite depot, as a consequence of these activities, stock can then be 
picked and put on trailers direct to stores rather than via a diversion to a central DC.
One advantage of establishing a distribution centre at a port is that it cuts down on the 
number of empty (return) containers on roads by “stripping” (e.g. emptying) imported 
containers at the port. This also allows faster repositioning of containers to another port 
where they are required.
In the article Port-centric logistics (2009), port-centric logistics was referred as the “new” 
industry standard, challenging much of the conventional wisdom of inland cargo movement 
and creating a broader approach to hinterland distribution. This approach evolved into a 
series of mature relationships with importers and cargo owners, together with third-party 
operators and ensures that the very best supply chain solutions are specified and 
consistently delivered. 
For instance Hutchison's UK ports have established themselves as leaders in the field of 
global logistics, acquiring a unique position, because they tailored a package of logistics 
services to meet and perhaps exceed  the needs of cargo owners. 
Ports are not a static element or player in the entire supply chain, as stated  in the 
aforementioned article, ports continue to work closely with both shippers and consignees 
in challenging the traditional model of logistics. The positive consequences of this 
challenge, has been the reduction of expensive and wasteful practices, early visibility, fast-
tracking, elimination of demurrage and the reduction of inventory levels. 
According to NEP (2012), the positive consequences of port-centric logistics will only be 
found if people consider the entire logistics chain. Players only look at the distribution from 
DC to the retail store; that is where all the sophisticated figures are and the costs 
calculated. But people don’t take into account the empty containers going back to the port. 
Someone has to pay for that. It adds to the cost and when you overlay with the carbon 
footprint issue, that is when the business case gets stronger, when people look at the total 
picture rather than one or two legs of the chain. 
Pag.  36
4.3.1 Examples from the United Kingdom 
The United Kingdom is recognised as being well-organised in terms of port-centric 
activities. Most of the ports across the country reorganised logistics and efficient 
distribution systems in order to satisfy customer demand. 
Several actors in the UK confirm the benefits coming through of the port-centric idea, one 
of those is Perry Glading, Chief Operating Officer, Forth Ports, who believes that port-
centric ideas can be applied to a much broader range of cargoes and supply chains: 
“When people talk about port-centric, they get carried away with it only being for imports of 
containers. We believe it is about how you use the port as a centre for both import and 
export. It is about broadening the role of the port. We talk about 360° port-centric logistics: 
the port sits in the middle. Too many people have a vision of going in one direction, but it 
isn’t, and exports from the UK are growing. It is how you use your port to add value. You 
either don’t touch the cargo and it goes straight through, or you add value in and 
out.” (NEP, 2012)
Many medium-sized ports in the UK are pursuing port-centric logistics as a way of 
competing with larger ports. Indeed, even large ports like Felixstowe are using this 
strategy where possible and the new development at London Gateway is designed as a 
port-centric operation (Monios, 2011); at Felixstowe there are 70,000m2 of warehousing 
located within the HM Revenue and Customs wharf-approved area. (Port-centric logistics, 
2009)
For instance Bapgroup (2016) and PD Ports (2016) offer a wide range of services from the 
port-centric perspective, such as in the north-east, PD Ports has been a leading advocate 
of port-centric logistics, making use of its very significant land bank at Teesport; the port 
counts more than 3.5 million ft2 of warehousing (equivalent to 325,000m2 or 32,52 hectare) 
on the port estate or close to the port, occupied by shippers using the port for import/
export activities; at the same port, retailers such as ASDA and Tesco have positive effects 
on their logistics activities. (NEP, 2012). Stephen Taylor, Director of Port Centric Logistics 
Partners, says: “Land has always been a key issue for port-centric logistics”; so, land is a 
positive influence on the success and competition of the port. As a consequence, the 
proactive development of port-centric logistics at English ports such as Teesport will exert 
a strong influence on the future directions of logistics in Scotland.
Forth Ports is investing heavily in the rebranded London Container Terminal at the Port of 
Tilbury, which handles deep-sea, short-sea and feeder services. At the same time, work 
has started on Tilbury’s new London Distribution Park, north of the existing port estate. 
This will add another one million ft2  (92,900m2 or 9.29 hectare) of warehousing to the 
port’s already substantial supply of five million ft2  (464,500m2 or 46.45 hectare) on the port 
estate. (NEP, 2012)
Pag.  37
An example of port-centric logistics onshore is the warehousing developments at the port 
of Grangemouth, which has received government funding, indicating government support 
for a strategy of port-centric logistics whereby the port authority is aiming to develop retail 
business at the site (Monios and Wilmsmeier, 2012).
The Port of Tyne has focused on the port-centric concept, which it has historically 
promoted as a one-stop shop approach, incorporating quayside handling and elements 
such as warehousing, stock control, picking and packing, distribution and haulage (NEP, 
2012). 
London Gateway Logistics Park
According to Stephen Taylor (NEP, 2012) and Londongatway.com (2016), the impact of DP 
World’s (DPW) London Gateway investment will be a big factor in the logistics network. 
The new deep-sea container port on the Thames, comes with the benefits of a 10 million 
ft2 (929,000m2 or 92.9 hectare) logistics park being developed alongside. Several retailers 
invested in the logistics park such as Marks & Spencer, announcing plans for a £200 
million warehouse development. In the opposite site, DPW announced that the park will 
include a purpose-built common user facility (CUF). This will ensure that all shippers, 
whether leading retailers or SMEs, can take advantage of the port-centric opportunities. 
Peter Ward, Supply Chain Commercial Manager says: “The potential supply chain cost 
savings in terms of primary and secondary distribution for occupiers of the logistics park 
are compelling”. Stephen Taylor, regarding CUF says: ‘Building a CUF for port-centric is a 
great move for SMEs engaged in international trade; as Tesco and ASDA already did […]. 
According to Importservices.co.uk (2016), the port-centric model is optimum for the new 
world of retail logistics, confirming that port-centric retail logistics with import services, is 
the answer to certain business activities. For instance, in Southampton the distribution 
centres allow stock to be held, free of duty and VAT, until sold to market in the EU or 
transhipped, to external markets still under bond;  at last some help to ease company’s 
cash flow.
It is mentioned that if the company is located in Southampton and the order is B2C, 3PL 
will move with agility and speed for next day delivery, straight from the container port 
facilities, to the customer’s home. Port-centric with Import Services means that the carton 
delivery is processed with thousands of other orders on the day. All orders moving from the 
port warehouses, in full trailer loads, directly to the parcel hub for sortation and onward 
delivery via integrated parcel carriers. 
Retailers are particularly keen on Port-centric logistics, which helps rationalise deliveries 
into their DC’s, cutting supply chain carbon emissions and allowing a significant tick in the 
environmentally friendly box, for all concerned (ibid).
Pag.  38
4.4 Port Hinterland
Port Hinterlands have been described as captive and contestable (de Langen and Pallis, 
2005). A captive port hinterland is a region, where a single port has a competitive 
advantage (e.g. lower prices for freight trips) over other ports in handling the region’s 
cargo. A contestable hinterland is a region where no single port has a clear competitive 
advantage over competing ports. Port terminal operators have greater (less) bargaining 
power versus port users when their ports have captive (contestable) hinterlands; operators 
are more likely to charge relatively high (low) port prices when port hinterlands are captive 
(contestable), e.g. high (low) rent extraction. The bargaining position of port service 
providers versus shippers is generally stronger than that of port service providers versus 
shipping lines. The rationale for the latter is that shipping lines have larger volumes of 
cargo (from consolidating different origin-destination cargoes) that strengthens their 
bargaining position in the bargaining process. Port hinterlands have also been described 
as captive and overlapping (shared by more than one port) hinterlands. 
Ports with overlapping hinterlands compete for the overlapping hinterland market. 
However, a port with a large hinterland can also compete and be more competitive in 
computing for the overlapping market (Zhang, 2008). Specifically, a port with a large 
captive hinterland will 1) allow for more frequent services by shipping lines, 2) facilitate the 
growth of third-party logistics providers and freight forwarders, 3) allow shipping lines to 
use larger ships, deriving cost economies of ship size at sea, 4) yield higher ship 
utilisation, and 5) allow more value-added clusters to be developed. The higher traffic 
density at the port will in turn, among other things, lower shipping rates to and from the 
port, thereby making it more competitive in competing for the overlapping market (Talley, 
2009, p. 143).
Zhang (2008) states that a larger port hinterland allows for a larger size of ships being 
attracted, thus realising economies of ship size (Jansson and Shneerson, 1987), higher 
frequencies of service realising Mohring effects, stronger roles as load centres, better 
availability, of third party logistics service providers and more value-added clusters (de 
Langen, 2004).
4.5 Logistics HUB
Song, and Panayides (2012, p. 203) give this definition: “A maritime logistics hub is 1) a 
nodal point of cargo transit or transshipment assuring flawless door-to-door cargo 
movements, 2) a principal distribution centre functioning as a temporary storage and 
sorting, and 3) a place creating and facilitating value added services on a regional and/or 
international scale.”
Europlatform (2004) provides a precise definition of logistics centre: the hub for a specific 
area where all the activities relating to transport, logistics, and good distribution, both for 
Pag.  39
national and international transit, are carried out, on a commercial basis, by various 
operators.
This pattern drives companies to consolidate shipments on a large scale at major 
terminals (e.g. hubs) and to redistribute smaller shipments to their respective destinations 
via radial links (e.g. spoke). This concept has been introduced in the supply chain section. 
The development of international trade and industrial distribution patterns has impacted on 
the development of logistics facilities as they have been recognised as main strategic 
contributor to achieving competitiveness and attractiveness (Cullinane and Song, 1998). 
In the 1990s, the hub concept became the primary distribution model employed by 
logistics integrators as DHL, TNT, UPS, FedEx and leading international carriers. 
Shipment coming from several origins are consolidated at major terminals (e.g. hub) and 
redirected to their respective destinations through radial links (e.g. spoke) (Cavinato, 
1989). In the field of logistics and supply chains, however, the hub concept has often been 
introduced  under various terms according to its functionality of storage and transportation: 
logistics centre, logistics zone, freight terminal, distribution centre, warehouse, intermodal 
terminal, international transport terminal, and so on (Song and Panayides, 2012, p. 
195-196). 
4.6 Port Services 
According to Worldbank (2001) port services definition, there are two types of activities 
carried out by ports: core (traditional port) and value-added (non-traditional port) services. 
Core services consist of marine (e.g. pilotage, towage, and vessel traffic management 
services), terminal (e.g. vessel tie-up, container storage and container stuffing and 
stripping), and repair services (i.e dry dock ship repair, container repairs). Nontraditional 
port services “create value for shippers by expanding the scope of markets that they can 
economically access, by reducing the delivered cost of products they sell, or by reducing 
the cost to complete buy/sell transactions” (Worldbank, 2001, p. 10). Non-traditional port 
services (e.g. information, office and equipment rental, equipment maintenance services, 
and freeport zone) typically add value to the logistics activities, e.g. inventory management 
and warehousing, of shippers (Talley, 2009, p. 44). 
Customers now tend to look at value-added logistics services as an integral part of their 
supply chain. As a result, ports must attempt to satisfy these needs by offering 
differentiated services (Song and Panayides, 2012, p. 201). The importance of a number 
of logistics value-added services (such as consolidation, packaging, labelling, assembly, 
economic processing, contingency protection, and operation efficiency) is assessed by 
various different authors (Song and Panayides, 2012).
Pag.  40
4.7 Port Choice and Shipping Lines
Several factors influence the shipping lines routes, or port choice; one such factor is port 
consignment size, the greater the likelihood that a shipping line will have its ships call at a 
given port (Talley, 2009, p. 65).
A shipping line’s liner (scheduled service) pricing policy will also affect whether a port is 
included in a ship’s transportation network. Equalisation liner pricing is a port-to-portlier 
pricing scheme whereby the freight rate (or price) for cargo is the same from any main port 
in a port range (on one end of a ship’s round-trip route) to any main port in a port range on 
the other end. If the shipper is responsible for inland transportation costs to and from ports, 
the shipper would minimise total transportation costs (ocean and inland) by having the 
cargo shipped to the port that is nearest to the shipper’s location.
The most prominent explanatory variables for port choice are ocean transport costs, inland 
transport costs, port costs and variables capturing quality of service aspects, such as 
Mohring effects (as mentioned earlier). The demand elasticity of a port can be measured 
by applying logs models based on revealed or stated preferences. The demand elasticity 
is measured as the change of demand as consequence of an increase in port call cost 
consisting of port dues, marine charges and terminal handling charges associated with the 
shipment of one twenty-foot equivalent unit (TEU) in a port (Cullinane, 2011, p. 323).
Ports that can accommodate larger ships while maintaining fast ship turnaround times 
(e.g. time differences between ships entering and leaving a port) will likely see an increase 
in the number of calls by larger ships. Ports with relatively shallow water depths will likely 
experience a decline in ship calls over time as ships increase in size, conversely for ports 
with deep water. If a port in a port range charges significantly lower port prices to shipping 
lines than another port in this port range, the shipping line will prefer the less expensive 
port in this port range. Also, if one port has superior inland transportation connections, 
existing port relationships (or a service history), with a given shipping line, and closes 
access to trade lanes, the given shipping line is more likely to choose this port over 
another port in a port range. If one port in a range of ports is subject to less port 
government regulation (e.g. economic, safety, and environment regulation) than another 
port, the former will more likely be chosen as the port of call in this rage than the latter, all 
else held constant (Talley, 2009, p. 66).
4.8 Port Competition and Measurements
Port competition may be inter- or intraport competition. Interport competition is competition 
between different ports whereas intraport competition is competition among marine 
terminals. Intraport competition will not be analysed in this research because the main 
analysis concern the competition among the main ports located in Scandinavia as: Oslo, 
Copenhagen-Malmo and Stockholm. 
Pag.  41
4.8.1 Interport Competition 
Notteboom and Winkelmans (2001) noted that inter-port competition has intensified, even 
among more distant ports, and point out that for example the competition between 
European ports situated in different port ranges has increased considerably in recent 
years.
Fleming and Baird (1999) pointed out that the real future competition will not be between 
ports and individual transport carriers per se, but between a handful of “total logistics 
chains”. Indeed, Goss (1990), drawing upon Verhoeff (1981), discussed five different forms 
of competition which ports are subject to, namely – competition between whole ranges of 
ports or coastlines; competition between ports in different countries; competition between 
individual ports in the same country; competition between the operators or providers of 
facilities within the same port; and competition between different modes of transport. 
Fleming and Baird (1999), identify the characteristics influencing interport competition as 
the following: 
1) Port performance improvements, with improvements in quality of service, the port time 
prices of port users are expected to be lower. By reducing its costs, the port is then 
able to lower its port prices.  
2) Port accessibility by having superior sea and land accessibilities, a port’s 
competitiveness relative to other ports is enhanced. A ship’s transit time and costs such 
as pilotage and towage costs are less when a port is near the open sea. By having 
direct connections to highways, rail and inland  navigation systems, a port’s land 
transportation transit times for its cargoes will be less all else held constant. The 
competitiveness of ports is also enhanced if they are located near centres of 
consumption and production. 
3) Port tradition: ports located in cities with a long tradition of supporting port expansion 
projects give rise to a culture of support for port improvement projects, especially when 
a competing port appears to be gaining an interport competitive edge 
4) Government assistance: the greater the government assistance to a port, the greater 
the port’s competitiveness relative to other ports. That is to say, the port will be in the 
position to reduce its port prices after receiving government operating assistance. The 
latter may include, for example, tax reduction, low costs loans, guaranteed loans, 
provisions of port infrastructure, and the fallout from government-funded research and 
development programs that benefit the port. 
5) Port Users Preference by congregating larger volumes of cargo at fewer ports, the 
shipping lines (due to the larger cargo volumes at these ports) are able to obtain lower 
negotiated rates often not proportional to distance) from inland carriers an thus charge 
lower door-to-door rates (Talley, 2009, p. 140-141). 
Major ports in China such as Shanghai and Shenzhen, are are feeling the effects of 
competition with the neighbouring ports as Hong Kong, Singapore and Busan (South 
Korea) (Sang-Hun, 2006; Wright, 2007). However as more capacity comes on stream, 
Pag.  42
ports are looking to attract other traffic, especially transshipment traffic, which passes 
through ports in neighbouring countries. These ports outside of China are pursuing a 
variety of strategies, such as developing tax free zones and developing facilities for value-
adding activities within the port area, in order to retain their traffic from the onslaught of 
competition from ports in China. 
Increasingly, ports are recognised as key components in determining the overall 
competitiveness of national economies. Cullinane and Song (2002) point out that ports 
constitute a critical link in the supply chain and that their level of efficiency and 
performance influences, to a large extent, a country’s competitiveness. Similarly, Sanchez 
et al (2003) in the context of a number of Latin American countries, showed that port 
efficiency is a relevant determinant of a country’s competitiveness and interestingly they 
add that, unlike most other relevant variables, port efficiency can be influenced by public 
policies. 
4.8.2 Port Competitiveness 
A port’s competitive position (or its competitiveness) may be evaluated in terms of the 
growth, market share, and diversification of its traffic volume (Talley, 2009). An analytical 
tool that has been used to evaluate the competitiveness of a port (in a port range) that 
considers these factors is strategic position analysis (SPA). SPA includes: Product portfolio 
analysis (PPA): Four levels of PPA have been used to evaluate the competitive position of 
ports in a port range (Haezendonck et al, 2006)
a. The overall market shares and total growth rates of the traffic volumes of ports in 
the port range are presented (external positioning analysis/portfolio of ports)
b. The market share and the growth rates of various traffic categories in a port’s total 
traffic volume in the port range are described (internal positioning analysis/portfolio 
of traffic categories)
c. The port’s market shares and growth rate at each commodity group in their total 
commodity groups in their traffic volumes in the port range are described (portfolio 
commodity groups)
d. Differs from the third level in that the shares and growth rates are within a port 
rather than within the port range
4.8.3 Indicator Port Performance 
Port operate in different economic, social, and fiscal environments. For example, even if 
ports have the same economic objective of maximising annual throughput subject to a 
profit constraint, the profit constraint is likely to differ among ports. Also, one port may have 
a negative profit (or deficit) constraint that is to be subsidised, while another port may have 
a positive or break-even profit constraint. Ports may also have different economic 
objectives (Suykens, 1986). Thus, in a multi performance evaluation approach, where the 
performance of one port is compared to that of another, similar ports should be used 
Pag.  43
(Talley, 2009: 139). Port management and strategies are both directly and indirectly 
influenced by prevailing logistics trends, since the demand for port services is a double 
derived demand (Marlow and Paixao-Casaca, 2003). From the port industry’s perspective, 
the shipping industry would be the party which has the most direct impact on it (Cullinane, 
2011, p. 445).
According to Cullinane (2011, p. 439), the role and function of ports has evolved rapidly 
and has changed in the context of supply chains and logistics chains. Ports now operate in 
a new logistics environment focused on supply chain management, global sourcing and 
logistics outsourcing. Port operators and port authorities are adopting new strategies for 
improving service quality, such as strategic integration along the supply chain, customer-
oriented practices and value-added activities, as well as improving operational efficiency, 
so that they can adapt to a more challenging logistics environment.
Talley (1994) identifies the criteria specification methodology for selecting port 
performance indicators: 
1) Conciseness requires that the redundancy and overlap among selected indicators be 
limited;
2) Consistency with objectives: requires that the indicators be consistent with the port’s 
operating  objectives, e.g. they affect these objectives when their values change. 
3) Data availability; 
4) Data-collection time and cost: the time and cost to be incurred in the collection of the 
indicator data should be considered in the selection of port performance indicators;
5) Measurability: requires that the selected indicators must be measurable, e.g. having a 
continuous as opposed to a discrete unit of measurement;
6) Minimisation of uncontrollable factors requires that the values of the port’s selected 
indicators be under the control of port management;
7) Robustness requires: that the selected indicators allow  for the port to be evaluated 
under various scenarios.  
4.8.4 Port Efficiency 
Port literature has focused on measuring efficiency while other transport modes such as 
air, road and rail put a greater emphasis on external perspectives such as customer 
orientation, reliability and service (Brooks, 2007).
It appears that a reduction of the average waiting time of vessels by one hour corresponds 
with a cost decrease of 46.4 Euro per TEU Handled. A reduction of the average hinterland 
transport transit time by one hour corresponds to a reduction in costs of 4.88 euro per 
TEU, which is nearly a tenth (Cullinane, 2011, p. 336). 
In order to improve port efficiency, lower cargo handling costs and integrating port services 
with other components of the global distribution network, is the correct path according to 
Bryan et al (2006). 
Pag.  44
Port costs, for example, represent about 8–12 percent of total transport costs from product 
origin to destination. Shippers make shipping decisions in part based on those costs. Clark 
et al (2001) declare that port efficiency can affect transportation costs and that an 
inefficient port has the effect of increasing the distance to a shipper’s export market by 60 
percent. In a study of Asia-Pacific Economic Cooperation (APEC) countries, Wilson et al 
(2003) explore the importance of port efficiency relative to other factors that enhance or 
constrain trade, such as customs performance, the regulatory environment, and e-
business.
Calculating indicators for each factor, Wilson et al (2003) found that improvement in port 
efficiencies yields the largest increases in trade flows; specifically, an improvement of just 
0.55 percent in the port efficiency indicator has the same impact as 5.5 and 3.3 percent 
improvements in customs performance and e-business indicators, respectively. Improving 
those procedures can lower total transaction costs and thereby improve the 
competitiveness of a country’s trade, and recent research suggests that better procedures 
can lower costs substantially. 
4.9 Freeport Zone 
An overview of FTZ is due because the PoG is interested in developing this area, in order 
to attract new companies. 
Rodriguez (2016h), defines the Foreign Trade Zone (FTZ) is an area that is considered 
outside the customs jurisdiction of a country where cargo can be placed in a duty and tax 
free environment until ready to enter the country. 
FTZ is a prominent value-added service. A freeport zone is a designated area (within or 
outside a port), where imported goods are stored and/or processed and exported - free of 
all customs duties (Firoz, 2003).
The main advantages of FTZ are thus regulatory and financial, which enables rather 
unique and flexible supply chain management practices Rodrigue (2016h):
1. Custom clearance: Done inland instead of at the gateway port (merchandises go 
directly to the FTZ); Simpler and faster; Consignment can stay for an unlimited amount 
of time in the FTZ; Consignee gets further advance notice that shipment is ready; 
Quotas can be managed through postponement.
2. Duties and Fees: Duties and merchandise processing fee not paid until the 
consignment is released and moved out of the FTZ (storage); Not paid if goods are 
exported or re-exported; Deferred if goods moved to another FTZ; Not paid for 
damaged, defective or obsolete goods; Lower insurance premiums since no duties.
3. Settlement: Vendors often not paid until consignments leave the facility for delivery 
(Delay settlement); Remove damaged or defective products from the settlement.
4. Security: Higher security level since under jurisdiction of national customs; Lower 
insurance premiums.
Pag.  45
5. Transformations and manufacturing: Product remarked or labeled to meet national 
requirements; If transformation is performed in the FTZ, the duty class may change 
(Select the taxation regime); Added value activities performed in a FTZ not subject to 
custom duties.
A variety of activities can be undertaken in a freeport zone, e.g., packaging, assembling, 
cleaning, repackaging, sorting, testing, labelling, and combining imported goods with 
domestic goods or other foreign goods. Freeport zones boost the local port economy by 
employing labor and other resources and attracting foreign investment for the provision of 
freeport zone services. The goal of freeport zones is to maximise the value of 
transshipment cargoes (Feng and Hsieh, 2008). 
Several FTZ examples can be found in emerging countries: 
- Shanghai (China): Airport bonded area, Yangshan (deep water area), logistic park area; 
- Dubai (UAE) JAFZA (Jabel Ali Freezone Authority), where the following benefits are 
included: 100% foreign ownership, 0% corporate tax for 50 years (a concession that is 
renewable), No restriction on capital repatriation, 0% import or re-export duties, 0% 
personal income tax, No currency restrictions, No restriction on foreign talent or 
employees, Ability to mortgage your premises to a bank or financing company, Onsite 
Customs.
The NVO (non vessel operating common carriers), also known as OTIs (ocean transport 
intermediaries), in other words, the commoners that are handling the freight of a customer 
- can split out the cargo here and then have it cleared by customs. This is what is meant 
by cargo (or container) freight station bonding. The facility also provides bonded 
warehousing; for example, an importer of liquor can leave it indefinitely here and only pay 
duty on it when they move it out.  
The site was also a foreign trade zone, or FTZ. As an example: this mean that the goods 
have not yet entered the commerce of the Country. The FTZ enables firms to manipulate 
cargo. (Bonacich and Wilson, 2008, 132) 
Pag.  46
5. BACKGROUND E-COMMERCE  
This section provides an overview of retailers and online retailers characteristics, 
strategies, location and distribution centres in order to better perform activities that can 
satisfy customer demand in a short lead time; and some e-commerce definitions. Several 
parameters are taken into consideration when retailers select the e-consumers segment, 
the most appropriate country in which to focus their business activities.
Image 5.1 E-commerce Literature Investigation
5.1 E-Commerce Overview 
Fernie and Sparks (2015, p. 205) define e-commerce as “[…] is the sale and distribution of 
goods and services via electronic means, has developed rapidly over the last couple of 
decades. There are a variety of e-commerce sectors including: business-to-business 
(B2B); business-to-consumer (B2C); business-to-government (B2G); consumer-to-
consumer (C2C) and government-to-business (G2B).” 
The e-commerce phenomenon will continue to grow both for business-to-business (B2B) 
and business-to-consumer (B2C) sectors. From a convenience point of view and under 
greater environmental pressure, grocery home shopping and delivery will also grow 
significantly (Richards, 2014, p. 21).
The author is primarily concerned with B2C e-commerce in order to support the location of 
online retailers' warehouses in the port area, port-centric warehouses for online retailers, 
contributing to a better distribution system across the country and internationally.
The increase in port-centric logistics has resulted in companies building large warehouses 
as close to ports of entry as possible. As mentioned, Tesco's 1.2 million square foot 
warehouse at Teesport UK is a typical example (Richards, 2014, p. 21).
Pag.  47
Source: personal elaboration
According to the IMRG report (2011), the growth of e-commerce was closely linked to the 
development of internet usage. In 2000 there were just over 350 million internet users in 
the world, a figure that grew to over 2 billion in the next 10 years and is forecast to grow to 
5 billion by 2015. By contrast, the Global Internet Report (2015) specifies that globally 
there are 3 billion internet users as at May 2015; the mobile penetration is forecast to 
reach 71 per cent by 2019; there are 192 countries with active 3G mobile networks, which 
cover almost 50% of the global population; Smartphone sales are the majority of mobile 
handsets sold worldwide; and tablet sales will soon exceed total PC sales. Considering the 
dedicated geographical area of this investigation - Western Europe (Sweden, Finland, 
Denmark and Norway included), internet users are 79 per cent of the population, the 
mobile internet penetration is about 64 per cent, and the 3G population coverage is 97 per 
cent. 
According to Forrester (2013) online retail sales in the United States in 2013 reached $262 
billion – a rise of 13 per cent over 2012's $231 billion; this represents 8 per cent of the total 
retail market and will reach $370 billion by 2017. In the United Kingdom online retail sales 
accounts for approximately 10 per cent of overall sales and is likely to grow between 10 
and 15 per cent over the next few years. The growth in countries such as China is closer 
to 75 per cent (Richards, 2014). Instead, in the old continent, in Europe, 2014 e-commerce 
sales counted for 372.84 $M, in 2015 counted for 418.05 $M, and 458.98 $M (2016 
forecast) (Statista, 2016).
Internetlivestats.com (2016) with data elaborated by International Telecommunication 
Union (ITU), United Nations Population Division, Internet & Mobile Association of India 
(IAMAI) and World Bank, statistics for the countries featured in this study are: 
- Sweden: there are 9,169,705 internet users (93.1 per cent of population penetration)
- Denmark, with 5,479,054 internet users (96.3 per cent of population penetration)
- Norway, with 5,167,573 internet users (98 per cent of population penetration) 
- Finland, with 5,107,402 internet users (92.5 per cent of population penetration) 
This information supports the growth trend in e-commerce business, but a deeper 
investigation about the online sector continues in the analysis section. 
The growth of broadband allowed faster download speeds and facilitated the growth of 
successful e-tail websites, as mentioned by Fernie and Sparks (2015). 
Fernie and Sparks (2015, p. 207) pay particular attention to the problem with the B2C 
model compared with C2C and B2B models, because it entails trade goods that are 
tangible and need to be stored and transported to the final consumer. The two authors 
specify that market presence and brand identity are necessary ingredients to wean 
customers away from their traditional methods of buying. 
Yet despite these apparent drawbacks, the ‘hype’ associated with this new form of trading 
led many analysts to discuss the notion of disintermediation in B2C markets.
Pag.  48
5.2 E-Retailers Market Evolution 
The fourth “P” of the marketing mix, Place, was traditionally centred on the wholesale and 
retail trade and how suppliers would channel their products to market (Fernie and Sparks, 
2014, p. 36). 
Despite all of the hype about international retailing, little has been written about the supply 
chain implications of the internationalization process. Sparks (1995) acknowledges that 
there are three main threads to understanding retail internationalization: international 
sourcing; international retail operations; and internationalization of management ideas. 
Fernie and Sparks (2015, p. 24) highlight that retailers need to create market demand 
before investing in costly infrastructure.  
One of the large changes in recent years has been the expansion of ‘reserve and collect’ 
and ‘click and collect’ type operations. It had been thought that internet shopping would be 
based around home delivery, but consumers have shown that they also value the ability to 
decide where and when they receive products. In reserve and collect type systems 
consumers seem to be using the internet to check local inventory before going to the store. 
In click and collect operations they are opting to have the order assembled at store and 
then collect it at a time of their choosing and convenience. For retailers such 
developments remove some of the issues of organizing home delivery, but emphasize the 
importance of having accurate and real-time stock and inventories as well as changing 
work practices. Similarly, the strong development of mobile and tablet computing and 
shopping has encouraged retailers to shorten their advertised delivery periods and in 
some urban areas to offer same-day or even two hour-delivery options. This poses real 
challenges for many retailers. 
The same authors highlighted that times have changed and retail logistics has also 
changed. Retailers are the channel captains and set the pace in logistics. Having extended 
their channel control and focused on efficiency and effectiveness, retailers are now 
attempting to engender a more cooperative and collaborative stance in many aspects of 
logistics. 
In 1996, Alan McKinnon reviewed and summarized the key components required for this 
retail logistics transformation. He identified six closely related and mutually reinforcing 
trends: Increased control over secondary distribution, Restructured logistical systems, 
Adoption of ‘Quick Response’ (QR), Rationalization of primary distribution (e.g. factory to 
warehouse), Increased return of packaged material and handling equipment for recycling/
re-use, Introduction of Supply Chain Management (SCM) and Efficient Consumer 
Response (ECR).  
The dedicated order picking model utilizes e-fulfillment centres to pick and deliver orders 
to customers. The advantage of this system is that it is dedicated purely to e-commerce 
customers so OOS should be low and delivery frequencies should be higher. These 
picking centres, however, have less of a product range and they need to be working at 
Pag.  49
capacity to justify investment costs. In non-food there are some highly successful 
operators of this model (e.g. asos.com) (Fernie and Sparks, 2015, p. 23). 
5.3 Online Retailers
Eisenmann, Hallowell, and Tripsas, (2002, p. 301) mention that catalog and web business 
are similar in two important ways: 1) goods cannot be inspected prior the purchase and, 2) 
consumers do not have access to the goods after the purchase.  
What are online retailers exactly? Online retailers are companies that 1) use a web site to 
merchandise newly manufactured physical goods for which they take title, and then 2) rely 
on third party service providers (e.g. UPS, Fedex, DHL, etc.) to deliver those goods from 
remote warehouses. 
According to Eisenmann et al (2002, p. 303), compared to the traditional shopping format, 
online shopping offers several advantages such as 1) online retailers can offer “24/7” 
service (e.g. consumers can shop 24 hours a day, 7 days a week; 2) online retailers can 
reach consumers who might live far away to shop at their brick-and-mortar stores. 
Web retailers own different attributes: 
- Information-Rich Products: where graphics and detailed information help consumer to 
understand the product’s features and benefits 
- Large Selection: internet retailers can offer a big variety of product selection 
- Little Need for Hands-on Service or Product Trial: certain products such as apparel are 
often sold after a product trial and through examination.
- High Value-to-Weight ratio: Internet retailers ask consumers to bear shipping costs or 
absorb such costs themselves through “free shipping” promotions;  
- Easily customisable products: complete, multi-featured products that lend themselves to 
customisation are well suited to the web (Dell Case)   
- Rapid changes in Stock availability, Demand, and/or Price: consumers can use websites 
to check the availability of hard-to-find items, information that can be frustrating and 
time-consuming to obtain by phoning or visiting brick-and-mortar retailers. 
- Replenishment Driven: internet technology can be employed to automate the frequent 
reordering of groceries, pet supplies, ad similar items. Internet retailers who can lock 
customers into a “sticky” replenishment cycle then have an opportunity to cross-sell 
additional products and services to these consumers. 
- Unpleasant Brick-and-Mortar Retailing Environments: Most consumers dislike grocery 
shopping, finding it time-consuming and repetitive. Parents often dislike shopping for 
toys with their children because  in a toy store children tend to become very excitable. 
The internet helps consumers avoid these unpleasant brick-and-mortar retailing 
environments. 
Eisernmann (2002) continues with the categorisation of e-retailers in two ways: 
Pag.  50
1) Merchandise emphasis 
a. Horizontal focused, when they sell many product categories such as amazon.com, 
because it sells a broad range of products
b. Vertical oriented, when retailers sell in one distinct area (single category of 
merchandise); examples are garden.com, eToys, and Pets.com
2) Pricing format 
a. Fixed pricing (format valid in the offline market)
b. Auction, such as egghead.com who sells computer hardware and software 
products.
c. Group buying (demand aggregation) sites as mercata.com and MobShop.com
d. Deep discount model, such as buy.com who sold, once, products at cost price, in 
order to create a customers’ database and then selling it manufacturer (for 
advertising and marketing programs); but the model had poor results  
In the offline market, companies like Wal-Mart and Macy’s are considered Horizontal 
retailers, while Toys and Home Depot can be considered vertical oriented. 
Eisenmann et al (2002, p. 304), mention first of all that online prices are lower between 
6-10 percent comparing to their brick-and-mortar competitors due to different transport 
costs; instead several barriers influence the shopping online such as 1) sending the credit 
card information over the web; (but turned out on development of electronic wallet); 2) 
Consumer’s lack of familiarity with the brands of some pure-play companies (e.g. 
companies that were “born on the web” and lack a brick-and-mortar or print catalogue 
heritage) can compound consumers’ concerns about credit card theft; and building 
consumers’ trust is an important task for young websites; 3) waiting for home delivery, 
because 70 percent of the population is not home during the day; for this reason 
amazon.com organised the delivery in 1 hour, or selecting the appropriate window time for 
the delivery, in order to reduce thefts when packages are left in front the door.
Fernie and Sparks  (2015, p. 218) specify that retailers need the trust of the consumer 
before investing in the necessary infrastructure. 
5.4 Online Purchase and Distribution 
According to Rodrigue (2016i), E-commerce offers advantages for the whole commodity 
chain, from consumers being exposed to a wider range of products to manufacturers and 
distributors being able to adapt quickly to changes in demand. E-commerce generates 
significant number of home deliveries parcel movements that are carried by conventional 
postal services as well as specialized parcel carriers. In the United States, about 70% of 
home deliveries are made by the United States Postal Services, while the remaining 30% 
is carried by private parcel companies. Fulfillment (warehousing, packaging) costs account 
for 10 to 12% of the revenue of e-commerce, while shipping and delivery costs added up 
another 10%. E-commerce is also inciting shifts in retail freight distribution (Image 5.2) with 
Pag.  51
the setting of new fulfillment and sortation centers. As retail sales get partially replaced by 
online sales the need for conventional retail space declines while the footprint occupied by 
distribution centre increases.
Image 5.2: Evolution of retail freight distribution
Table 5.1: Logistics Facilities Supporting E-commerce
Facility	Type Facility	A?ributes Loca?onal	A⴮ibutes
E-Fulfillment	
Centre
Large-sized	facility	(half	a	million	to	one	
million	square	foot).	Cross-docking	
configura?on	common.	High	racks	storage.	
Push	towards	automa?on.
Low	land	costs.	Proximity	to	highway.	
Access	to	a	major	parcel	hub.
Parcel	Hub	/	
Sorta?on	Centre
Large-sized	facility	(half	a	million	square	
foot).	Cross-docking	configura?on	for	
handling	trucks.	Automated	and	semi-
automated	sorta?on.
Low	land	costs.	Accessibility	to	regional	
distribu?on.
Parcel	Delivery	
Centre	/	Urban	
Logis?cs	Depot
Medium-sized	facility.	Cross-docking	
configura?on	for	loading	vans.
Periphery	of	metropolitan	areas.
Freight	Sta?on	/	
Pickup	Loca㐳n
Small	or	micro-sized	facility.	Store-like	facility	
(pickup	loca?on).	Locker	banks	(freight	
sta?on).
High	density	neighborhood	loca?ons.
Pag.  52
In standard e-commerce distribution chains, e-fulfillment facilities are usually owned by the 
online retailer while parcel hubs, sortation centers and parcel delivery centers are usually 
owned by third party logistics providers. However, consolidation trends are emerging as 
large online retailers are opening their own sortation centers. Some are also getting 
involved in the transportation segment of their distribution with urban delivery vehicles and 
trailers to move cargo between e-fulfillment and sortation centers Rodrigue (2016m).
According to Richards (2014, p. 22-24), there are three types of fulfillment centre:
- integrated fulfillment, where internet sales are carried out alongside existing retail 
operations;
- dedicated fulfillment, carried out in a purpose-built facility; and
- store fulfillment, which involves picking online orders from existing retail shelves for 
separate delivery ex store. A same-day courier service provided by Shuttle boasts a 
record delivery time of 13 minutes 57 seconds for an online order using this channel!
The third option has been favoured in the past for launching the service and establishment 
of e-fulfillment but is least favoured for a substantive operation. 
With regard to warehousing, pure internet traders have had an advantage in developing 
purpose-built facilities according to a recent TI report for Savills (2013) whereas existing 
retailers and manufacturers who are selling online need to adapt existing logistics systems 
and facilities to meet these new demands or create new ones to accommodate the move 
to multichannel retailing.
The report suggests that the tipping point for dedicated e-commerce fulfillment centres is 
approximately 200,000 orders and that warehouses are in the region of 20–60,000 square 
feet (Richards, 2014, p.22).
Online shopping is, nevertheless, imposing new logistical requirements. First, it is 
substantially increasing the volume of goods that must be handled, creating the need for 
new DCs and larger vehicle fleets. Second, many online retailers are serving customers 
from different socio-economic backgrounds from the traditional mail order shopper. As they 
live in different neighbourhoods, the geographical pattern of home delivery is changing. 
Third, online shoppers typically have high logistical expectations, demanding rapid and 
reliable delivery at convenient times (Xing and Grant, 2006).
According to Fernie and Sparks (2015, p. 223), the distribution of online purchases 
normally exhibits the following characteristics: 
1. Products are generally supplied directly to the home from the point of production or a 
central DC. Each order comprises a small number of items (often just one) and the 
order picking is centralized at a national or regional level. A large proportion of the 
orders are channelled through the ‘hub-and-spoke’ networks of large parcel carriers or 
mail order companies. 
2. Within these J4U delivery networks, each order must be individually packaged at the 
central distribution point. This not only increases the volume of packaging in the supply 
Pag.  53
chain: it also takes up more space on vehicles in both the forward and reverse 
channels. 
3. Within home shopping systems, whether catalogue- or internet-based, there is a large 
rate of returned product. Typically, around 30 per cent of non-food products delivered 
to the home are returned to e-tailers (in contrast to 6–10 per cent for ‘bricks and 
mortar’ retailers) (Nairn, 2003). This requires a major reverse logistics operation 
comprising the retrieval, checking, repackaging and redistribution of returned 
merchandise.
The home delivery channel terminates at the home or a nearby customer collection point. 
It is less clear where it begins. For the purposes of this review, the start of the home 
delivery channel will be defined as the ‘order penetration point’ (Oldhager, 2003). This 
physical process usually begins with the picking of goods within a stock-holding point. Only 
when picked are the goods designated for a particular home shopper. Distribution 
downstream from this point is sometimes labelled J4U, ‘just for you’ (Fernie and Sparks 
(2015, p. 222-223).
This links to innovation in the ordering process discussed earlier leading to the ‘any time, 
any place’ mentality and retailers have responded through offering a plethora of delivery 
(and returns) options for customers. This means that retailers offer tighter time windows for 
delivery, provide click and collect choices (the customer incurs the transport costs!) and a 
range of collection/return points (mainly convenience stores) (Fernie and Sparks, 2015, p. 
221).
Pag.  54
6. BACKGROUND - E-BUYERS 
In order to have a better overview about this research, the author investigated e-buyer 
characteristics. From the e-buyer characteristics point of view, e-retailers have better 
knowledge about the specific customer. In this case the actors above mentioned will focus 
their activities and logistics services based on location, and customer characteristics.  
A company's primary responsibility is to serve its customers. Profit is not the primary 
goal, but rather an essential condition for the company's continued existence. 
(DRUCKER, 1954) 
Image 6.1 E-Buyers’ Literature Investigation
6.1 E-Buyer Evolution 
According to Kewill (2013) Generation Z/the post-90s generation have entered the market, 
as both consumers and employees. Having grown up using e-mail, social networking and 
communications technology such as mobile/smart phones, MP3 players, laptops/tablets 
and games consoles, they have never known a world without them. Adept at switching 
between multiple platforms, formats and devices, they expect to utilize the technology they 
are familiar with in the work environment, accelerating the prevalence of Bring Your Own 
Device (BYOD) in industries heavily reliant on the timely transfer of data, such as logistics.
Croucher, Baker and Ruston (2014) refer about the rapid growth in online selling 
companies, such as Amazon, and the fact that all major grocery companies have wholly 
embraced the concept means that home shopping is now very common, with all the 
implications for logistics that home delivery brings.
It is important to differentiate between home shopping and home delivery (e-fulfillment). 
‘Home shopping’ refers to the different ways of shopping for and ordering products from 
Pag.  55
Source: personal elaboration
home. ‘Home delivery’, or e-fulfillment, refers to the physical delivery of the product to the 
home (strictly speaking, e-fulfillment is the delivering of orders made via the internet but 
the terms are used interchangeably).
The growth of home delivery has led to the need for some fundamental changes in 
logistics operations that wish to serve the home market. The very nature of the final 
delivery operation to the home is dramatically different from a standard delivery operation, 
and home delivery requirements also affect other elements in the supply chain (Croucher, 
Baker and Ruston, 2014); typical implications are:
- shops become showrooms where stock replenishment is no longer an issue
- there has been a major increase in direct home deliveries, where restricted delivery time 
windows, often during the evening, have an impact on delivery vehicle utilization
- new distribution systems have been established (small deliveries on small vehicles into 
residential areas, community depots, etc)
- existing delivery systems have been provided with new opportunities (postal service, 
parcels delivery operations)
- customer ordering systems can be linked directly to manufacturers’ reordering systems;
- there is a high rate of returns – reverse logistics. Outside the grocery sector, returns 
levels are quite high and can vary between 30 and 50 per cent.
6.2 E-buyer Characteristics 
In only a decade or so, internet connectivity changed from an English-speaking, developed 
country phenomenon to a global one. This conceals the different stages of development 
for different country markets and the geo-demographic profile of internet consumers. 
Furthermore, the increasing cosmopolitan tastes of a new generation of consumers has 
led to the creation of buying centres throughout the world by the ‘mega groups’ (Fernie and 
Sparks, 2014).
Eisenmann et al (2002, p. 305) mention that a website must often tailor its pricing, 
merchandising approaches, and customer service to the needs of distinct customer 
segments. Online shopper can be classified into the following groups:
1) E-bivalent Newbies: newest to the internet, this population is somewhat older, and 
spends the least amount of time online; 
2) Time sensitive Materialists: group of consumers interested in saving time and 
maximising convenience and is less likely to read product reviews, compare prices, or 
use coupons;
3) Click and Mortar: this segment prefer to shop online but prefer to buy offline, are more 
likely female homemakers, have privacy and security concerns about buying online, 
and visit brick-and-mortar shopping malls most frequently;
4) Hooked, Online, and Single: this is a young single male segment, with high income, 
have been on the internet the longest play games, download software, investments, 
and shop online the most often;
Pag.  56
5) Hunter-Gatherers: this segment is typically age 30 to 49, married, with two children, 
and most often goes to sites that provide analysis and comparisons of products and 
prices;
6) Brand Loyalists: this segment of people go directly to the website of a merchant they 
know, are the most satisfied with shopping online, and spend the most online. 
This conceals the different stages of development for different country markets and the 
geo-demographic profile of internet consumers. 
In terms of demographic variables, key variables on online behaviour include income, 
education, race, age and gender, with life-style, culture and social factors also of 
importance. However, research has found that as the online market has matured, the 
general demographic profile of online shoppers has become more similar to those of 
traditional shoppers (Fernie and Sparks, 2014). Internet shoppers, according to a major 
international study, tend to be more impulsive, value convenience, tend to be wealthier and 
are heavier users of internet and e-mail. They also have favourable attitudes to advertising 
and direct marketing (Doherty and Ellis-Chadwick, 2010). 
The profile of an online shopper is not just linked to demographic and psychographic/
behaviour variables that favour online shopping, or to geography, technology and 
confidence in the online market, but to the merchandise being bought. For example: the 
age profile for online grocery shoppers tends to be younger, in the 18–40 year old range. 
Grocery shoppers also tended to be in the higher social categories. Older shoppers (65 
plus) were less likely to shop online for groceries (IGD, 2011). 
It is interesting to note that early research into M-commerce customers indicates some 
similarities to customers in the early years of the uptake of e-commerce, for example, most 
shoppers (62 per cent in 2005) were young (14–24) males. They tended to be confident 
internet users and experienced internet shoppers (Bigne et al, 2005). The demographic 
and gender profile is likely to rebalance as the technology becomes widely familiar and the 
market develops. Internet use was not found to influence mobile shopping, but previous 
experience of internet purchase meant consumers were more predisposed to buy on 
mobile devices. 
All of this research shows that e-tailing has been most successful to date where a multi-
channel ‘click and bricks’ approach is adopted. The companies best equipped to adopt 
such a strategy were traditional department stores and clothing specialists in that they had 
considerable experience of dealing with the non-store shopper through their catalogues 
and ‘low tech’ selling techniques, especially as these companies were well equipped to 
deal with home deliveries and a returns policy. 
According to Harrison, Hoek and Skipworth (2014, p. 287), if the delivery service does not 
meet customer expectations, sales can be lost. Marks & Spencer (M&S), a household 
retail brand in the UK, was faced with online shoppers expecting next-day or even same-
Pag.  57
day delivery of their orders, but its antiquated technology and delivery systems were not 
up to the job, Butler (2013) reports.
6.3 The Components of Customer Service
Croucher, Baker and Rushton, (2014, ch.3) refer to the logistics components of customer 
service and their classification in different ways.
Logistics customer service elements can thus be divided into three categories that reflect 
the nature and timing of the particular service requirements (before, during and after 
delivery of the product):
1) Pre-transaction elements: these are customer service factors that arise prior to the 
actual transaction taking place. They include: written customer service policy; accessibility 
of order personnel; single order contact point; organizational structure; method of ordering; 
order size constraints; system flexibility; transaction elements.
2) Transaction elements: these are the elements directly related to the physical transaction 
and are those that are most commonly concerned with distribution and logistics. The 
following are included: delivery time; delivery reliability; delivery of complete order.
3) Post-transaction elements: these involve those elements that occur after the delivery 
has taken place, such as: availability of spares; call-out time; invoicing procedures; 
invoicing accuracy; product tracing/warranty; returns policy; customer complaints and 
procedures; claims procedures.
Logistics customer service elements can also be classified by multifunctional dimensions. 
The four main multifunctional dimensions are:
- time: usually order fulfillment cycle time;
- dependability: such as guaranteed fixed delivery times of accurate, undamaged orders;
- communications: such as the ease of order taking or effective queries response;
- flexibility: the ability to recognize and respond to a customer’s changing needs.
Each of these can be broken down into further detailed elements (Croucher, Baker and 
Ruston, 2014, ch.3). One example of this is shown in Image 6.2, which describes the 
different time-related components.
The total order fulfillment cycle time has been split into the five main time-related 
components from order receipt to final delivery. In addition, there is a preliminary step from 
order placement to order receipt, although this is not considered by some companies 
because it is deemed to be part of their customers’ ordering process. When identifying and 
measuring order fulfillment cycle time it is important to be able to break it down to all of the 
key components. Thus, if there is a customer service problem it can be measured and 
traced quickly and easily and the actual detailed problem can be identified and remedied.
Pag.  58
Image 6.2 The Constituent Parts of Total Order Fulfilment Cycle Time
6.4 The Importance of Customer Service 
According to Croucher, Baker and Ruston (2014, p. 33), the core product concerns the 
item itself: the technical content, the product features, the ease of use, the style and the 
quality. The service elements, which can be called the ‘product surround’, represent the 
availability of the product, the ease of ordering, the speed of delivery, and after-sales 
support.
Image 6.3 Core Product Versus Product ‘Surround’:
illustrating the importance of the Logistics-Related Elements
Pag.  59
Source: Croucher, Baker and Ruston, 2014, ch.3 and personal elaboration
Source: Croucher, Baker and Ruston, 2014, p. 33 and personal elaboration
The marketing departments of many companies recognize that the product surround 
elements are very important in determining the final demand for a product. In addition, 
these aspects often represent only a small percentage of the cost of a product. Thus, true 
to the Pareto 80/20 rule, it is estimated that product surround or logistics elements 
represent about 80 per cent of the impact of the product but only represent 20 per cent of 
the cost. It is essential that the customer service elements are satisfactory, and logistics 
plays a crucial role in providing good customer service (Croucher, Baker and Ruston, 
2014, p. 33). 
One of the definitions of logistics that was provided in the previous sections, referred to 
‘the positioning of resource at the right time, in the right place, at the right cost, of the right 
quality’. 
This definition can be expanded into what might be considered as the seven ‘rights’ of 
customer service. These are the right quantity, cost, product, customer, time, place and 
condition (Image 6.4). 
All of these different aspects can be key requisites of a good customer service offering – 
indeed, each of them may be essential to ensure that a product achieves its expected 
sales in the various markets where it is made available. It is notable that all of these 
elements are affected by the standard and quality of the logistics operations that are 
essential to getting a product to market (Croucher, Baker and Ruston, 2014, p. 33).
Image 6.4 The "Right" Service 
Pag.  60
Source: Croucher, Baker and Ruston, 2014, p. 33 and personal elaboration
The key topic of customer service continues to increase in importance and to have a major 
impact on logistics, such that the logistics function has become the key element in 
customer service strategy. This includes:
- the development of ‘customer-facing’ organizations and operations
- a move towards service policies based on market segmentation
- JIT and quick-response systems requiring markedly more frequent and reliable delivery
- ‘brand image’ becoming less strong – the dominant differentiator being availability.
One very recent example of the increasing importance of customer service has been the 
move to develop an alternative approach to the supply chain by creating what is called 
demand chain management (DCM). Here the intention is to move the emphasis away from 
the supply of products and towards the demand for products – to reflect the importance of 
what the customer requires rather that what the supplier wants to provide. Ultimately this is 
linking the two concepts of supply chain management (SCM) with customer relationship 
management (CRM), or linking logistics directly with marketing (Croucher, Baker and 
Ruston, 2014).
6.5 Online Environmental Impact 
Concerns have been expressed that online retailing is likely to generate more transport 
and impose a heavier burden on the environment than store-based retailing (Hesse, 
2002). Some e-tailers, on the other hand, advertise their service as being good for the 
environment. Matthews et al (2001) compared the externalities associated with the 
distribution of books through a conventional retail channel and from an online bookseller 
and came to the conclusion that the latter was less environmentally damaging. According 
to their calculations, which included ‘trucking, air freight, production, packaging and 
passenger trips’, energy consumption, air pollution, greenhouse gas emissions and the 
quantity of hazardous waste were respectively, 16 per cent, 36 per cent, 9 per cent and 23 
per cent lower in the case of online retailing. (Fernie and Sparks, 2015, p. 231)
Pag.  61
7. METHODOLOGY 
The current section presents the methods and methodology that have been used to 
conduct this research.  
In order to better define the type of research conducted, the classification of the study is 
provided; it gives an overview of how this research can be classified according to the 
purpose, process, outcome and logic of the research. 
This is followed by an explanation of the study’s paradigm and how the data and literature 
were collected. 
This section continues with an overview of several models used in the analysis.  
Image 7.1 Study process - Methodology
7.1 Classifying Research
According to Collis & Hussey (2014), research can be classified according to the purpose, 
process, outcome and logic of the research. To clarify how this study has been conducted, 
the different classifications will be described in this section. 
The purpose of the study is to investigate how the location of a warehouse/DCs at a 
Scandinavian port would influence online retailers, with particular reference to the ports of 
Gothenburg, Oslo, Copenhagen-Malmo and Stockholm. 
According to Collis & Hussey (2014), this purpose classifies the current research project 
as predictive research. Predictive research looks into answering the questions of ‘how’, 
‘why’ and ‘where’ and the answers or solutions generated from this analysis will be used to 
generalize in similar studies where applicable. 
The process of a study refers to the kind of data that is collected during that study in order 
to answer the research question(s) (Collis & Hussey 2014). 
The research question is this: assuming that all four ports included in the research provide 
warehouses to e-retailers, which location has the most convenient distribution (e.g. short 
lead time and large e-buyer customer base)? How can the Port of Gothenburg (PoG) 
contribute to the success of online retailers? Which factors create a competitive advantage 
for e-retailers? Which factors influence the choice of location for a warehouse/DC?
Pag.  62
In order to answer these questions, both qualitative and quantitative data needs to be 
collected. 
The qualitative data refers to the panel session organised with the Port of Gothenburg 
director and top managers, in order to get experts within the field to share their knowledge 
of the current situation and receive some inputs. The research sessions contributed to the 
improvement of this paper (on going) based also on online retailers’ perceptions and 
services requested. 
The study relies on a quantitative analysis of data obtained mainly from scientific and 
official resources. The quantitative data refers to the numerical data that has been used to 
map the different locations, customers, costs, routes, port’s performances, country 
economy, and different performances within the specific areas that are part of the study. 
The data consists of coordinates of the port’s location as well as data that is used to 
calculate the time, costs, capacity and the geographical distance between the distribution 
centres and customers, which were necessary to be able to identify the best Scandinavian 
port (among those identified) for online retailers interested in the Scandinavian market. 
As described above, the purpose of the research is to investigate the port best able to 
satisfy the demand for online retailers, shipping lines, offering a well connected hinterland, 
and penetrating e-buyers spread across the North of Europe (Finland, Sweden, Norway, 
Denmark). If the Port is aware of what is important to the actors involved in the e-business, 
the port itself will deliver high services to its customers, and all actors involved work, as a 
consequence, for “next customer” satisfaction. The outcome of the research can be said to 
be applied research, as described by Collis & Hussey (2014). Applied research refers to a 
study where the goal is to solve a problem. Since the Port of Gothenburg faces challenges 
regarding port activities, lead time, costs and customer satisfaction, these can be related 
to the problem that this research aims to solve. 
A theoretical structure was created, with the purpose of being tested later in the process of 
the research. This structure of the process indicates that this study was made under a 
deductive approach. A deductive approach refers to empirical observations that are tested 
against an already-developed theoretical structure and to a method that goes from general 
to the particular, something that can also be related to in this study. (Collis & Hussey 2014) 
7.2 Paradigm
This section presents an explanation of the study’s paradigm and how the data and 
literature were collected.
A research process is guided by a paradigm, that is to say, a framework that is based on 
assumptions about the nature of knowledge and the world but also based on individuals’ 
philosophies. There are two main paradigms that exist, which are interpretivism and 
Pag.  63
positivism. Interpretivism refers to the idea that social reality is subjective, since social 
reality shapes people’s perception. This paradigm focuses on exploring the complexity of 
social phenomena, while a positivist paradigm is more about measuring social phenomena 
(Collis & Hussey 2014). A positivist paradigm focuses on different theories that can be 
explained by the social phenomena that exist. Since this study is about building 
warehouses/DCs in the PoG, with an investment of 490million USD (ca.) and the 
introduction of new services for e-retailers, LSP, e-buyers, and port, including the 
development of a new network by using theories about network-hub-port-centric activities, 
this study is conducted under a positivistic paradigm. 
There are different philosophical assumptions that underpin the paradigm and since this 
study is done under a positivistic paradigm, the philosophy that is used in this study is 
methodological assumption since a particular aspect was studied in this research and also 
because the association between the variables was analysed. To add to this, as the 
sample size studied here was large, it was therefore this assumption that suited the study 
best. (Collis & Hussey 2014) 
7.3 Literature Collection 
Considering the extensive literature on the research topic, some previous theories and 
studies had to be collected. The literature that has been searched for and collected can be 
referred to as secondary data, as the data already existed before the study began.
To find relevant literature, as published in articles and journals, the first step is to identify 
the scope of the research. 
The scope of the research was to investigate 1) The supply chain from an independent 
point of view, in order to have a solid background; 2) The warehouse/DCs characteristics, 
focusing on e-retailers and LSP; 3) The maritime section, as a relevant part of the SC, was 
analysed taking into consideration the port perspective, shipping line preferences related 
to port efficiency and hinterland/logistics infrastructure, focusing on port-centric activities; 
4) Online retailers as part of the SC were analysed considering their preferences to better 
respond to customer demand; 5) Logistics service providers, as actors in the SC who 
receive the non-core activities by e-retailers; 6) E-consumers, as the final users of online 
retailers’ products, were investigated considering their characteristics and locations. 
This investigation as a whole identifies properly the role of the port in E-commerce 
business, identifying the most appropriate port in which to establish a DC for e-retailers. 
By having the scope defined, it is possible to identify some limitations, which improve the 
literature review. (Collis & Hussey 2014) 
After the scope was defined, the literature review began. By using different databases 
provided by Gothenburg University (GU) and Chalmers’ library, together with keywords, 
relevant literature could be found. The specification of the two universities was applied 
because the first university (GU) has limited access to some online literature, and the 
Pag.  64
second one provides an extensive database of e-books, relevant material, scanned 
magazine-articles and online newspapers. The author investigated leading international 
logistics and maritime transport journals, marketing and management journals, recent 
books about SC, warehousing, distribution, transport modelling and transport geography. 
Relevant literature about facility location by different authors was analysed from different 
perspectives.
Moreover, the author searched for relevant articles in other international journals and news 
sources by using electronic databases, such as ProQuest (ABI), Spinger link, IHS, Sea-
web.com, Eurostat, UN Comtrade, IMF, search words by section. 
Dividing the literature background into different sections contributed to identifying several 
key words, and observations have been classified. The different sections include the 
following key words: 
- Supply Chain: supply chain management, transport strategy, supply chain network, 
logistics factors, supply chain performance; SC key activities, SC network, logistics 
strategy, transportation network, transport strategy, route, transport structure, hub and 
spoke, type of networks, transport geography, transport distance, green logistics;
- Warehouses (W.): w. location, w. strategic location, w. distance from the inbound 
logistics access point and distribution area, type of warehouses, warehouses 
classification, facility location strategy, public warehouse, private warehouses;
- Maritime Logistics: Port efficiency and characteristics, port services, port hinterland, port 
strategic positioning, sea port productivity, port infrastructure in logistics, port 
competitiveness, port performance, port-centric, port-centric activities, port inefficiency, 
port choice and shipping lines, models to analyse the port performance, shipping 
voyage estimation cost, Free Trade Zone (FTZ);
- Online Retailers: DCs localisation, facility location, where online retailers decide to 
locate a warehouse for the online and store distribution; factors online retailers consider 
when investing in a DC, infrastructure and logistics services required;
- Logistics Service Providers: LSP classification, party logistics services, LSP green 
attitude, LSP localisation preferences;
- E-Consumers: e-consumer characteristics, e-buyer segment, e-buyer geo-demographic 
characteristics. 
By studying the gathered literature, the opportunity to find other relevant sources and 
original sources was given, something that was important to providing the study with high 
validity. 
In line with the theories, the competitors analysis must be conducted through the Port of 
Oslo, Copenhagen-Malmo, Stockholm and Gothenburg. 
Several considerations have been identified in order to have clear guidelines for the 
research: 
Is the competitiveness of the Port of Gothenburg related to the expansion of the port land? 
and/or is it related to the presence of logistics infrastructure? and/or is it related to port 
efficiency - performance? and/or is related to the lead time? and/or is related to shipping 
Pag.  65
line routing? and/or is it related to the investment of large online retailers? and finally, is 
the competitiveness of the Port of Gothenburg positively related to the identification of 
Gothenburg as a HUB? 
7.4 Data Collection
Data is collected independently and according to the literature background. Each section 
has a dedicated model or set of data to be investigated. The final result is to combine all 
data together and present a ranking of the most efficient and competitive port (geographic 
location) in which to locate a warehouse. 
Considering that the strategic value of a company relates to many aspects of the business, 
non-quantitative aspects must also be considered. 
In order to formulate a logical supply chain network model, the following elements must be 
considered: 
- The Objective is the goal of the optimisation and the criteria to be used to compare 
different solutions. If the object is to minimise the distribution time, it is possible to 
compare two different solutions and judge which is the better based on time; 
- The Constraints defines the rules of a legitimate solution. 
- The Decision defines what the company allows the optimisation to chose from. In the 
optimisation of the physical supply chain, the main decisions include how much product 
moves from one location to another, how many sites are picked, where those sites are, 
but of course the decision cannot be separated from the constraints;
- Data refers to the factors the company wants consider in the decision-making process. 
In cases where no supporting data is available, a company will figure out how to make 
good decisions by creating multiple scenarios. 
7.5 Modeling 
According to Watson (2013, p.12-13), considering the complexity of the supply chain, 
mathematical optimisation technology is the best way to sort through the various options 
balance trade-offs, determine the best location for facilities, and support better decision 
making. Mathematical optimisation relies on linear and integer programming.
Optimisation is a complementary, not competitive, technology that allows a company 
actually to determine the best locations for the facilities. The decision maker can let 
optimisation do the have number crunching to determine the details of the alternatives 
(where to locate, what is made where, how product flows, which customer is served by 
which warehouse, for instance); and the positive consequences of optimisation, if set up 
correctly, are that it will uncover ideas that the decision maker never thought about.
Pag.  66
Regarding the population (e-buyers), different sources have been analysed in order to 
understand the geographical location of potential buyers; each country’s economic 
performance has been considered in terms of, for example, the main economical indicator, 
trade flow (import/export), trade value, trade throughput. 
In the maritime section, several indicators are considered such as the number of TEUs, 
containers (inward/outward), number of vessels (and GT), port characteristics, berth length 
and depth, the services offered by the port, the working hours, port charges, location, 
maritime transport by country, and future/actual investment planned. The port’s location is 
compared with the COG, evaluating the network efficiency. A relevant factor is the shipping 
route from Asia to Europe (especially to the four ports); a shipping voyage calculation is 
provided in order to highlight which port that is more convenient for the shipping line 
(costs, timing, and SECA nautical miles). The four ports are in SECA area and are required 
to use a different type of fuel with a lower percentage of sulphur (this fuel has a different 
price to the open sea used fuel). 
For logistics, a centre of gravity (COG) problem is usually defined as selecting the location 
of a facility so that the weighted-average distance to all the demand points is minimised. A 
COG solution suggests that facilities are located at the centre (the “centre of gravity) of a 
collection of demand points (or in some instances, for firms with many suppliers, at the 
centre of the supply points). Centre of gravity models, by definition, are clear cut and not 
ambiguous. 
Problem formulations do not require a skilled professional to determine the cleanest 
approximation or modelling formula, but rather, merely require a correct and accurate 
specification. Centre of gravity studies are useful both for building the intuition of the 
professional analyst and for validating the accuracy of his or her more comprehensive 
results. The location of the warehouse was also considered from the perspective of time 
range. In order to serve the higher number of customers in the shortest leat time, the 
distances to the potential e-customers were analysed from the port (as a departure point) 
and from the COG, and then compared (both road and rail). They study also focuses on 
sustainable routing, and in this case Eco-transIT carbon emission calculator was used. 
Pag.  67
8. Analysis - Trade 
According to the literature introduced previously, in this section the author goes on to 
investigate international trade by country - Denmark, Finland, Norway, and Sweden. The 
analysis focuses on the selected HS codes, Import-Export value by selected countries, top 
Import-Export trade partners, and trade value among the Scandinavian countries.
Image 8.1 Study Process - Trade Analysis 
International trade - Import & Export - is a picture of the country, and a local population’s 
consumption habits show willingness to spend in products or services. 
International trade, sourcing from foreign markets, products directed to different 
marketplaces, market/industry trends and goods traffic flows are important elements to 
consider for supply chain, maritime transport and warehouse location. 
According to the Port of Gothenburg’s request, in order to analyse in detail the e-
commerce sector, several products with high value have been identified such as apparel, 
electronics (computers), sports equipment, household, books, handicraft material and 
jewellery; and related products. 
To perform this investigation was analysed in detail each single HS code by country. In 
appendix A the selected HS codes are reported, with the proper classification. 
After that the HS codes results have been merged to summarise the results (Appendix B). 
In appendixes C-D-E-F the results are reported by country and single HS code.
In our analysis the HS codes have been classified as below, first by range (HS from/to) 
and by dedicated category:  
1. HS from 28 to 38: Chemicals & Allied Industries, categories included no. 30-33-34-37
2. HS from 41 to 43: Raw Hides, Skins, Leather, & Furs, category included no. 42
Pag.  68
3. HS from 44 to 49: Wood & Wood Products, categories included no. 48-49
4. HS from 50 to 63: Textiles, categories included no. 57-60-61-62-63
5. HS from 64 to 67:  Footwear / Headgear, categories included no. 64-65-66
6. HS from 68 to 71:  Stone / Glass, category included no. 69
7. HS from 72 to 83:  Metals, category included no. 71
8. HS from 84 to 85:   Machinery / Electrical, category 84 but only subcategories no. 
8467-8468-8469-8470 ; and category 85
9. HS from 90 to 97:  Miscellaneous, categories included no 90-91-92-94-95-96.
8.1 Total Import-Export by the Selected Countries
Figure 8.1 shows import/export data 
by country for the year 2015 (in 
relation to the rest of the world) 
(Appendix B, table B.1). 
Sweden is the first importer and 
exporters of goods, with a total of 
278 billion USD, respectively 137,8 
billion USD in import, and 140,1 
billion USD in export. 
Norway is in second position with the 
total value of 183,23 billion USD, 
respectively 76,79 bill ion USD 
( import) and 106 bi l l ion USD 
(export). 
Denmark ranks third, with a total 
value of 179,70 billion USD, with the import value of 85,27 billion USD, and export value 
equal to 94 billion USD. 
Finland comes in fourth position, with a total trade value equal to 119,85 billion USD, the 
import value reached 60,17 billion USD and the export value is equal to 59,68 billion USD. 
Figure 8.2, export by selected HS category, highlights export value by country (to the rest 
of the world) (see Appendix B, table B.2, for data). 
In order to better understand the value trade, the average have been calculated, equal to 
3,25 billion USD. 
Sweden in 2015 had an overall better performance in export compared to the three 
neighbours’ countries. 
Sweden’s total export value for the selected HS codes is equal to 44,9 billion USD; second 
better performance in exports is Denmark with 32,5 billion USD; third is Finland with 18,9 
billion USD; and last is Norway with 7,6 billion USD. 
Pag.  69
Figure 8.1  Import-Export Value Selected 
Countries 2015
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30
60
90
120
150
180
210
240
270
300
Source: UN Comtrade 
Denmark Finland Norway Sweden
Import Export Total 
Figure 8.3 shows import value in million USD by selected HS codes, for the selected 
countries (the import is considered from the rest of the world). The average import value, 
among the considered countries, is 3,27 billion USD. 
The “picture” of the import level changed slightly from the previous figure (8.2). 
According to the selected HS category, Sweden remains the major importer among the 
Scandinavian countries, with the total value of 39,5 billion USD; in second position is 
Denmark with a total of 27,69 billion USD; third is Norway with 22,16 billion USD; and last 
is Finland with the import value equal to 15,2 billion USD (see Appendix B, table B.3, for 
data). 
In order to better understand the trade value for each single country, a deeper 
investigation was conducted. In the next paragraphs the reader will have a detailed picture 
about the country’s top import/export partners, and the import/export value among the 
Scandinavian countries; details about trade flow are reported in the dedicated appendix. 
For a deeper investigation about HS codes (Import-Export) by country, refer to the 
appendix C-D-E-F.
66
Pag.  70
Figure 8.2 Export - Selected HS Category by 
Country 2015
Chemicals & Allied Industries 
Raw Hides, Skins, Leather, & Furs
Wood & Wood Products
Textiles
Footwear / Headgear
Metals 
Machinery / Electrical
Miscellaneous 
Value in million USD (Source: UN Comtrade)
0 2.400 4.800 7.200 9.600 12.000 14.400
Sweden 
Finland 
Denmark
Norway
Pag.  71
Figure 8.3 Import - Selected HS Category by 
Country 2015
Chemicals & Allied Industries 
Raw Hides, Skins, Leather, & Furs
Wood & Wood Products
Textiles
Footwear / Headgear
Metals 
Machinery / Electrical
Miscellaneous 
Value in Million USD (Source: UN Comtrade)
0 2.700 5.400 8.100 10.800 13.500 16.200
Sweden
Finland
Denmark 
Norway 
8.2 Denmark Trade
Figure 8.4 shows Denmark’s top 5 import countries. 
The first country from which Denmark imports 
products and services is Germany, with a value of 
17,4 billion USDs  (39 per cent). 
Denmark imports for 10,5 billion USD products and 
services from Sweden (23 per cent). 
The Netherlands ranks third with a value of 6,81 
billion USD (15 per cent). Denmark imports “just” 6,37 
billion USD (14 per cent); and last one is United 
Kingdom with total value of 3,83 billion USD (9 per 
cent) (see appendix C, table C.2, for data). The 
percentage considered is based on the value of top 5 
import countries and not based on total import . 
Figure 8.5 highlights Denmark’s top 5 export 
countries. 
Germany represents the major market for Denmark 
where the products are exported; the total value of this 
trade is 15,29 billion USD (36 per cent of top 5 export 
value). Sweden is ranked second with 10,45 billion 
USD (24,65 per cent); Norway rank third, with the 
total value equal to 6 billion USD (14,17 per cent). 
United Kingdom in fourth position, receive goods and 
services from Denmark with the total value of 5,41 
billion USD (12,78 billion USD). The last country 
receiving Danish export is USA with the value equal 
to 5,21 billion USD (12,32 per cent) (see appendix C, 
table C.3, for data). The percentage was calculated 
on the total top 5 export value.
Analysing the details of the import and export trade 
between Denmark and Scandinavian countries is 
clear to highlight the major country partner - Sweden 
(Figure 8.6).  
Figure 8.6 shows the import/export trade value 
between Denmark and Sweden-Finland-Norway. The total trade with Sweden count for 
20,94 billion USD, with import value equal to 10,49 billion USD, and total export equal to 
10,44 billion USD. 
Norway, is ranked second, among the nordic countries with the total import/export value 
with 10 billion USD (3,9 billion USD import; 6 billion USD export) (see appendix C, table C.
4, for data). 
Pag.  72
Figure 8.5 Denmark - Top 5 Export 
Countries (UN Comtrade, 2015)
12,32%
14,17%
12,78%
24,65%
36,08%
Germany Sweden 
United Kingdom Norway 
USA
Figure 8.4 Denmark - Top 5 Import 
Countries (UN Comtrade, 2015)
9%
14%
15%
23%
39%
Germany Sweden 
Netherlands China 
United Kingdom 
Finland total trade with Denmark counts for 3,43 billion USD. Denmark import from Finland 
1,10 billion USD, and export 2,32 billion USD. 
The average value calculated for Denmark, it is equal to 7,63 billion USD. This data is 
used at the end to compare the trade value among the countries. 
Pag.  73
Figure 8.6 Denmark, Import/Export 2015 Neighbours 
Countries (UN Comtrade)
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2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
20.000
22.000
Sweden Norway Finland
Total Import Export 
8.3 Finland Trade 
According to UN Comtrade (2015), Finland’s major 
import partners are Germany, Sweden, Russian 
Federation, China and the Netherlands (Figure 8.7). 
Germany export value for 8,99 billion USD (30,11 per 
cent), Sweden count for 6,74 billion USD (22,59 per 
cent), Russian Federation trade value for 6,58 billion 
USD (22,06 per cent), China trade value is 4,36 
billion USD (14,63 per cent), and last is the 
Netherlands with 3,16 billion USD (10,61 per cent) 
(see appendix D, table D.2). The percentage was 
calculated on the total top 5 import value. 
Figure 8.8 shows Finland’s top 5 export countries: 
Germany, Sweden, USA, the Netherlands, and 
Russian Federation. 
In 2015, Germany imported goods with the total value 
of 8,1 billion USD (31,86 per cent), Sweden imported 
goods for 6,05 billion USD (23,80 per cent), USA 
imported goods from Finland with the value of 
almost 4 billion USD (15,75 per cent). In fourth 
position the Netherlands imported goods with 3,82 
billion USD (15,05 per cent); and last is the Russian 
Federation who imported goods for 3,44 billion USD 
(13,55 per cent) (see appendix D, table D.3 for 
data). 
The percentage was calculated on the total top 5 
export value. 
Analysing the details of the import and export trade, 
Germany results being the first partner’s trade, but 
Sweden result the first country among the Nordic 
ones. 
Figure 8.9 shows the import/export trade value 
between Finland and Sweden-Denmark-Norway. 
The total trade with Sweden accounts for 12,79 billion USD, with import value equal to 
6,74 billion USD, and total export equal to 6 billion USD. 
Norway, is ranked second, among the nordic countries with the total import/export value of 
2,79 billion USD (1,08 billion USD import; 1,71 billion USD export). 
Pag.  74
Figure 8.7 Finland Top 5 Import 
Countries 2015 (UN Comtrade)
10,61%
14,63%
22,06%
22,59%
30,11%
Germany Sweden
Russian Federation China
Netherlands
Figure 8.8 Finland Top 5 Export 
Countries 2015 (UN Comtrade)
13,55%
15,05%
15,75%
23,80%
31,86%
Germany Sweden
USA Netherlands
Russian Federation
Denmark’s total trade with Finland counts for 2,92 billion USD. Finland import from 
Denmark  is 1,91 billion USD, and export 1 billion USD (see appendix D, table D.4, for 
data).
The average import/export value from the Nordic countries is equal to for 4,11 billion USD.
Pag.  75
Figure 8.9 Finland Import/Export 2015 Neighbours 
Countries (UN Comtrade)
Va
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0
1.400
2.800
4.200
5.600
7.000
8.400
9.800
11.200
12.600
14.000
Sweden Norway Denmark 
Total Import Export
8.4 Norway Trade
Figure 8.10 shows Norway top 5 import countries in 
2015 (UN Comtrade, 2015). The first country from 
where Norway import products and services is 
Sweden with a value of 8,86 billion USD (25,1 per 
cent). Norway import for 8,71 billion USD products 
and services from Germany (24,6 per cent). 
China rank third with a value of 8,02 billion USD (22,7 
per cent). United Kingdom export to Norway 4,94 
billion USD (14,0 per cent); and last one is USA with 
total value of 4,84 billion USD (13,7 per cent) (see 
appendix E, table E.2, for data). The percentage 
considered is based on the value of top 5 import 
countries and not based on total import. 
Figure 8.11 highlights Norway top 5 export countries 
in 2015. 
United Kingdom represents the major market for 
Norway where the products are exported; the total 
value of this trade is 23,15 billion USD (35,3 per cent 
of top 5 export value). 
Germany is ranked second with 18,68 billion USD 
(28,5 per cent); the Netherlands rank third, with the 
total value equal to 10,5 billion USD (16,1 per cent). 
France in fourth position, receive goods and services 
from Norway with the total value of 6,92 billion USD 
(10,6 billion USD). The last country receiving 
Norwegian export is Sweden with the value equal to 
6,32 billion USD (9,6 per cent) (see appendix E, table 
E.3, for data).
The percentage considered is based on the value of 
top 5 export countries and not base don total value. 
Analysing the details of the import and export trade 
between Norway and Nordic countries is clear to 
highlight the major country partner - Sweden. 
Figure 8.12 shows the import/export trade value between Norway and Sweden-Denmark-
Finland. The total trade with Sweden count for 15,18 billion USD, with import value equal 
to 8,86 billion USD, and total export  equal to 6,32 billion USD. Denmark total trade with 
Norway counts for 8,31 billion USD. Norway import from Denmark  is 4,41 billion USD, and 
export 3,89 billion USD.
Pag.  76
Figure 8.10 Norway - Top 5 Import 
Countries 2015 (UN Comtrade)
13,7%
14,0%
22,7% 24,6%
25,1%
Sweden Germany
China United Kingdom
USA
Figure 8.11 Norway - Top 5 Export 
Countries 2015 (UN Comtrade)
9,6%
10,6%
16,1%
28,5%
35,3%
United Kingdom Germany
Netherlands France
Sweden
Finland, is ranked third, among the nordic countries (trade with Norway) with the total 
import/export value with 2,87 billion USD (1,73 billion USD import; 1,14 billion USD export) 
(details in appendix E, table E.4). 
The average import/export value from the Nordic countries is equal to for 5,86 billion USD.
Pag.  77
Figure 8.12 Norway Import/Export 2015 Neighbours 
Countries (UN Comtrade , 2015)
Va
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1.600
3.200
4.800
6.400
8.000
9.600
11.200
12.800
14.400
16.000
Denmark Finland Sweden
Total Import Export
8.5 Sweden Trade
Figure 8.13 shows Sweden top 5 import countries in 
2015. The first country from where Sweden import 
products and services is Germany with a value of 
24,77 billion USD (37,7 per cent). 
Sweden import for 11,42 billion USD products and 
services from the Netherlands (17,37 per cent). 
Norway rank third with a value of 11,32 billion USD 
(17,22 per cent). Denmark export to Sweden 10,61 
billion USD (16,5 per cent); and last one is United 
Kingdom with total value of 7,61 billion USD (11,58 
per cent) (see appendix F, table F.2, for details). The 
percentage considered is based on the value of top 5 
import countries and not based on total import. 
Figure 8.14 highlights Sweden top 5 export countries 
in 2015  (UN Comtrade). 
Norway represents the major market for Sweden 
where the products are exported; the total value of 
this trade is 14,10 billion USD (24,50 per cent of top 5 
export value). 
Germany is ranked second with 13,98 billion USD 
(24,28 per cent); United States rank third, with the 
total value equal to 10,16 billion USD (17,65 per 
cent). 
United Kingdom in fourth position, receive goods and 
services from Sweden with the total value of 9,81 
billion USD (17,05 per cent). The last country 
receiving Swedish export is Denmark with the value 
equal to 9,50 billion USD (16,51 per cent) (see 
appendix F, table F.3, for details).
The percentage considered is based on the total 
value of top 5 export countries and not based on total 
value worldwide. 
Analysing the details of the import and export trade 
between Sweden and Nordic countries is clear to 
highlight the major country partner - Norway.  
Figure 8.15 shows the import/export trade value between Sweden and Norway-Denmark-
Finland. 
Pag.  78
Figure 8.13 Sweden - Top 5 Import 
Countries 2015 (UN Comtrade)
11,58%
16,15%
17,22%
17,37%
37,68%
Germany Netherlands
Norway Denmark
United Kingdom
Figure 8.14 Sweden - Top 5 Export 
Countries 2015 (UN Comtrade)
16,51%
17,05%
17,65%
24,28%
24,50%
Norway Germany
USA United Kingdom
Denmark
The Swedish total trade with Norway (figure 8.15) count for 25,43 billion USD, with import 
value equal to 11,32 billion USD, and total export  equal to 14,10 billion USD. 
Denmark total trade with Sweden counts for 20,12 billion USD. Sweden import from 
Denmark  is 10,61 billion USD, and export 9,50 billion USD.
Finland, is ranked third, among the nordic countries (trade with Sweden) with the total 
import/export value with 15,62 billion USD (6,36 billion USD import; 9,26 billion USD 
export) (see appendix F, table F.4, for details). 
The average import/export value from the Nordic countries to Sweden is equal to 13,59 
billion USD. 
Pag.  79
Figure 8.15 Sweden Import/Export 2015 Neighbours 
Countries (UN Comtrade)
Va
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2.600
5.200
7.800
10.400
13.000
15.600
18.200
20.800
23.400
26.000
Denmark Norway Finland
Total Import Export 
8.6 Comparing the Average Value
This analysis is based on the average data calculated in the fig. 8.6, fig. 8.9, fig. 8.12; fig. 
8.15. Figure 8.16 compares the different values of average according to the import/export 
trade value in USD between the four countries (value in thousands).
The result is that Sweden rank first for the trade value between the nordic countries, 
Denmark is second, third Finland, and fourth Norway. 
8.7 Comments
According to Ballou (1999, p.34) there are different products directed to the selected 
marketplaces (HS codes). Considering the figure 8.2, Sweden is the country with the 
highest level of export value for the selected products (6 categories out of 8 are higher 
compared with the other countries); instead, the figure 8.3 confirm Sweden as the top 
importer for the selected HS codes categories (8 out of 8). 
It is confirmed by Mulcahy (1994) and Richards (2014) that one important element to 
consider, in warehouse investment, is the goods traffic flow; and Sweden definitely has the 
higher values in Import-Export compared to the selected countries. When discussing about 
logistics centre, Europlatform (2004) mention the goods flow on national and international 
basis; in this case Sweden, considering the trade values both by HS codes (categories) 
and by trade value among the Scandinavian countries (figures 8.6 - 8.9 - 8.12 - 8.15, 
summarised in figure 8.16), is the country that perform better (almost with the double 
Pag.  80
Figure 8.16 Average Analysis - Import/
Export Countries
0
3500
7000
10500
14000
Average
4.115,13
5.860
7.639
13.597,46
Sweden Denmark Norway Finland 
value fig. 8.16, compared to Denmark) in Scandinavia (trade flow perspective). Botha and 
Ittmann (2008) and Cullinane and Song (2002) confirm that the expansion of seaports (as 
critical link in SC) and economic growth (here the trade flow) are related; Sweden trade 
flow is higher compared to the rest of the countries (the seaports’ expansion are 
investigated in the next sections). 
 
The literature investigated and the supported data, highlight Sweden as the right location 
where to invest for a new warehouse/DC. 
Pag.  81
9. Analysis - Maritime
In this section several analyses are conducted in order to provide a general picture of the 
maritime sector in Denmark, Norway and Sweden. Finland is not taken into consideration 
because it is not part of the maritime research (only as a customer market).
A general overview of the maritime freight by country (and region), the port analysis 
investigation, and the navigation costs will contribute to a clearer picture of the selected 
countries and main ports (Oslo, Copenhagen-Malmo, Gothenburg, and Stockholm). 
Image 9.1 Study Process Maritime Secto
9.1 Maritime Freight by Country
9.1.1 Denmark 
According to Eurostat 2013, Denmark’s national overall performance in freight (loaded and 
unloaded) counted for 74,500 thousand tonnes. Particularly the loaded in 2013 was 33,601 
thousand tonnes and the unloaded 45,817 thousand tonnes. The port of Copenhagen is 
located in Hovedstaden region; this region counted 4,437 thousands tonnes and unloaded 
8,933 thousand tonnes, with the total of 13,341 thousands tonnes. This data refers to the 
different regions and not the port itself.
Pag.  82
Table 9.1 Denmark Maritime Freight 
9.1.2 Norway 
According to Eurostat 2013, Norway nationally had a total of 187,287 thousands tonnes of 
freight. Particularly Oslo had 856 thousands tonnes loaded and 4,939 thousands tonnes 
unloaded, with a total of 5,794 thousands tonnes. In percentage terms Oslo accounts for 
3.09 per cent of total Norwegian freight. This data refers to the different regions and not 
the port itself.
Table 9.2 Norway Maritime Freight
Maritime transport of 
freight - Denmark 2013 - 
Thousand tonnes
Loaded (1) Unloaded (1) Total (2) 
Danmark 33.601 45.817 79.418
Hovedstaden 4.437 8.933 13.370
Sjælland 8.734 11.315 20.049
Syddanmark 13.098 12.783 25.881
Midtjylland 3.859 8.534 12.393
Nordjylland 3.474 4.251 7.725
Note
this table identify thousands with the “.” “dot”.
1) Eurostat 2013 
2) Author analysis based on Loaded + Unloaded flow
Maritime transport of 
freight - Norway  2013 - 
Thousand tonnes
Loaded (1) Unloaded (1) Total (2) 
Norway 130.900 56.387 187.287
Oslo og Akershus 856 4.939 5.795
Sør-Østlandet 13.577 11.973 25.550
Agder og Rogaland 11.969 8.266 20.235
Vestlandet 51.602 20.791 72.393
Trøndelag 1.421 2.251 3.672
Nord-Norge 28.226 3.453 31.679
Extra-Regio level 1 23.251 4.715 27.966
Note
this table identify thousands with the “.” “dot”.
1) Eurostat 2013
2) Author analysis based on Loaded + Unloaded
Pag.  83
9.1.3 Sweden 
Sweden in 2013  accounted for 132,710 thousand tonnes of freight, with 59,745 thousands 
tonnes loaded and 72,965 thousands tonnes unloaded. Particular focus is on 3 different 
regions: 
1) Stockholm 
2) Sydsverige  (Malmo)
3) Vastsverige (Gothenburg)
In 2013, Stockholm region had 9.009 thousands tonnes of freight by maritime transport, 
Sydsverige (Port of Malmo location) had 36,569 thousands of tonnes and Vastsverige 
(Port of Gothenburg location) had 47,025 thousands tonnes of freight. 
This data refers to the different regions and not the port itself. 
Table 9.3 Sweden Maritime Freight
9.1.4 Comparing the Freight Results
Figure 9.1 compares the results presented in the previous paragraphs. 
In 2013 Norway had a higher turnover of freight compared to Sweden (2nd) and Denmark 
(3rd).  
Maritime transport of 
freight - Sweden 2013 - 
Thousand tonnes
Loaded (1) Unloaded (1) Total (2)
Sweden 59.745 72.965 132.710
Östra Sverige 6.806 13.610 20.416
Stockholm 2.737 6.273 9.010
Östra Mellansverige 4.070 7.338 11.408
Södra Sverige 39.943 47.874 87.817
Småland med öarna 1.777 2.230 4.007
Sydsverige 16.033 20.586 36.619
Västsverige 22.134 25.057 47.191
Norra Sverige 12.995 11.481 24.476
Norra Mellansverige 2.771 3.726 6.497
Mellersta Norrland 2.374 2.705 5.079
Övre Norrland 7.850 5.050 12.900
Note
 this table identify thousands with the “.” “dot”.
1) Eurostat 2013
2) Author analysis based on Loaded + Unloaded
Pag.  84
By contrast the region - Vastsverige, where Gothenburg is the capital, had the highest 
turnover freight  compared to Sydsverige (Malmo, 2nd), Copenhagen (3rd), Stockholm 
(4th) and Oslo (5th).
9.2 Ports Overview
In order to show performance in gross tonnage (GT) by country, Eurostat (2014) reported 
the data by country and by port (Figure 9.2) (details in Appendix “H”, table H.0). 
To better understand the port characteristics the appendix “G” provides some details for 
the selected ports; and the appendix “H” presents the containerships data by port. 
Denmark in 2014 registered 23.59 million GT, while Copenhagen had 3.43 million GT, that 
represent the 14.55 per cent of the total Denmark. 
Norway in 2014 registered 21.93 million GT, and Oslo registered 3.28 million GT, 
equivalent to 14.97 per cent of total Norway. 
Sweden results being to largest country in terms of gross tonnage in 2014. Malmo 
registered 488 thousand GT, in percentage terms equal to 1.29. Stockholm registered 1.72 
million GT (4.57 per cent); and last Gothenburg with 21.37 million GT (56.58 per cent of 
total Sweden). The PoG has almost the same GT levels of Norway (21,933 GT) and 
Denmark (23,595 GT). It results that Gothenburg represent the major port among the 
selected.
Pag.  85
Figure 9.1 Comparing the Freight Results
(S
ou
rc
e:
 E
ur
os
ta
t 2
01
3)
Denmark 
Copenhangen
Norway 
Oslo 
Sweden 
Stockholm 
Sydsverige
Vastsverige
Thousand Tonnes
0 40.000 80.000 120.000 160.000 200.000
Figure 9.3 (Eurostat, 2014) (see appendix “H”, table H.1 for details) contributes to the 
general understating of the number of containerships arriving to the Port of Oslo, Port of 
Copenhagen-Malmo, Port of Stockholm, and the Port of Gothenburg. 
In total the four ports received 1,727 containerships (2014); 386 arrived at the port of Oslo 
(22,35 per cent), 389 to the  port of Copenhagen-Malmo (22,52 per cent), 165 to the port 
of Stockholm (9,55 per cent), and 787 to the port of Gothenburg (45,57 per cent). In 
proportion, the Port of Gothenburg perform better than the other ports (see other tables in 
appendix H, from H.2 to H.5). Figure 9.3 shows the PoG as the only port (among the 
others) that receive calls by ships’ GT range from 40.000 to 199.000. 
The higher segment, for the PoG, is the calls by ships within 7.000 to 7.999 GT; the 
second higher segment is the call from ships within 9.000 - 9.999 GT. 
Figure 9.3 can be considered as the shipping line preferences according to the most 
appropriate trade market (import-export) and port characteristics. The PoG is able to 
receive calls by larger containerships due to the water depth (introduced in the next 
sections).
Pag.  86
Figure 9.2 Gross Tonnage by Country and by Port
G
T 
(T
ho
us
an
ds
)
0
4.000
8.000
12.000
16.000
20.000
24.000
28.000
32.000
36.000
40.000
Source: Eurostat 2014
D
en
m
ar
k
K
øb
en
ha
vn
s 
H
av
n
N
or
w
ay
O
sl
o
S
w
ed
en
M
al
m
ö
S
to
ck
ho
lm
G
öt
eb
or
g
The appendix H, table H.4, summarise the port’s call performance. The PoG received a 
larger number of calls (compared with the selected ports) in different categories (in total 10 
out of 14); it is the only port able to receive calls from containerships in different ranges, 
from 40,000 to 199,999 GT. 
Instead the Port of Oslo received calls (25) for the segment 2.000-2.999 (equal to 83,33 
per cent for the total segment), and 101 calls (segment 8.000-8.999) equal to 53,72 per 
cent. By contrast the Port of Copenhagen-Malmo (CMP) received 63 calls for the segment 
6.000-6.999, equal to 49,61 per cent of the total segment; CMP performed better in the 
segment 20.000-29.999 with 34 calls, equal to 61,82 per cent of the total segment. 
In the appendix “H” a comparison analysis is provided by port and by category. 
Pag.  87
Figure 9.3 Number of Containerships in Specified Ports (inwards) (2014)
N
um
be
r o
f c
on
ta
in
er
sh
ip
s 
in
 a
 s
pe
ci
fie
d 
po
rt 
(u
ni
ts
)
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
Source: Eurostat 2014
2 
00
0 
to
 2
 9
99
 G
T
Fr
om
 3
 0
00
 to
 3
 9
99
 G
T
Fr
om
 5
 0
00
 to
 5
 9
99
 G
T
Fr
om
 6
 0
00
 to
 6
 9
99
 G
T
7 
00
0 
to
 7
 9
99
 G
T
8 
00
0 
to
 8
 9
99
 G
T
9 
00
0 
to
 9
 9
99
 G
T
10
 0
00
 to
 1
9 
99
9 
G
T
20
 0
00
 to
 2
9 
99
9 
G
T
40
 0
00
 to
 4
9 
99
9 
G
T
50
 0
00
 to
 7
9 
99
9 
G
T
 8
0 
00
0 
to
 9
9 
99
9 
G
T
10
0 
00
0 
to
 1
49
 9
99
 G
T
15
0 
00
0 
to
 1
99
 9
99
 G
T
Port of Oslo Port of Copenhagen-Malmo Port of Stockholm Port of Gothenburg
9.3 Container Traffic for Selected European Ports
The previous paragraphs already provided an idea about the selected ports, showing 
Sweden - Gothenburg as the 
Table 9.4 introduce the country’s annual throughput, the liner shipping line index (LSCI), 
and liner shipping bilateral connectivity index (LSBC). 
The throughput rate (2013 and 2014), in table 9.4, shows the total number of TEUs (and 
FEUs) by country. UNCTAD (2016a) define it as “TEU (Twenty foot Equivalent Unit) 
include loading, unloading, repositioning and transshipment containers as well as Forty-
foot Equivalent Units (FEUs) being counted as two TEUs.” Sweden, for the referred years, 
result being the country with the highest level of throughput, followed by Denmark and 
Norway.  
UNCTAD (2016b) defines “the Liner Shipping Connectivity Index captures how well 
countries are connected to global shipping networks” and “[…] the number of ships, their 
container-carrying capacity, maximum vessel size, number of services, and number of 
companies that deploy container ships in a country's ports”. It results that Sweden, has the 
higher connectivity index (58,84) compared to Denmark (54,85) and Norway (5,89). 
Another index considered to compare the countries is the liner shipping bilateral 
connectivity index, which indicates a country pair's integration level into global liner 
shipping networks (UNCTAD, 2016b). China was considered as the second country, to 
compare, because the major shipping routes are from Asia (China) to Europe. It results 
that Sweden has the higher index (0.58) followed by Denmark (0.54) and by Norway 
(0.27); the maximum level is equal to 1.
Table 9.4 Containers Traffic by Country and Index 
Figure 9.4 represents the TEUs flow for the selected ports. The total TEUs flow is 
1,245,210. 
According to ESPO (2014), the Port of Stockholm, has the lowest TEUs level equal to 
51,000 TEUs (4.09 per cent of the total), the Port of Copenhagen-Malmo, with 145,000 
TEUs (11.64 per cent), the Port of Oslo with 212,579 TEUs (17.07 per cent), and last one, 
the Port of Gothenburg with 836,631 TEUs (67.17 per cent of the total), is the largest port 
General data Denmark Sweden Norway 
Throughput 2013 (TEUs) (1) 873.464 1.602.472 360.635
Throughput 2014  (TEUs) (1) 918.011 1.684.198 379.027
Liner shipping connectivity 
index (2) 2016
54,85 58,84 5,89
Liner shipping bilateral 
connectivity index, 
annual, 2014 (3)
0,54 0,58 0,27
Note 
this table identify thousands with the “.” “dot”; the “comma” “,” identify decimals
1) Unctadstat.unctad.org. (2016a)
2) Unctadstat.unctad.org. (2016b), Max = 100
3) Unctadstat.unctad.org. (2016c), Max = 1
Pag.  88
for TEUs flow in 2014 (see table H.6 in Appendix “H”). The data, in figure 9.4, were 
collected through ESPO, Eurostat and Maritime Insight.
Pag.  89
Figure 9.4 Containers Traffic for Selected 
Scandinavian Ports (2014)
Port of Stockholm
Port of Copenhagen-Malmo
Port of Oslo
Port of Gothenburg
Total 
TEUs (Source: ESPO, Eurtostat, Maritime insight)
0 280.000 560.000 840.000 1.120.000 1.400.000
TEUs Flow
9.4 Ports’ Traffic Data
A relevant investigation is the analysis of the traffic (containers, TEUs, throughput, number 
of vessels and Ro-Ro) in order to evaluate the ports’ traffic. The table below (9.5) provides 
a general overview about the total throughput, number of vessels, number of containers 
and number of TEUs by port in 2015. From the data collected by ESPO (2015), is 
confirmed that the Port of Gothenburg has a better performance comparing to the other 
ports; by contrast the Port of Stockholm receives a higher number of vessels (16,084). 
Table 9.5 Ports’ Traffic Throughput-Containers 2015
2015 (1) Port of Oslo 
Port of 
Stockholm 
Port of 
Copenhagen
-Malmo (3)
Port of 
Gothenburg 
Total 
1
TOTAL THROUGHPUT 
(1.1+1.2)
5.773.000 8.336.000 14.500.000 38.200.812 66.809.812
1.1 Inward 4.677.000 5.315.000 19.739.229 29.731.229
1.2 Outward 1.096.000 3.021.000 18.461.583 22.578.583
2
NUMBER OF 
VESSELS
9.236 16.084 7.800 11.000 44.120
3
NUMBER OF 
CONTAINERS 
(3.1+3.2)
116.897 34.034 - 476.961 627.892
3.1 Empty (3.1.1+3.1.2) 42.512 9978 81.362 133.852
3.1.1 Inward 2.361 888 51.749 54.998
3.1.2 Outward 40.151 9.090 29.613 78.854
3.2 Loaded (3.2.1+3.2.2) 74.385 24.056 395.599 494.040
3.2.1 Inward 60.118 18.039 193.932 272.089
3.2.2 Outward 14.267 6.017 201.667 221.951
4
NUMBER OF TEUs 
(4.1+4.2)
195.459 50.943 164.000 819.953 1.230.355
4.1 Empty (4.1.1+4.1.2) 71.585 15.354 139.071 226.010
4.1.1 Inward 3.764 1.523 97.358 102.645
4.1.2 Outward 67.821 13.831 41.713 123.365
4.2 Loaded (4.2.1+4.2.2) 123.874 35.589 680.882 840.345
4.2.1 Inward 99.109 27.130 323.029 449.268
4.2.2 Outward 24.765 8.459 357.853 391.077
5 Number of Ro-Ro 726 3.943 715 9.288 14.672
Note: this table identify thousands with the “.” “dot”, and decimals with the “comma” “,”
1) Source data ESPO, 2015 
2) Author’s data elaboration
3) CMPort.com 
Pag.  90
9.5 Ports Characteristics Overview
Ports differs in infrastructural characteristics, different services provided, water condition 
during the winter, and facilities. Table 9.6 summarise the different characteristics for the 
selected ports (see appendix “G” for details). Other ports’ specifications are in the tables 
9.7 - 9.8. 
 
Table 9.6 Port’s Characteristics
P. Malmo P. Copenhagen P. Oslo P. Stockholm P. Gothenburg 
Port details
Port Number (1) PO3225 PO1422 PO2303 PO2626 P2582
UNLOCODE SEMMA DKCPH NOOSL SESTO SEGOT 
Latitude (2) 55° 37' N 55° 42' N 59° 54' N 59° 20' N 57° 41' N 
Longitude (2) 12° 59' E 12° 38' E 10° 44' E 18° 3' E 11° 51' E 
Max Draught 12.5 11.5 11 11 19.05 
Max LOA 260 NA NA 295 350
Max Offshore 
BCM NA NA NA NA NA
Max Beam 45 NA NA 32.3 NA
MAX DWT NA NA NA NA 225.000
Port Facilities 
Container 
Facilities
Y Y Y Y Y
RoRo Facilities Y Y Y Y Y
Navigation 
Dock density (3) 1010 1005 1025. 1005. Average 1013.
Weather 
Malmo : the harbour is practically 
never closed by ice, drift ice can be 
encountered in the outer part of the 
dredged channels even during 
normal winters. 
Copenhangen: Prevailing winds: 
W’ly. 
-
Ice: Navigation is 
maintained 
throughout the 
year with the 
assistance of 
icebreakers. 
However, branch 
passages are 
often closed 
during severe 
periods of icing.
Ice: The harbour 
is generally ice 
free, although it 
may have ice in 
the period 
January to March 
in hard winters.
Pag.  91
Tables 9.5 and 9.6 show different results in terms of vessels traffic. 
The port of Stockholm received 16,084 vessels (ESPO, 2015), instead the data are not 
available in Sea-Web for the year 2015 (2016). Instead, regarding the Port of CMP there is 
Tugs 3
Compulsory for 
vessels over 
100m in length, 
passing through 
bridges. 
Tugs are 
available by 
arrangement with 
vessel's agent 
prior to arrival/
departure. The 
largest tugs are 
equipped for fire 
fighting 
2 ("Tug" 2,400hp, 
30 board pull; 
”Ted" 1,400hp,  
15 bollard pull )
min. 3 tugs. 
Other info 
Appendix. 
Port Description
Number of 
vessels 8000 Approx 9,020 NA NA
Tons of cargo 14,400,000t cargo 
5,820,000t of 
cargo  
Approx 
8,500,000 of 
cargo,
38,200,000t of 
cargo
TEUs 141,000TEU 202,500TEU 27,840TEU 820,000TEU 
MAX size 
LOA 260m, 
beam 45m, 
draught 12.5m 
Provestenen 
Harbour: 
Draught 
11.5m. 
Max draught in 
Drobak 
Passage is 
12.0m, 
alongside 
11.0m.
Largest vessels 
handled: 
Passenger and 
dry cargo 
vessels: LOA 
295m, beam 
32.3m, draught 
11.0m.
Hammerby 
Lock: Length 
115m, width 
17.4m, depth 
6.5m. 
Vessels 
transiting Lake 
Maleran max 
airdraught 
25.2m. 
LOA 350m, 
tanker draught 
19.05m (18.6m 
if water level 
low), container 
draught 11.5m, 
225,000DWT. 
Max airdraught 
in Inner harbour 
45m.
 
Gota River: 
LOA 89m, 
beam 13.4m, 
draught 4.7m, 
with special 
permission up 
to 5.4m. 
Airdraught 
27.0m. 
Bohus: LOA 
135m, beam 
16.5m. 
Trollhattan 
Kanal: LOA 
125m and 
beam 16.5m. 
Note 
1) Sea-web 2016
2) Conversion latitude and longitude ports in the appendix “G”
3) Dock density, see definitions. 
4) Y = YES
5) NA = Not Available
P. Malmo P. Copenhagen P. Oslo P. Stockholm P. Gothenburg 
Pag.  92
a slight difference between the two sources; similar situation is for the port of Oslo. Instead 
the PoG received 11,000 vessels in 2015, but this data cannot be confirmed by Sea-web 
because it wasn’t available. 
Table 9.7 shows infrastructure available for the selected ports; some data were not available, even 
trying to combine different sources. 
Table 9.7 Facilities Available in Ports
P. Malmo (1)
P. 
Copenhagen 
(2)
P. Oslo (1) P. Stockholm (1)
P. 
Gothenburg 
(1) 
Warehouses (w) 200.000 88.500 4 (tot: 140,000m2 ) 137.200
Car storage (m2) 250.000 NA NA 63.000 (5)
Container storage 
(m2) 50.000 NA NA 180.000 (5)
Roofed storage (m2) 16.000 NA NA NA
Ro-Ro Storage: NA NA NA 150.000 (5)
Land  storage area 
(m2) 250.000
1.255.000 
(land area) (3)
1,140,000 
( land area) 
(4)
1.000.000
Terminal buildings 4.700 NA NA NA
Note 
1) Sea-web 2016
2) CMPort.com
3) Port of Oslo 2016
4) Port of Stockholm 2014
5) Port of Gothenburg (private source)
Pag.  93
Table 9.8 summarised the different cranes available in ports. The data have been 
elaborated in the next paragraphs in order to compare the cranes performance among the 
ports. 
Table: 9.8 Equipment Available in Ports - Cranes
(1) P. Malmo
P. 
Copenhagen P. Oslo P. Stockholm P. Gothenburg 
Stationary cranes 
3 * 20t - - -
Mobile crane
< 50t 1 * 40t 1 * 16-23t - 1 * 40-50t
< 100t 2 * 64t 1 * 20-100t - 1 * 40-60t
<300t - - 1 * 260t - 
Gantry Crane 
< 40t 1 * 40t - 2 * 35-40t - - 
< 50t - 3 * 50t 1 * 35-50t 2 * 42t; Outreach 22m. 2 * 40-45t
< 50t 2 - - 1 * 40-50t - - 
< 70t - - - - 4 * 40-70t
Post Panamax 
crane - - - - 2 x 45-70t 
Note 1) Sea-web 2016
2) CMPort.com 
Pag.  94
9.5.1 Berth descriptions
In this paragraph are reported several tables to highlight the different infrastructure 
characteristics (berth length, depth, and draught) to measure the competitiveness of the 
ports. The fours ports have other berths such as berth for cruises and berths for tankers, 
but in this investigation were considered only the following berths: RO-RO, containers and 
general cargo. The data are elaborated in the next paragraphs.
Table 9.9 Port of Stockholm Berth
Port of 
Stockholm 
Area (1)
Berth 
number 
Length 
(m)
Depth 
Use (m) 
Average 
depth (m)
draught Use 
Stadsgarden 
(and 
Masthamnen)
S162 to 
S163 200 7,5 7,5
Ferry Terminal. Cruise vessels. Ro-Ro 
ramp to SE of 163 (fore or aft) 25m 
wide. 
S164 200 7,5 7,5
Ferry Terminal. Cruise vessels. Ro-Ro 
ramp to SE of 163 (fore or aft) 25m 
wide. 
Vartahamnen 
Cruise and 
Ferry 
terminal 
V508 180 8,5 8,5
Ro-Ro. Fast passenger and freight 
ferries. Ramp (fore and aft loading) 
14.0m to W end. (3 other side ramp 
areas 9m and 10m). Pier area due to 
be redeveloped and expanded. 
V509 to 
V512 298
8,0 to 
8,5 8,25
Ro-Ro. Fast passenger and freight 
ferries. Ramp to W end (fore and aft 
loading) 23m wide. Pier area due to 
be redeveloped and expanded. 
V515 to 
V520 367
7,5 to 
8,5 8
Ro-Ro. Fast passenger and freight 
ferries. Ramp to W end (fore and aft 
loading) 21m wide. Pier area due to 
be redeveloped and expanded. 
Frihamnen 
Cruise and 
Ferry 
Termnal
F641 to 
640 
(Quay 4) 
110 7,5 7,5 Ro-Ro berth (see F630 and F650) 
F650 to 
F652 
(Quay 5)
222 7,5 to 8,5 8
Ro-Ro ramp at SW (Quay 4) 55m 
wide. 
Container 
Terminal 
Frihamnen 
(CTF) 
F653 to 
F655 240
8,5 to 
9,0 8,75 Containers 
Total (2) 1817 64
Average (2) 227,13 8
Note
this table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web
2) Our analysis
Pag.  95
Table 9.10: Port of Malmo Berth
Port of Malmo 
Area (1)
Berth 
number Length (m)
Depth Use 
(m) 
Draught 
(m) Use 
New Harbour 504 175 7,2 6,6 Ro-Ro, ferries, draught 6.6m 
505-506 180 7,2 6,6 Ro-Ro, ferries, draught 6.6m 
Free port 606-604 120 9,1 8,6 Ro-Ro and general cargo, LOA 240m, beam 32.5m,
605 185 8,1 - Ro-Ro
612-615 500 9,2 8,6 General cargo/Ro-Ro,
Toyota Nordic 
Hub Terminal 616 325 10,0 -
Ro-Ro
617 190 9,0 - Ro-Ro
Nordo-Link 
Ro-Ro 
Terminal
702 245 8,5 - Ro-Ro and Ro-Pax ferries 
703 245 8,5 - Ro-Ro and Ro-Pax ferries 
704 245 8,5 - Ro-Ro and Ro-Pax ferries 
Malmo 
Container 
Terminal 
(North 
Harbour)
705 150 9,2 - LOA 240m
706 150 9,2 - LOA 240m
Total - 2535 103,7 - -
Average - 211,25 8,6 - -
Note
this table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web
Pag.  96
Table 9.11 Port of Copenhagen Berth
Port of Copenhagen 
Area (1)
Berth number/
name
Lengt
h (m)
Depth 
Use (m) 
draug
ht Use 
MELLEMBASSIN (NU 
TOLDHAVN) 220, DFDS 27 9 -
Ro-Ro ramp area for Berth 221, 28m 
wide (fore or aft). 
221, DFDS Ostre 
leje 173 9 - Passengers and cargo.
222, DFDS Vestre 
leje 200 9 -
Passengers and cargo. Ro-Ro ramp area 
22m wide (fore or aft). 
227, DFDS Ro/Ro 
leje 
210 7
-
Passengers and cargo. Ro-Ro ramp 24m 
wide (fore or aft). 
ORIENTBASSIN 
(FRIHAVN) 255, Traelastkaj 
72 9,5
-
Containers. End of Orientbassinet. 
256, Traelastkaj 72 6 - Containers. End of Orientbassinet. 
257, Levantkaj 98 6 - Containers. 
258, Levantkaj 130 9,5 - Containers. 
259, Levantkaj 33 9,5 - Containers. Ro-Ro.
260, Levantkaj 105 9,5 - Containers. 
261, Levantkaj 100 9,5 - Containers. 
262, Levantkaj 100 9,5 - Containers. 
263, Levantkaj 112 9,5 - Containers. 
264, Levantkaj 100 9,5 - Containers. 
265, Levantkaj 100 9,5 - Vehicles. General cargo. Ro-Ro. 
266, Levantkaj 98 9,5 - Vehicles. Ro-Ro. 
FAERGEHAVN NORD 393 100 6 - Containers. 
394 150 6 - Containers. 
395 100 6 - Containers. 
396 100 6 - Containers. 
KALKBRAENDERIHAV
NEN
401, 
Kalkbraenderilobs
kaj 
115 6,7 - Dry bulk. Ro-Ro (fore or aft). 
402, 
Kalkbraenderilobs
kaj 
100 6,3 - Ro-Ro (fore or aft) 
CHRISTIANSHOLM 642, Vestkaj 147 6 - Palletised cargo 
Total (2) - 2542 184 - -
Average (2) - 110,5 8 - -
Note
this table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web 2016
2) Our analysis
Pag.  97
Table 9.12 Port of Oslo Berth
Port of Oslo 
Area (1)
Berth 
number/
name
Lengt
h (m)
Depth 
Use (m) 
Average 
depth (2) Draught Use 
Filipstad 
Terminal:
General 
cargo 
Berth 
463 8,7-9,1 8,9 - General cargo, breakbulk, Ro-Ro and containers 
General 
Cargo 
Terminal: 
Kneppeskj
aer 165 6,4-8,0 7,2 - PCC, containers and Ro-Ro
Container 
Terminal:
Sondre 
Sjursoykai 304 12 12 - Containers
Container 
Terminal 
(South):
Ormsundk
aia 287 9,3-9,6 9,45 - Containers
Total (2) - 1219 - 28,65
Average (2) - 304,75 - 7,1625
Note
this table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web
2) Our analysis
Pag.  98
Table 9.13 Port of Gothenburg Berth
Port of 
Gothenburg 
Area (1)
Berth 
number 
Length 
(m)
Depth Use 
(m) 
Average 
depth (m)
Average 
Alvsborgshamn
en Ro-Ro 
Terminal
751 203 9,8 9,8 LOA 180m, draught 9.3m. Width of ramp 26m
750A 47 9,8 9,8 Ro-Ro ramp width 50m. Draught 9.3m
750 225 9,8 9,8
Ro-Ro. LOA 200m, draught 9.3. Width of ramp 
26m.
713 200 11,0 11,0
Ro-Ro. LOA 230m, draught 8.9m. Width of ramp 
26m.
712 149 11,0 11,0
Ro-Ro. LOA 230m, draught 10.5m. Width of ramp 
43m.
711 232 11,0 11,0 Ro-Ro. Draught 10.5m
710 265 11,0 11,0 Ro-Ro. Draught 10.5m. Width of ramp 26m
702 210 11,0 11,0
Ro-Ro. LOA 197m, draught 10.5m. Width of ramp 
24m.
700 190 9,5 9,5
Ro-Ro. LOA 184m, draught 9.0m. Width of ramp 
28.7m.
AMP Container 
Terminal: Total 
length 1,750m 
(source PoG 
and sea-
web.com)
643 135 14,2 14,2
Ro-Ro. Width of ramp 54m. Max LOA 250m when 
draught 10.5m, max LOA 300m when draught 
9.5m 
642 95 14,2 14,2
Continuous length 640m, max LOA 250m when 
draught 10.5m, max LOA 300m when draught 
9.5m
641 190 14,2 14,2
Continuous length 640m, max LOA 250m when 
draught 10.5m, max LOA 300m when draught 
9.5m 
640 190 14,2 14,2
Continuous length 640m, max LOA 250m when 
draught 10.5m, max LOA 300m when draught 
9.5m 
615 190 14,2 14,2
Ro-Ro. Width of ramp 27m. Continuouse length 
1,132m, LOA 200m, draught 10.4m
614 190 14,2 14,2
Continuous length 1,132m, LOA 390m, draught 
11.5m
613 190 14,2 14,2
Continuous length 1,132m, LOA 390m, draught 
11.5m
from 610 
to 612 570 14,2 14,2
From the east for 500m, the water depth is 14.2m 
MW. At the rest of berth, the water depth is 12.0m 
except for the last 220m where the depth is 11.9m 
MW. Continuous length 1,132m, draught 13.5m
Logent Ports & 
Terminals Car 
Terminal
601 135 14,2 14,2 Vehicles. LOA 290m
600 170 14,2 14,2 Vehicles. LOA 170m
Stena Line 
Germany 
Terminal - 
Majnabbehamn
en
46 60 9 9 Reserved space
Pag.  99
Port of 
Gothenburg 
Area (1)
Berth 
number 
Length 
(m)
Depth Use 
(m) 
Average 
depth (m)
Average 
47 138 9 9
Ro-Ro, passengers, containers. Ramp 55m long 
by 27m width
48 137 9 9
Ro-Ro, passengers, containers. Ramp 55m long 
by 27m width
49 140 9 9
Ro-Ro, passengers. Ramp 55m long by 26.8m 
width
Total (2) 4251 271,9
Average (2) 184,83 11,82
Note
this table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web, 2016
2) Our analysis
Pag.  100
Table 9.14 add extra information about each single port, such as working hours, holiday, 
transport network availability. 
Table 9.14 Extra info
(1) SE DK NO SE SE
Malmo Copenhagen Oslo Stockholm Gothenburg 
Public holidays 
(fixed) (not  
days) 
14 7 9 + All weekends 16 + ALL 
weekends
14
Public holidays 
(moveable) (not 
days ) 
7 8 8 7 7
Working hours
Straight time 
0700-1600hrs, 
overtime 
1600-0600hrs.
Normally Mon-
Thu 
0700-1500hrs, 
Fri 
0700-1430hrs. 
All weekend 
work is 
overtime.
Open throughout 
24 hours. Day 
watch 
0700-1530hrs. 
Sat: Voluntary 
and with 
overtime pay.
Normally Mon-Fri 
0700-1600hrs.
Normally Mon-Fri 
0700-1600hrs;  
Container 
Terminal 
0700-2359hrs, Fri 
0630-2200hrs. All 
other hours are 
overtime. The oil 
ports work 
throughout 24 
hours.
Surveyors:
Class and cargo 
surveyors are 
located at 
Malmo and 
Gothenburg.
- Available.
All surveyors for 
both dry and 
liquid cargo are 
available.
-
Barges available none available - vailable from towage company.
Drydocks:
Small drydock 
and shiplift 
available.
none Not available in Oslo. 
Two graving 
drydocks 
available. Size of 
vessels that can 
be handled: LOA 
185m, max beam 
22m, max 
draught 8.5m. 
2
Transport 
Malmo Transport: Nearest 
airport: Sturup/Malmo approx 
30km; City International located in 
port area with service directly to 
Copenhagen Airport which has 
world wide connections. Nearest 
railway: Malmo Central (passenger 
and freight) 2km. Nearest 
motorway: Approx 2km. 
Copenhagen Nearest airport: 
Copenhagen (Kastrup), 8km from 
city centre. 
Nearest railway: Copenhagen.
Nearest airport: 
Gardermoen 
Airport, approx 
50km from Oslo 
City Air Terminal. 
Nearest railway: 
Oslo Central, 
close to the port.
Nearest airport: 
Arlanda 
International 
Airport, 45km, 
Bromma Airport, 
8km. 
Airport facilities: 
Arlanda 
International full 
facilities, Bromma 
mostly domestic 
flights. 
Nearest railway: 
Stockholm City.
Nearest airport: 
Landvetter 30km. 
Nearest railway: 
Central Station 
(city centre).
Note 1) Source: Sea-web
Pag.  101
9.6 Ports’ Characteristics Analysis 
Considering the table 9.8 (Equipment available in Ports - Cranes), in the next table (9.15) 
the different cranes and handling capacity (in tonnes) are considered to develop the port’s 
crane tonnes efficiency indicator, in order to analyse which port perform better 
comparing to the others. 
Table 9.15 Port’s Crane Tonnes Efficiency Indicator
In order to calculate the port’s crane tonnes efficiency indicator the weighted average is 
computed. 
For those ports with the crane range (in tonnes), e.g. Oslo Gantry crane (quantity = 2) and 
different capacity (35-40t) (table 9.8), the average was calculated = 37.5t ((35+40)/2); the 
same formula was applied to the other ports’s crane tonnes range. 
The first step is to calculate the weighted average by port in column “A”, as below: 
Port of Stockholm = [(1*260) + (2*42) / (260+42)] = 260.28
Sta?onery	cranes	(1)	 Mobile	cranes	(1)	 Gantry	cranes	(1)	
WA	by	
port	(A)
Percentage	on	
total	(B)
Quantity Tonnes Quantity Tonnes Quantity Tonnes - - 
Port of 
Copenhagen-
Malmo 
3 20 1 40 1 40 268,70 19,14
2 64 3 50
Port of Oslo 
1 19,5 2 37,5 197,22 14,05
1 60 1 42,5
1 45
Port of 
Stockholm 
1 260 2 42 260,28 18,54
Port of 
Gothenburg
1 45 2 42,5 400,46 28,52
1 50 4 55
2 57,5
Total tonnes 970,5
Total Weighted 
Average
1.404,12
Note
This table identify thousands with the “.” “dot”, and decimals with “,” “comma”
1) Source: Sea-web 2016. 
2) WA: Weighted average mean
Pag.  102
The second step is to calculate the total weighted average (using the similar approach 
above), in order to compare the different ports’ cranes. The total weighted average 
identified is 1.400,12. 
The third step is to relate the weighted average by port with the total weighted average 
(proportion); the proportion is calculated as below: 
Port of Stockholm: [(260.28/1.404,12) * 100] = 18.54 
Table 9.15 highlights the PoG as the port with higher tonnes capacity (28.52 per cent, 
compared with the other ports). In second position the Port of Copenhagen-Malmo with 
19.10 per cent crane efficiency; third is the Port of Stockholm with 18.52 per cent; and last 
one is the Port of Oslo with 14.03 per cent.
The figures above explain that PoG, compared to the others ports (cranes and capacity), 
has the most appropriate equipment (cranes) able to manage large vessels (in tonnes 
terms).
Pag.  103
Table 9.16 Performance Indicators 
The Performance indicator 1) Port’s Crane Tonnes Efficiency Indicator, was previously calculated 
in table 9.15
The Performance indicator 2) Weighted Average Berth (see appendix G, table G.3) was 
calculated to identify which port in average terms has the longest berths length and depth. 
The result is that PoG has a longer berths length and depth, in relation to the other ports. 
The Performance indicator 3), Throughput by Port / Total Four Ports, was calculated taking into 
consideration the figures in the table 9.5, n order to compare the port’s throughput with the total 
throughput (four ports). The result is that PoG, in relation to the other ports, has 57.18 per cent of 
the total throughput.   
(1)
Port of 
Copenhagen-
Malmo
Port of Oslo Port of 
Stockholm 
Port of 
Gothenburg 
Total
1
Port’s Crane Tonnes 
Efficiency Indicator 
(%)
19,14 14,05 18,54 28,52 -
2
Weighted Average 
Berth (length and 
depth)
8,34 9,57 8,05 12,12 -
3
Throughput by Port 
(2015) / Total Four 
Ports (2015)
21,70% 8,64% 12,48% 57,18% -
4 Throughput (2015) /Total Berth Length 2.761 4.736 4.588 8.986 5.328,16
5
TEUs (2014) / 
Containerships 
(2014)
372,75 550,72 309,09 1063,06 721,02
6 Throughput (2015) / Vessels (2015) 1.858,97 625,05 518,28 3.472,80 1.514
7 Vessels (2015) / 12 months 650 770 1.340 917 3.677
8 Containerships (2014) / 12 months 32,42 32,17 14 66 144
9 RO-RO (2015) / 12 months 60 61 329 774 1.223
10
Percentage of 
containerships by 
port (2014)
22,52% 22,35% 9,55% 45,57% - 
Note 
This table identify thousands with the “.” “dot”, and decimals with “,” 
“comma”
1) our analysis
Pag.  104
The Performance indicator 4) Throughout / Total Berth Length, is calculated considering : 
[(Cargo Throughput 2015) / (Tot. Berths Length)].
Cargo Throughput, data in table 9.5 (1).
Total berth length (dedicated port data in tables 9.9 - 9.10 - 9.11 - 9.12 - 9.13). 
Example: Port of CMP = [Cargo Throughout (14,500,000) / Tot. Berth Length (2,710 + 2,542)] = 
2,761. The result represent the berth utilisation rate (by meter). The total is calculated considering 
the Total Throughout and the Total berths length (among the ports). PoG has the higher berth 
utilisation rate, considering the total length and total throughput.
The Performance indicator 5) Number TEUs / Number of Containerships is calculated 
considering:
[( Number TEUs (2014) / (Number of container ships (2014)]. 
Number of TEUs (data in figure 9.4 or Appendix H, table H.6).
Number of Containerships (data in figure 9.3 or Appendix H, table H.1).
This indicator shows which port, in average terms, received more TEUs related to the number of 
containerships. The total considered the total number of TEUs 2014 (1,245,210) for the selected 
ports and the total number of containerships for the selected ports 2014 (1,727) (see Appendix H, 
table H.2). The PoG, in relation to the number of containerships, receives (discharge) more TEUs 
(1,063) in relation to number of ships.
The Performance indicator 6) Throughput / Vessels is calculated considering: 
[(Throughput by port, 2015) / (Number of Vessels by port, 2015)].
Throughput (data in table 9.5 (1). Number of Vessels (data in table 9.5 (2).
This indicator shows which port receive the higher level of throughput by vessels. The total 
considered (1) 66,809,812 and the total number of vessels (2) 44,120. In average terms the PoG 
has the higher level of throughout by vessels. 
The Performance indicator 7) Vessels / 12 months is calculated considering: 
[(Number of vessels by port (2015) / (12 months)]. 
Figures of vessels in table 9.5 (2). 
This indicator shows, in average terms, the number of vessels per month by port. The port of 
Stockholm has, in average terms, the higher number of vessels. 
The Performance indicator 8) Containerships / 12 months is calculated considering: 
[(Number of containerships (2014) / (12 months)].
Figures of containerships (2014) in table H.1 (appendix H). 
This indicator shows, in average terms, the number of containerships per month by port. The PoG 
has, in average terms, the higher number of containerships (66 per month). 
The Performance indicator 9) Ro-Ro / 12 months
[(Number of Ro-Ro (2015) / (12 months)]. 
Figures of Ro-Ro (2015) in table 9.5 (5). 
This indicator shows, in average terms, the number of Ro-Ro’s per month by port. The PoG has, in 
average terms, the higher number of Ro-Ros (774 per month). 
Pag.  105
The Performance indicator 10) Percentage of containership by port, is calculated considering: 
the figures in tables H.1 and H.2 (appendix H). The percentage calculated considered the total 
number of containerships by port and the total number of containerships. 
Example: PoG = [(787) / (1727) * 100] = 45.57 per cent
It results that PoG received in 2014, 45 per cent of the total containerships, for the selected ports. 
9.7 Port’s Latest Developments
In order to understand the ports’ economical performance a short summary about future 
development is provided. This will provide the reader a general overview about port’s 
investment, goals to achieve and in some cases country’s preferences. 
9.7.1 Port of Copenhagen-Malmo (CMP)
In Copenhagen ports’ side, a new dry bulk area in South part of Provestenen is underway. 
When the infill work is complete Provestenen area will be extended by 50% and water 
depth at the new quays will be 13.5m (Sea-web.com, 2016a). 
Malmo: a Low Sulfer Fuel Terminal is being built to help ships with Emission Control Area 
(ECA).The project if being financed by the port in partnership with Scandinavian Tank 
Storage, and will store fuel supplied by Statoil. It is expected that 170 vessels will use the 
new terminal for refuelling per year (Sea-web.com, 2016b). 
Development of a 900,000m2 industrial park is currently underway in the Northern Harbour 
(Norra Hamnen). As increasing number of companies begin operating in the Northern 
Harbour, capacity will be increased by the addition of more terminals, docks, berths and 
railway tracks. In addition to the industrial park two facilities for LNG are planned. 
Container operations in Free Port are due to be moved to the Northern Harbour, freeing up 
space to increase the car storage capacity (Sea-web.com, 2016b). 
There are plans for expansion in the Dry Bulk area of Berths 740 to 760 with a new wharf 
side area providing extra berths and two extra piers in the Nordo Link Ro-Ro harbour area. 
CMP announced on 27th November 2014 that a barge service will be introduced between 
the two cities. "Daily barge traffic between the cities will simplify transportation of 
containers and other freight. The shortcut over the strait will be flexible and cost-effective 
for freight customers, however it will also deliver environmental benefits”. CMP officials 
have said that they want to develop the port into a regional, northern European transport 
hub. The airports of both cities are also located along the motorway and railway link 
between the two cities, which further contributes towards the realisation of the transport 
hub ambitions (Sea-web.com, 2016). 
9.7.2 Port of Oslo 
According to Sea-web (2016d) the port of Oslo announced “Norway project looks to spur 
port and ship electrification (Sea-web, 2016d); “Inspired by Norway’s successful promotion 
of electric cars, maritime organisations are working with engineers and investors to study 
Pag.  106
how to expand the country’s shore power and boost its use of electric- and hybrid-powered 
ships”. 
Bjorvika (Oslo area) is due for urban development, Sorenga (Oslo area) will act as a 
temporary transit depot for empty containers until new facilities are developed at Sydhavna 
(from Kongshavn down through Sjursoya, Kneppeskjaer Pier to Ormsund Quay). A seabed 
tunnel has to be constructed under Bjorvika before the other developments start (Se-web, 
2016c). 
9.7.3 Port of Stockholm 
The Port of Stockholm is developing the entire Vartahamnen, Frihamnen and Loudden 
area in a joint project with the City of Stockholm. The largest project is the Varta Pier 
expansion. Due to complete in 2016 at a cost of $300M, it will have a new passenger 
terminal, five quay-berths and a total of quay length of 1200 m. 
Vaatahammen Cruise Terminal: Construction and dredging is underway to develop a 
dedicated cruise terminal by converting the existing 3,000m2 cargo warehouse located at 
Frihamnen. The adjacent pier will also be extended by 130m, and increase depth from 9m 
to 10.5m, to enable the facility to accommodate 3 Panamax cruise vessels simultaneously, 
with completion expected in 2015 (Sea-web, 2016e). 
According to Port of Stockholm, (2014), new development are planned and partially 
realised as the new container terminal (CTF) where several actors are involved such as 
Hutchinson Port Holding (HPH), Greencargo, MSC Sweden AB, Team Lines Sverige AB, 
Unifeeders Sweden AB, CMA-CGM (Port of Stockholm, 2016). 
9.7.4 Port of Gothenburg 
The Port of Gothenburg, has announced the construction of a new freight terminal to be 
completed after 2020 to handle the increase in demand for sea transport via the port. The 
terminal will have an area of 220,000m2 and a depth of 11.0m (Sea-web.com, 2016g).
"We are extremely pleased to receive this decision, which will strengthen Gothenburg as 
the logistics capital of the Nordic region. The terminal is an important part of our future 
expansion and will present us with an opportunity to handle the increase in demand for 
sea transport via the Port of Gothenburg," said Magnus Kårestedt, Port of Gothenburg 
CEO, in a statement (3rd March 2016) (Sea-web.com, 2016f). 
The port of Gothenburg is a type of port seeking on continuous improvements, for example 
it simplified the call notification system as reported by the authority and local news: “Ships 
making calls at the largest port in the Nordic countries can now notify the relevant 
authorities through a new platform using Swedish Maritime Administration system 
Reportal. It replaces Port of Gothenburg’s now redundant VTMS system (Sea-web.com, 
2015a). 
Pag.  107
PoG announced to create a new 1 million m² logistics park with industry partners. The new 
investment expected to generate more than 2,000 jobs and be completed by 2025. 
Speaking to IHS Maritime, a port spokeswoman stated, “Gothenburg Port Authority will 
invest approximately SEK1 billion (USD122 million) and the other four land owners 
involved – NCC Property Development, Prologis Nordic, Eklandia Fastighets, and 
Bockasjö – about SEK3 billion.” (Sea-web.com, 2015b). The new park will be built directly 
adjacent to the port's Hisingen freight terminals and Gothenburg CEO Magnus Kårestedt 
described the project as an enormous investment and a golden opportunity for every 
company looking to establish a warehouse directly beside the largest port in Scandinavia 
(Sea-web.com, 2015b).
Gothenburg is currently the only port in Sweden with the capacity to receive the world's 
largest container vessels and has just opened a 900 m quay extension to the container 
terminal operated by APM Terminals. The port also has terminals for oil, cars, ro-ro, and 
passengers (Sea-web.com, 2015b). 
PoG, in order to maintain his green philosophy, decided to attract green ships with a 
discount on harbour dues from 10 to 30 per cent. Seven shipping lines were involved and 
25 ships already signed for the agreement and environmental scheme. (Sea-web.com, 
(2015c)
Vessels scoring 30 points or less on the Environmental Ship Index and Clean Shipping 
Index qualify for the lower figure, while those using LNG get the higher one (Sea-web.com, 
(2015c).
According to IHS and Sea-web.com (2015d), PoG decided to maintain the same tariffs of 
2015 for 2016. 
Image 9.2 New PoG Logistics Park
Source: Sea-web (2015d)
Pag.  108
"Our aim behind this move is to reinforce industrial growth, shipping, and the port," stated 
PoG managing director Magnus Kårestedt, "Shipping costs become transport costs for 
industry. By doing our best to keep port charges down, we can contribute to maintaining a 
strong cluster of shipping companies in Gothenburg and a broad range of services to key 
markets."  "We also hope other parties in the transport chain do everything to keep costs 
to a minimum. The state fairway charge, for example, doesn't exist throughout the rest of 
Europe (except Finland) and simply makes transport more expensive for Swedish 
industry."  (Sea-web.com, 2015d). 
 
The port of Gothenburg is planning a new energy port at Risholmen, situated at the 
entrance to the port of Gothenburg. Five new berths are planned, start of construction is 
due in 2018 and completion expected by 2030. Future development projects should 
increase forest exports through the port including new road and rail links and a weather-
protected forest terminal (Sea-web.com, 2016g).
 
In the shorter term PoG:  
New dolphins/mooring posts at Alvsborg Ro/Ro AB: to replace a number damaged in 
various collisions and projects at the Vehicle Terminal in order to receive even larger car 
carriers. 
Extensive repair and reinstatement of 70,000 square metres of ground space is in 
progress in Alvsborg Ro/Ro AB's terminal  
Upgrade of the container areas within the container terminal: APM Terminals Gothenburg 
and The Port of Gothenburg are co-funding the upgrade. Also in the container terminal, 
work is in progress on upgrading bollards to ensure the safe arrival of larger vessels within 
the whole terminal. 
Product pipelines are being extended to put in place a complete system for oil right out to 
the Rya Harbour. This is being done in order to be able to use the Rya Harbour more to 
ease the pressure on the Skarvik Harbour and thus be able to carry out maintenance work 
at Skarvik. At the same time, redevelopment of service platforms is in progress to improve 
the working environment. 
Dredging sludge at the Lundby Harbour: A strategically important issue is the potential to 
take care of contaminated dredging sludge, thus ensuring that in time our fairways and 
docks do not silt up again. As part of this process, we have completed an area in the old 
dock at the Lundby Harbour during the year and planning of new areas is underway. 
In the long term, expansion of the fairways is planned into the Tor Harbour to increase the 
depth in order to receive very large, fully loaded tankers (VLCCs). The aim is to develop 
the energy harbour as a transit harbour for, for example, oil from Russia. Alongside depths 
at the Container Terminal may also be deepened (Sea-web.com, 2016g).
Pag.  109
9.8 Voyage Calculation 
A voyage calculation is provided in order to compare part of the costs necessary to reach 
the four ports. 
The identified departure port is Shanghai - China, because the major navigation route is 
ASIA - EUROPE. 
In order to perform a proper calculation, the following characteristics are identified: 
Containerships : Triple E class Mærsk Mc-Kinney Møller
Capacity : 18,270 TEU
Length : 400 metres
Draft : 14.5 metres
Beam : 59 metres
Height : 73 metres
Top speed : 25 knots (46 km/h)
Deadweight : 165,000 tonnes
Gross Tonnage : 194,849 GT
Deadweight Tonnes (DWT) : 194,153
Our assumption: 
Contract type : Time charterer 
Fixed costs : 60,000USD/day
Capacity : 18,000TEUs (9,000 containers 40feet)
Weight per TEUs : 2 tonnes 
Total containers weight: 36,000 tonnes 
Fuel consumption per day: 190tons 
Voyage speed : 20 knots 
Fuel price (open sea) (IFO  0380): 233USD/mt
Fuel price for SECA area (MGO):  465USD/mt
Discharging day: week days 
Suez Canal charges: are not considered because Suez Canal tool calculator required two 
parameters : SCGT (Suez Canal Gross Tonnage) and SCNT (Suez Canal Net Tonnage); 
those parameters are only available for the shipping company (Suez Canal Tonnage 
Certificate). 
The containerships will discharge 18,000 TEUs to the dedicated port. The Port of 
Stockholm, the Port of Oslo, and the Port of Copenhagen-Malmo do not have the depth 
water adapted to host Maersk Triple E. The Northern Sea route is considered with the 
same vessel, and during the period between March/April and September; no icebreakers 
costs are considered. 
This calculation want demonstrate the different navigation routes and related  discharging 
ports’ costs. Ports apply different prices : per container (in tonnes), per TEUs, or total 
vessel GT. 
Pag.  110
Table 9.17 Voyage Calculation 
The voyage calculation cost show that the less expensive port, to transport 18,000 TEUs (or 9,000 
containers, with the weight of 2 tonnes) is the Port of Gothenburg. 
The preferred route by the shipping lines might be the Northern sea or the Suez-Gibraltar route. 
In the analysis was also considered the different fuel to use in open sea and in SECA area. 
Ports applies different rates to the discharged containers, and in our case was considered only the 
discharging fees by TEU or container. The fees were published on the considered ports web site. 
The results in details are presented in the appendix “I”, tables I.1 - I.2 - I.3 - I.4. 
9.9 Comments 
According to Cullinane and Song (2002), Botha and Ittman (2008), seaports are the main 
components in determining the competitiveness of nation’s economy, the result is that 
Sweden has the largest gross tonnage (fig. 9.2) and higher throughput level (table 9.4) 
compared to the considered countries. 
de Langen and Pallis (2005) discussed about the port hinterland (e.g. lower prices), and 
regarding the voyage costs, the Port of Gothenburg has competitive advantages over the 
competing ports. It means that PoG has a higher bargaining power compared to the other 
ports versus port users. Also, Zhang (2008) and Talley (2009) specify that a large captive 
hinterland is recognised by frequent services by shipping lines; the general performance of 
the PoG is definitely higher, compared with the competitors. 
The Mohring effect is confirmed (Zhang, 2008; Janson and Shneerson, 1987) by the 
higher frequencies of shipping lines, and the result is, in average terms, the PoG is the 
location receiving more Ro-Ros (per month), more containerships and higher levels of 
TEUs and containers, compared to the other ports. 
Culinane (2011) and Talley (2009) introduce the shipping lines preferences to a specific 
port; the shipping line will prefer call the port of Gothenburg because the depth water is 
higher compared to the other ports, and the handling fees at the Port of Gothenburg are 
lower. The trade lane is an important factor, because the shipping line will prefer call a port 
if located in the ship’s navigation route and the environmental regulation affect this choice. 
From 
Shanghai 
to /
via Suez-Gibraltar via Cape of Good hope via Cape Horn 
Northern Sea Route 
(passing by: 70° 26' 
47"N 171° 39' 57"W
Port of 
Copenhage
n-Malmo
23,7 
days
$3.146.391,43
30,80 
days
$3.886.829,32
37,61 
days 
$4.596.750,38
16,10 
days 
$2.315.805,74
Port of Oslo 
23,16 
days 
$2.766.507,83
30,23 
days 
$3.504.259,14
37,08 
days
$4.218.496,51
15,50 
days
$1.927.232,41
Port of 
Stockholm 
24,43 
days
$3.147.674,32
31,49 
days
$3.883.805,59
38,34 
days
$4.598.039,48
16,80 
days
$2.313.846,40
Port of 
Gothenburg 
23,03 
days
$2.497.196,62
30,09 
days
$3.233.330,13
36,95 
days
$3.948.641,07
15,40 
days
$1.663.341,19
Pag.  111
For example, considering that all four ports are in SECA area, the different type of fuel to 
use in this area (MGO) is more expensive compared to the open sea fuel (IFO 0380), this 
represent another positive element for the PoG and its location, because shipping lines will 
travel less nautical miles in the SECA area, meaning lower fuel costs.
The authors Notteboom and Winkelmans (2001), Fleming and Baird (1999), Goss (1990), 
Verhoeff (1981), in order to compare the port performances, and interport competition, 
confirm that the four ports compete because located in the port range or coastlines; the 
competition is not only among ports but also to the total logistics chain; particularly the 
voyage cost showed PoG as the less expensive port where to navigate and discharge the 
containership with 18,000TEUs; the hinterland is characterised by several operators 
(intermodal transport) and infrastructure able to satisfy the entire logistics chain. 
The shipping lines prefer to discharge larger volume to fewer ports (Talley, 2009), in order 
to negotiate on volumes, and PoG has the largest TEUs volume compared to the other 
ports. 
Talley (2009) introduces the strategic position analysis (SPA); one component is the 
product portfolio analysis (PPA). Part of our analysis, in line with the author (ibid.), confirm 
that the PoG has the largest market share compared to the other ports, in terms of 
containers, TEUs, containerships traffic categories (RO-RO) in table 9.5 - 9.16 and figure 
9.5. 
Tongzon (2007) when discussing about the country competitiveness, some key 
parameters were identified. According to the author (ibid.) Sweden, and PoG perform 
better compared to the other countries; such as port water depth, shipper preferences and 
port operations efficiency (Wilson et al, 2003). 
Fleming and Baird (1999) confirm that the collaboration between the port and government 
is a competitive advantage. The presented ports collaborate with government and special 
investments are planned. The PoG, recentely invested in many infrastructures (new 
warehouses, terminal expansion, etc.), freezing the containerships fees and adopting 
lower fees to the green containerships (confirmed by Bryan et al, 2006).
Cheng (2001), Song and Panayides (2012) pointed out that modern ports need efficient 
infrastructure, to accomplish better logistics operations, because all players are part of the 
global transport system. The PoG offers more efficient infrastructures compared to the 
other ports.
Pag.  112
10. ANALYSIS - POPULATION - E-BUYERS
In this section are presented the buyer characteristics by country and major cities. 
Companies when investing in a new country take into consideration several factors such 
as the population size (as a potential market), economic growth, income, labor force and 
internet access for the e-buyers. 
Image 10.1 Study process - E-buyers Analysis 
10.1 Country’s Economy and Population Overview 
In order to show the country economic performance several macro data have been 
collected. Table 10.1 show the characteristics of each single country, according to its own 
GDP (gross domestic product). The appendix “L” shows extra figures about this chapter. 
Sweden is first ranked among the nordic countries for GDP growth in 2014 (both in USD 
and Euro) with 571.1 billion USD, followed by Norway (499.81 billion USD), Denmark 
(342.4 billion USD) and Finland (272.2 billionUSD). 
Pag.  113
Table 10.1 Country Economic Overview
The annual growth is higher in Sweden, with 2.4 per cent, followed by Norway (2.2 per 
cent), Denmark (1.1 per cent) and Finland with a negative growth (-0.4 per cent). The 
growth among the nordic countries between 2004 and 2014, was higher in Sweden with 
1.7 per cent, Norway (1.4 per cent), Finland (0.7 per cent), followed by Denmark that 
performed the lowest growth in the Nordic countries with 0.4 per cent. 
In 2015 the registered GDP per capita was higher in Norway with 97,226 US dollars, 
followed by Denmark with 61,294 US dollars, in third position Sweden with 58,856 US 
dollars and last is Finland with 49,678 US dollars. 
In terms of global ranking, Sweden perform better comparing to the rest of the three 
countries (no. 23), followed by Norway (no. 28), Denmark (no. 36) and Finland (no. 44). 
(Eurostat, 2015)
Table 10.2 Population characteristics, highlights the residents in the specific country. 
Sweden rank no. 1 for population (ca. 9 million), number of e-buyers (9 million ca.), labor 
force (5 million ca.) and employed people (ca. 4.8 million). 
Denmark is the second largest market in Scandinavia in terms of population, e-buyers and 
number of employed people. 
Unemployment rate is lower in Norway with 3.60 per cent, Denmark (4.93 per cent) and 
Sweden (7.50 per cent),  and the highest unemployment rate is in Finland (9.38 per cent). 
Norway is the country with the youngest population (39.1 years old) (in average) followed 
by Sweden (41.2) and Denmark (41.8) and Finland (42.4). All the four countries have a life 
expectancy higher than 80 years old, where the first position in rank is Sweden with 82 
years, showing the country’s quality life. The life expectancy can be read, from the retailer 
Country Overview Denmark Finland Norway Sweden 
GDP 2014 (billion USD) (4) 346.12 272.22 500.52 571.09
GDP Growth Annual 2014 (1) 1.1 -0.4 2.2 2.4
GDP Growth 2004-2014 (2) 0.4 0.7 1.4 1.7
GDP/capita USD 2015 (1) 61,294 49,678 97,226 58,856
GNI per capita, PPP (current 
international $USD) (3) 46,850 40,630 67,100 46,870
GDP 2015 world rank (2) 36 44 28 23
GDP 2014 (billion EUR) (2) 257 204 377 429
GDP per capita 2015 (EUR) - (2) 45,600 37,400 73,400 44,300
Note
 this table identify thousands with the “,” “comma”, and decimals with “dot “.” 
1) Eurostat 
2) International Monetary Found (IMF) 2016 
3) Worldbank 
Pag.  114
point of view, as a future products' market expansion because the population will have 
different needs.
Table 10.2 Population Characteristics
Regarding internet, as relevant part of e-retailers, is necessary to highlight the number of 
internet users in a specific country. According to Eurostat (2015), internet users for 100 
people are higher in Norway (96.3 per cent), Denmark is second with 96 per cent, and 
Sweden and Finland (92.5 and 92.4 respectively) third and fourth position with customer 
ages between 16-74 years old. 
Eurostat (2014) takes into analysis the mobile subscriptions; Finland rank no. 1 for this 
category, with 139.7 per cent, showing that all users have multiple devices and possibilities 
to access to internet. Sweden is ranked second, with 127.8 per cent, followed by Finland 
(126.9 per cent) and last is Norway (116.1 per cent). In detail this category highlight the 
willingness to invest in multiple internet devices for the same user.
The category population density is higher in Denmark (smaller country) where 132.9 
people live per square kilometre, with a surface of  43,090 sq. km, followed by Sweden 
with 23.8 people per sq. km with a total surface of 447,420 sq. km., Finland has an 
Category Denmark Finland Norway Sweden 
Population (1) 5,638,530 5,461,512 5,136,886 9,696,110
e-Buyers (2) 5,479,054 5,107,402 5,167,573 9,169,705
Labor Force (2015) (3) 2,905.88 2,688.93 2,760.05 5,226.04
Employment (2015) (3) 2,714.13 2,436.84 2,639.10 4,772.50
Unemployment rate (2015) (3) 4.93 9.38 3.60 7.50
Average age 2015 (4) 41.8 42.4 39.1 41.2
Life expectancy (2014) (1) 80.5 81.1 81.8 82
Internet users (per 100 people) 2015 (1) 
(range 16-74 for Finland and Sweden) 96 92.4 96.3 92.5
Mobile cellular subscriptions (per 100 
people) 2014  (1) 126.9 139.7 116.1 127.8
Population density (people per sq. km 
of land area)  (1) 132.9 18 14.1 23.8
Surface (sq. km) (1) 43,090 338,420 385,178 447,420
CO2 emissions (1) (metric tons per 
capita) 2011 7.2 10.2 9.2 5.5
Note: this table identify thousands with the “,” “comma”, and decimals with 
“dot “.”
1) Eurostat 2015
2) International Monetary Found (IMF) 2016 
3) Worldbank 
4) UNCTAD
Pag.  115
average of 18 people per sq. km. with a total surface of 338,420 sq. km, Norway has the 
lowest population density among the nordic countries with 14.1 people per sq. km. 
The category CO2 emission highlighted by Eurostat (2011, last data available) shows the 
willingness of the local population in eco-friendly practices such as the use of public 
transport; Sweden rank first for the lowest CO2 emissions (5.5 metric tons per capita) 
among the Nordic countries. 
Eurostat 2016 identified the four countries Denmark, Finland, Norway, and Sweden, by the 
major cities (Image 10.2). 
Retailers and Online retailers when considering an investment in a new location, take into 
account the number of potential users (population) in a specific area (city). 
Image 10.2 shows the population density by major urban centres such as Olso, 
Gothenburg, Malmo, Copenhagen, and Helsinki. 
Image 10.2 Population Concentration by Country 
In the next paragraphs (10.2 - 10.3 - 10.4 - 10.5) the four countries and the major urban 
centres are analysed in details. 
Pag.  116
Source: image with population bubbles provided by EU statistics, and adapted by the author
10.2 Denmark
According to Eurostat 2015, the major cities (urban centres) in Denmark are Copenhagen, 
Arhus, Alborg and Odense (table 10.3). 
Copenhagen, the Danish capital, counts 559,440 residents, followed by Arhus (319,09 
ab.), in third position Alborg with 203,448 residents and last is Odense with 193,370 
people. Arhus and Alborg have the lowest unemployment rate, 3.90 and 4.80 per cent 
respectively. In opposite the Danish capital unemployment rate is 5.90 per cent, and 
Odense rank first for the unemployment rate in 2014 (6 per cent).
Table 10.3 Population in Denmark
10.3 Finland 
Comparing to Denmark, Finland has a different situation. The Finnish population is mostly 
concentrated around Helsinki, in Vanta, Espo, Tampere and Turku. The rest of the cities 
Oulu, Lahti, Kuopio and Jvaskyla are located in a more remote areas. 
Considering the closest cities around Helsinki as Vanta - Espo - Tampere and Turku, the 
population resident reach 872,179 people, reaching ca. 1.48 million with Helsinki. In 
opposite the remote areas such as Oulu, Jvaskyla, Lahti and Kuopio count in total for 
479,374 habitants. Table 10.4 shows the detail of the habitants in different cities. 
Table 10.4 Population in Finland
City 
Copenhagen Arhus Alborg Odense
Population 2015 (1) 559.440 319.094 203.448 193.370
Unemployment rate 
(2014) (1) 5,90% 3,90% 4,80% 6,00%
Note: this table identify thousands with the “.” “dot”, and 
decimals with “comma “,”
1) Eurostat 
City
Helsinki Vanta Espo Tampere Turku Oulu Jvaskyla Lahti Kuopio
Population 
2015 (1) 612.664 208.908 260.753 220.446 182.072 143.909 134.658 103.364 97.443
Unemploy
ment rate 
(2014) (1)
7,5% 8,2% 5,5% 12,6% 12,5% 12,7% 12,9% 13,7% 12,5%
Note
this table identify thousands with the “.” “dot”, and decimals with “comma “,”
1) Eurostat
Pag.  117
The highest unemployment rate is in Lahti (13.7 per cent) (ca. 100 km North-east from 
Helsinki), followed by Jvaskyla (12.9 per cent) (ca. 270 km North from Helsinki). In third 
position Oulu with 12.7 per cent unemployed people, followed by Turku and Kuopio both 
with 12.5 per cent unemployed rate. 
Different situation is for Helsinki’s suburbs area, Vanta (8.2 per cent) and Espo with 5.5 per 
cent who repent the lowest unemployment rate in Finland. Helsinki, the Finnish capital, 
maintain an unemployment rate equal to 7.5 per cent. 
10.4 Norway 
Norway, comparing with the previous two countries - Denmark and Finland, the higher 
number of habitants is concentrated in four major urban centres: Oslo (the capital), 
Bergen, Trondheim, and Stavanger. (Eurostat, 2015) 
In order to better understand the geographical disposal of Norway, the table 10.2 (previous 
pages) shows the different country’s surface among the four countries (DK-FI-NO-SE). 
Norway is the second largest Nordic country, followed by Finland and Denmark.
 
As mentioned earlier, the major city is Oslo, with 623,996 ab. and 3 per cent of 
unemployment rate (table 10.5). 
Bergen, the second largest city, is located in the extreme west part of Norway; it counts for 
ca. 267,950 ab. with the second lowest unemployment rate (1.9 per cent), and with a 
distance of ca. 300miles (ca. 500km) from the capital. 
Trondheim, third most populated city, is located in the north of Norway; it counts ca. 
179,692 ab., unemployment rate equal to 2.4 per cent, and with a distance of ca. 305 
miles (ca. 495km) from Oslo. Stavanger, furthest urban centre, is located in the South-
West part of Norway; it counts ca. 179,692 ab., unemployment rate equal to 1.8 per cent 
(the lowest in Norway), and the distance from the capital is 343miles (ca. 553km). 
Table 10.5 Population in Norway
City
Oslo Bergen Trondheim Stavanger 
Population 2015 (1) 623.966 267.950 179.692 129.191
Unemployment rate 
(2014) (1) 3% 1,9% 2,4% 1,8%
Note
this table identify thousands with the “.” “dot”, and 
decimals with “comma “,”
1) Eurostat
Pag.  118
10.5 Sweden 
Sweden, Scandinavian largest country, with 447,420 sq. km and with a population of 9.6 
million. Eurostat (2015) classified major cities (table 9.6) and one extra was added for the 
purpose of this research - Luleå (suggested by the PoG). The total population living in the 
major urban centres is ca. 3.1 million habitants. 
The major cities in Sweden are Stockholm (the capital) who counts ca. 864,324 ab. with 
the unemployment rate of 6.5 per cent; the second urban centre is Gothenburg with 
520,374 ab. (9.3 per cent unemployment rate); the last largest urban centre is Malmo with 
302,835 ab. with the 14.3 per cent of unemployment rate. 
The rest of the cities, from Uppsala to Boras, have a range of habitants between 200,000 
(Uppsala) and 100,000 (Boras); the unemployment rate wasn’t available for all cities (table 
10.6). The smallest urban centre is Lulea, with ca. 76 thousands habitats. Table 10.6 
presents the details of the Swedish population. 
Table 10.6 Population in Sweden
Pag.  119
Cities Population 2015 (1) 
Unemployment 
rate (2014) (1)
Stokholm 864.324 6,5%
Gothenburg 520.374 9,3%
Malmo (2012) 302.835 14,3%
Uppsala 200.001 6,1%
Linkoping 147.334 8,8%
Orebro 137.121 10,1%
Vasteras (2012) 134.684 NA
Jonkoping 128.305 6,2%
Norrkoping (2012) 128.060 NA
Helinborg (2012) 126.754 NA
Umea 116.465 8%
Lund 107.351 NA
Boras (2012) 101.487 NA
Luleå 75.966 NA
Note
this table identify thousands with the “.” “dot”, and 
decimals with “comma “,”
1) Eurostat 2015
10.6 E-buyers Characteristics and Retailing
In order to introduce the Scandinavian population characteristics, several charts present 
the four countries. 
Figure 10.1 shows the number of internet subscribers, internet users, mobile internet and 
mobile telephone subscriptions, by country. It is pretty clear that Sweden has the higher 
percentage of users and subscriptions (larger population). 
Sweden has ca. 14.4 millions of internet subscribers, 8.5 millions of internet users, 11.2 
millions of mobile internet subscriptions and ca. 12.8 millions of mobile telephone 
subscriptions (see appendix “L.1”, table L.1 for details). 
A relevant element to consider when investing in a new country (e-retailers point of view) is 
the presence of the number of devices hold by the population. Figure 10.2 shows the four 
countries personal computers, tablets, and smartphones (in percentage terms).  
94 per cent of the Swedish population has a personal computer, 35.5 per cent has a tablet, 
and 74.9 per cent has a smartphone. By contrast, 50 per cent of the Danish population 
own a tablet (see appendix “L.1”, table L.1  for details). Overall the four countries show a 
high level of devices. 
E-retailers are interested in the economical performances of the country, several 
economical indicators and the different social classes, in order to  have an idea about the 
products and services the customer are interested. Figure 10.3 shows the social classes 
by country. Euromonitor (2015) classified the population in five classes (A-B-C-D-E) (see 
appendix “L”, table L.2). 
Pag.  120
Figure 10.1 Internet & Devices Users
M
ill
io
n 
U
se
rs
 
0
1.600
3.200
4.800
6.400
8.000
9.600
11.200
12.800
14.400
16.000
Source: Euromonitor, 2015
Denmark Finland Norway Sweden 
Internet subscribers 
Internet users
Mobile internet subscriptions
Mobile telephone subscriptions
Social Class A refers to the number of individuals with a gross income over 200 per cent of 
an average gross income of all individuals aged 15+. Social Class B with a gross income 
between 150 and 200 per cent of an average gross income of all individuals aged 15+. 
Social Class C with a gross income between 100 and 150 per cent of an average gross 
income of all individuals aged 15+. Social Class D with a gross income between 50 and 
100 per cent of an average gross income of all individuals aged 15+. Social Class E with a 
gross income less than 50 per cent of an average gross income of all individuals aged 
15+.
Pag.  121
Figure 10.2 Devices by Country
%
 b
as
ed
 o
n 
P
op
ul
at
io
n
0
25
50
75
100
Source: Euromonitor 2015
Denmark Finland Norway Sweden 
Personal computers Tablets Smartphones
Figure 10.3 Social Classes by Country 
Denmark 
Finland 
Norway 
Sweden 
Population (‘000) (Source: Euromonitor, 2015)
0 600 1.200 1.800 2.400 3.0003.600 4.200 4.800 5.4006.000 6.600 7.2007.800 8.400 9.000
Social Class A
Social Class B
Social Class C
Social Class D
Social Class E
Three countries out of four have almost the same level of people belonging to social class 
A, by contrast Sweden has almost 600,000 people in that range. 
Denmark, Finland and Norway have almost the same level (ca. 400,000 people), with 
slight differences, for the segment B. Sweden has ca. 800,000 people in the same class.  
The relevant segments are C and D where Sweden count 1.9 million and 3.2 million 
respectively. Denmark, Finland and Norway have similar levels (ca. 900,000 (C) and ca. 
1.6 million (D)).  
The segment E is described  has the following results: Denmark 1.4 million habitants, 
Finland 1.18 million, Norway 1.1 million, and  Sweden has 1.76 million habitants.
In order to clarify the population in the four countries, figure 10.4 classify the population by 
age and people living in urban centres. 
The segment, 0 to 14 years, Denmark-Finland-Noway have almost the same level 
(900,000 people), instead Sweden counts 1.8 million people. 
The segment, 15-64 is almost constant among the first three countries (Denmark, Finland 
and Norway) equal to 3.6 million people (by country). By contrast Sweden reach 6.3 million 
people. 
The Population over 65 years old (in yellow) is almost the same in Denmark and Finland 
(1.16 and 1.24 million respectively). Norway counts 900 thousands and Sweden counts 
2.07 million people. 
The last chart in this section is the offline retailing and internet retailing market. Figure 10.5 
highlights the four countries, comparing them with the data of 2015 and the forecast of 
2020 (Euromonitor, 2015). Data are available in the appendix “L” table “L.3”. 
Pag.  122
Figure 10.4 Population by Segment
P
op
ul
at
io
n 
(0
00
)
0
900
1.800
2.700
3.600
4.500
5.400
6.300
7.200
8.100
9.000
Source: Euromonitor, 2015
Denmark Finland Norway Sweden 
Population aged 0-14
Population Aged 15-64
Population aged 65+
Urban popualtion 
The growth is registered for the four countries (2020) and particular emphasis is on 
Norway and Sweden (retailing). Instead, internet retailing in forecast to growth in the four 
countries as well. From the author perspective, the difference (in USmillion) between 
retailing and internet retailing must be seen as a big opportunity for the first mover big 
player entering in the  Scandinavian market, in order to get competitive advantages 
compared to other e-retailers. 
In the appendix “L”, table L.4 are are provided some sales data (apparel and footwear; 
beauty and personal care; consumer electronics) and Sweden has a better performance 
compared to the other countries. 
Pag.  123
Figure 10.5 Retailing and Internet
Retailing (2015)
Retailing forecast (2020)
Internet Retailing (2015) 
Internet Retailing (forecast 2020)
$USmn, constant prices, fixed exchange rate (Source: Euromonitor)
0 8.000 16.000 24.000 32.000 40.000 48.000 56.000 64.000 72.000 80.000
Denmark 
Finland 
Norway 
Sweden 
10.7 Comments 
According to Croucher, Baker and Ruston (2014) the home delivery (e-fulfillment) level in 
the selected countries will continue to grow in the next years (fig. 10.5), with Sweden as a 
driver. 
Fernie and Sparks (2014) state that several demographic variables are necessary to 
identify the e-buyers, and the figures introduced in tables 10.1 - 10.2, show the better 
performance of Sweden. Doherty and Ellis-Chadwick (2010) confirm that internet shoppers 
are wealthier, and the previous data show the higher income level in Sweden and Norway 
(table 10.1); by contrast figure 10.3 shows the higher level of income in Sweden, with 
different social classes. 
Bigne et al (2005), state that internet shoppers prefer buying on mobile devices and 
Denmark and Sweden are the countries with the higher level of mobile devices 
(smartphone and tablets). By contrast figure 10.1 shows Sweden with higher level of 
mobile internet subscription (11.2 millions people). 
IGD (2011) refers to the segment age 65+ (figure 10.4) as not potential buyers for online 
groceries. By contrast, the other segment 15-64 years are more willing to buy products 
online. Sweden represents the major market compared with Denmark, Finland and 
Norway.  
Pag.  124
11. ANALYSIS - WAREHOUSE LOCATION 
The following section analyse the warehouse location. The centre of Gravity (COG) has 
been considered under several perspectives. In order to perform a warehouse analysis is 
relevant taking into consideration the maximum number of potential customers reachable 
from one of the four locations (Port of Copenhagen-Malmo, Port of Oslo, Port of Stockholm 
and Port of Gothenburg). Furthermore the analysis consider different transport modes by 
road, rail and sea.  
Image 11.1 Study Process - Warehousing
11.1 Scandinavian Centre of Gravity 
According to the literature introduced previously (Watson et al, 2013), in order to identify 
the best location for a warehouse, is necessary to identify the centre of gravity (COG). For 
our purposes, several destinations (cities) have been identified across Denmark, Finland, 
Norway, and Sweden. The cities are the same mentioned in the population section (Image 
10.2, and table 11.1). 
The centre of gravity (COG) identified takes into consideration the longitude and latitude 
(of the city) and (weighted by) the local population. 
Applying the formulas F3.2 and F3.3, the new latitude and longitude are identified. COG 1 
has coordinates Latitude 59.1 and Longitude 16.2 see (Image 11.2).  
The total population identified is 7.531.429 potential customers (for the considered cities).
Pag.  125
Table 11.1 Cities Coordinates, Population, and COG
Using the same formulas F3.2 and F3.3, a second centre of gravity (COG 2) is identified. 
In this particular case a dummy variable (= 1) was considered. COG 2 is the centre of 
gravity, considering the four ports (longitude and latitude distances). The new coordinates 
are the followings: latitude 58.2 and longitude 13.3 (Image 11.2)
City Latitude (1) Longitude (2) Population (3) 
Copenahgen 55,676097 12,568337 559.440
Arhus 56,162939 10,203921 319.094
Alborg 57,04882 9,921747 203.448
Odense 55,403756 10,40237 193.370
Helsinki  60,169856 24,938379 612.664
Vanta  60,293352 25,037769 208.908
Espo 60,205491 24,6559 260.753
Tampere  61,497752 23,760954 220.446
Turku  60,451813 22,26663 182.072
Oulu 65,012089 25,465077 143.909
Jvaskyla 62,242603 25,747257 134.658
Lathi 60,982675 25,66121 103.364
Kuopio 62,89797 27,678172 97.443
Oslo  59,913869 10,752245 623.966
Bergen  60,391263 5,322054 267.950
Trondheim 63,430515 10,395053 179.692
Stavanger  58,96998 5,733107 129.191
Stockholm Port 59,329323 18,068581 864.324
Gothenburg 57,70887 11,97456 520.374
Malmo (2012) 55,604981 13,003822 302.835
Uppsala  59,858564 17,638927 200.001
Linkoping 58,410807 15,621373 147.334
Orebro 59,275263 15,213411 137.121
Vasteras (2012) 59,6099 16,544809 134.684
Jonkoping 57,782614 14,161788 128.305
Norrkoping (2012) 58,587745 16,192421 128.060
Helinborg (2012) 56,046467 12,694512 126.754
Umea 63,825847 20,263035 116.465
Lund 55,70466 13,191007 107.351
Boras (2012) 57,721035 12,939819 101.487
Luleå 65,584819 22,156703 75.966
Centre of Gravity 
(COG) 59,1 16,2 7.531.429
Note
Note: in the column (1) and (2) decimals are after the “comma” “,” . In the column (3) thousands are 
after the “dot” “.” Column Latitude, a negative sign (-) is used in the excel sheet formula.
Pag.  126
Image 11.2 Centres of Gravity in Scandinavia
Image 11.2 identifies geographically Stockholm, Oslo, Gothenburg and Copenhagen-
Malmo. 
The first centre of gravity (COG 1) (latitude 59.1 and longitude 16.2), weighted by the 
population (from Denmark, Finland, Norway and Sweden) (table 11.1). It is located in 
Sweden, route 56, 15 km north from Katrineholm. It is located 130 miles (209km) from 
Stockholm, 307 miles (494km) from Gothenburg, 344 miles (553km) from Copenhagen, 
327 miles (526km) from Malmo, and 380 miles (611km) from Oslo.  
A second COG (COG 2) was identified (latitude 58.2 and longitude 13.3), comparing only 
the four ports geographical location. The new COG 2 is located in north-east from 
Gothenburg, starting from Highway E20, and when in Vara the route 47 direction Falkoping 
(for ca. 20km). 
COG 2 is located 106 miles (170km) from Gothenburg, 179 miles (288km) from 
Copenhagen, 212 miles (341km) from Oslo, and 337 miles (542km) from Stockholm 
(euclidean distances). A second centre of gravity (COG 2) was considered, in case the 
investors (online retailers) need to make a decision among the considered ports. It shows 
the closest port is PoG. 
Pag.  127
Source: Google maps; and author adaptation
11.2 Centre of Gravity and City’s Distance 
The centre of gravity identified in the coordinate (latitude 59,1; longitude 16,2) is the 
geographical position that better satisfy all customers (Watson et al, 2013). But, the 
centre of gravity calculated by the longitude and latitude considered the euclidean distance 
weighted by the population. 
In order to identify the best location for a warehouse, is necessary to proceed with other 
considerations. For instance retailers consider important to satisfy the higher number of 
customers within 500miles (804,6km). 
The first step is to calculate the distance, in miles, from each port to the selected cities 
(table 11.2) (using the formula F3.1). 
Pag.  128
Table 11.2 Euclidean Distances from Ports and COG to Cities
Country/City
Port of 
Copenhagen-
Malmo 
Port of Oslo Port of Stockholm
Port of 
Gothenburg
Centre of 
Gravity 1
Denmark 
Copenahgen 5 318 455 147 344
Arhus 171 260 584 155 461
Alborg 209 205 583 140 456
Odense 155 311 593 186 474
Finland 
Helsinki  903 980 479 919 607
Vanta  913 987 487 928 615
Espo 886 961 460 901 588
Tampere  866 906 421 863 547
Turku  741 797 301 744 429
Oulu 1.094 1.076 644 1.067 758
Jvaskyla 1.011 1.048 568 1.009 694
Lathi 970 1.033 537 980 666
Kuopio 1.151 1.187 708 1.150 834
Norway 
Oslo  318 2 505 172 380
Bergen  599 375 881 488 756
Trondheim 555 245 599 409 500
Stavanger  527 351 850 431 722
Sweden
Stockholm city 451 508 1 444 130
Gothenburg 146 174 434 9 307
Malmo (2012) 26 335 433 164 327
Uppsala  449 476 46 427 112
Linkoping 278 353 179 265 62
Orebro 304 312 196 257 69
Vasteras 382 401 106 350 42
Jonkoping 178 278 289 160 167
Norrkoping 316 387 138 306 35
Helinborg 24 298 434 127 321
Umea 769 711 346 719 430
Lund 38 335 418 165 313
Boras 141 214 370 75 244
Luleå 947 880 516 896 608
Total miles 15.523 16.704 13.561 15.053 12.998
Note conversion in miles to km: 100 miles = 160,93km ; 200 miles = 321,86km ; 300 miles = 482,80km 
; 400 miles = 643,73km ; 500 miles = 804,67km
Pag.  129
We proceed to the identification of the port that satisfy the higher percentage of customers 
within a certain range of miles and in particular 500miles (table 11.3).
Table 11.3 Percentage of Customers Covered by Destination
Table 11.3 identifies the higher number of customers within a certain range of miles. 
The Port of Copenhagen-Malmo (base Copenhagen port latitude and Longitude) satisfy 15 
per cent of the population within 100 miles. The Port of Gothenburg satisfies 42 per cent of 
the population within 200 miles and 46 per cent within 300 miles. 
The Port of Oslo satisfies 55 per cent of the population within 400 miles. 
Finally, the Port of Gothenburg satisfies 71 per cent of the total population within 500miles. 
This analysis considered the euclidean distance. 
The result of this first investigation is that the centre of gravity identified, by euclidean 
distance, doesn’t satisfy the higher number of customers, in all categories. 
In order to know exactly the total number of potential customers within a certain range (of 
miles), the next table shows the population reachable from the ports (table 11.4), taking 
into consideration the euclidean distance.
The Port of Copenhagen-Malmo satisfies ca. 1 million of potential customers; the PoG 
reach 2.5 millions people from 101 to 200 miles; the Port of Oslo is able to reach ca. 1 
million people from 201 to 300 miles; the COG 1 reach 2.2 millions people from 301 to 400 
miles; and the Port of Stockholm reach 2.9 million people from 401 to 500 miles. Finally 
the PoG is able to satisfy 5.37 million customers within 500 miles. 
Miles Port of Copenhagen-
Malmo 
Port of Oslo Port of Stockholm
Port of 
Gothenburg
Centre of 
Gravity 1
% within 100 miles 15% 8% 14% 8% 7%
% within 200 miles 31% 15% 21% 42% 23%
% within 300 miles 36% 29% 23% 46% 24%
% within 400 miles 50% 55% 28% 50% 54%
% within 500 miles 64% 60% 67% 71% 70%
Note
conversion in miles to km: 100 miles = 160,93km ; 200 miles = 321,86km ; 300 miles = 482,80km ; 400 
miles = 643,73km ; 500 miles = 804,67km 
Pag.  130
Table 11.4 Population Within Specified Range (Euclidean Distance)
A relevant factor for retailers is the maximisation of the number of clients within a certain 
range. The next table (11.5) shows the number of clients reachable by different ports and 
COG (by euclidean distance). Table 11.5 summarised the figures from the previous table 
(11.4) and merged by miles range. 
Table 11.5 Maximum Number of Customers in a Specified Range (Euclidean Distance)
Table 11.5 identifies the Port of Copenhagen-Malmo as the location able to reach ca. 1.1 
million customers (range from 0 to 100 miles). The Port of Gothenburg, appear to be the 
location able to reach 3.18 million people within the range from 0 to 200 miles; and 3.47 
millions people within the range from 0 to 300 miles.
The Port of Oslo is the location within 400 miles, that can cover 4.17 million potential 
consumers. 
And finally, the Port of Gothenburg seems to be the location that better satisfy 5.37 million 
people within 500 miles (confirmed by table 11.4). 
The point of Gravity doesn’t cover the maximum number of customers as the other cities 
(highlighted in yellow). 
Miles 
Port of 
Copenhagen-
Malmo 
Port of Oslo Port of Stockholm
Port of 
Gothenburg
Centre of 
Gravity 1
from 0 to 100 miles 1.096.380 623.966 1.064.325 621.861 547.199
from 101 to 200 
miles 1.262.630 520.374 547.199 2.564.563 1.192.630
from 201 to 300 
miles 147.543 1.058.780 128.305 284.455 101.487
from 301 to 400 
miles 1.023.831 1.972.652 400.024 262.744 2.240.720
from 401 to 500 
miles 200.452 334.685 2.919.525 1.641.158 1.194.141
Total customer 
penetration 3.730.836 4.510.457 5.059.378 5.374.781 5.276.177
Note
Note 1:  this table identify thousands with the “.” “dot”.
Note 2: conversion in miles to km: 100 miles = 160,93km ; 200 miles = 321,86km ; 300 miles = 
482,80km ; 400 miles = 643,73km ; 500 miles = 804,67km
Miles range Port of Copenhagen-
Malmo 
Port of Oslo Port of Stockholm
Port of 
Gothenburg
Centre of 
Gravity 1
from 0 to 100 miles 1.096.380 623.966 1.064.325 621.861 547.199
from 0 to 200 miles 2.359.010 1.144.340 1.611.524 3.186.424 1.739.829
from 0 to 300 miles 2.506.553 2.203.120 1.739.829 3.470.879 1.841.316
from 0 to 400 miles 3.530.384 4.175.772 2.139.853 3.733.623 4.082.036
from 0 to 500 miles 3.730.836 4.510.457 5.059.378 5.374.781 5.276.177
Notes
this table identify thousands with the “.” “dot”.
Note: conversion in miles to km: 100 miles = 160,93km ; 200 miles = 321,86km ; 300 miles = 482,80km ; 
400 miles = 643,73km ; 500 miles = 804,67km
Pag.  131
Other considerations are presented in the next paragraphs.
12.3 Time range
After the miles/km distance calculation identified in the previous paragraph, a second 
consideration is necessary. Ballou (1999) and Mulchay (1994) suggest to identify the 
delivery time for a quicker response and closer proximity to consumers. 
Retailers are interested in time reduction, shorter lead time, in order to satisfy customer’s 
demand (e.g. deliver products within 24 hours). 
Considering the same data in the table 11.1 (latitude and longitude by city), using Google 
Maps®, a road-time calculation is provided in the table 11.7. The departure points 
identified are the Port of Copenhagen-Malmo, the Port of Oslo, the Port of Stockholm, the 
Port of Gothenburg and COG 1. Table 11.6 shows the coordinates latitude and longitude 
for different departure points. 
Table 11.6 Coordinates Ports and COG
Port of 
Copenhagen-
Malmo (1)
Port of Oslo 
(1)
Port of 
Stockholm (1)
Port of 
Gothenburg 
(1)
from Centre of 
Gravity (2)
Latitude 55.7000 59.90000 59.333333 57.683333 59.1
Longitude 12.6333 10.7333 18.0500 11.8500 16.2
Note this table identify decimals with the “.” “dot”.
(1) Source: sea-web.com® ; (2) Our calculation. Results in table 11.1
Pag.  132
Table 11.7 Travel Distances from Ports/COG to Cities
Table 11.7 shows the different time-distances by departure point (e.g. COG 1) and related 
city.  
Summarising the data from the table 11.7, and combining with the population (table 11.1), 
is possible to identify the number of potential customers within a certain time-range (table 
11.8). For example locating a warehouse in the Port of Stockholm, e-retailers are able to 
cover 1,327,069 people within 2 hours driving, and PoG is able to cover 2,230,304 
potential consumers in a time range between 2 and 4 hours. 
Country/City Copenhagen-Malmo Port Port of Oslo
Port of 
Stockholm 
Port of 
Gothenburg 
from Centre of 
Gravity 1
Denmark 
Copenahgen 0h16m 6h25m 6h40m 3h30m 5h47m
Arhus 3h38m 9h10m 9h30m 6h15m 9h45m
Alborg 4h35m 8h20m 10h00m 5h19m 9h15m
Odense 2h17m 7h55m 8h20m 5h04m 7h15m
Finland 
Helsinki  18h23m 17h35m 11h55m 16h44m 13h45m
Vanta  18h30m 17h36m 12h03m 16h47m 13h50m
Espo 18h12m 17h20m 11h40m 16h30m 13h30m
Tampere  18h35m 17h40m 12h00m 16h53m 13h50m
Turku  16h45m 15h55m 10h10m 15h02m 12h00m
Oulu 19h12m 17h05m 12h35m 17h6m 13h45
Jvaskyla 20h10m 19h25m 13h43m 18h30m 15h25m
Lathi 19h15m 18h25m 12h45m 17h37m 14h30m
Kuopio 21h48m 20h55m 15h30m 2h10m 17h04m
Norway 
Oslo  6h18m 0h15m 6h10m 3h18m 5h10m
Bergen  13h33m 7h10m 13h20m 10h27m 12h20m
Trondheim 13h05m 6h35m 9h36m 9h46m 10h15m
Stavanger  13h00m 7h20m 13h10m 9h51m 12h30m
Sweden
Stockholm city 6h50m 6h15m 0h10m 5h02m 2h05m
Gothenburg 3h24m 3h15m 4h50m 0h15m 4h00m
Malmo (2012) 0h51m 5h55m 6h12m 2h59m 5h20m
Uppsala  7h30m 6h00m 1h00m 5h19m 2h10m
Linkoping 4h45 5h40m 2h10m 3h04m 1h25m
Orebro 5h42 4h10m 2h13m 3h29m 1h15m
Vasteras 6h40m 5h00m 1h15m 4h25m 1h25m
Jonkoping 3h35m 4h45m 3h20m 1h56m 2h30m
Norrkoping 5h08m 5h46 1h52m 3h27m 1h00m
Helinborg 1h27m 5h20m 5h35m 2h27m 4h45m
Umea 13h22m 11h00m 6h47m 11h14m 7h55m
Lund 1h00m 5h46 6h05m 2h55m 5h10m
Boras 3h50m 3h50m 4h10m 0h58m 3h20m
Luleå 16h25m 13h55 9h45m 14h17m 11h00m
Note Results from Google Maps®. Car time. 
Pag.  133
Table 11.8 Distances by Time range Single Category
Merging the results from the table 11.7, combined with the population (table 11.1) and 
sorted by port, table 11.8 identifies the total population able to be served by ports and 
COG 1 in a different time ranges. 
Table 11.9 identifies the higher number of potential consumers within a specific time range. 
For instance, taking into consideration the PoG (as a departure point), e-retailers are able 
to deliver products to ca. 3 millions of potential customers within 4 hours driving, and ca. 5 
millions customers within 8 hours driving. By contrast the Port of Oslo is able to reach 5,3 
millions of potential consumers. 
What is relevant in this table is the maximisation of the number of potential consumers in 
the shortest delivery time; overall PoG performs better comparing to the other departure 
points, because within a lower time-range it maximises the number of clients; and as a 
consequence, it reduces the P-time and D-time and contributing to the company’s 
efficiency. 
Table 11.9 Distances by Time Multiple Categories
Time range Copenhagen-Malmo Port Port of Oslo
Port of 
Stockholm 
Port of 
Gothenburg 
from Centre of 
Gravity 1
from 0h to 
2hours 1.096.380 623.966 1.327.069 750.166 547.199
from 2h01m to 
4hours 1.262.630 621.861 412.760 2.230.304 1.814.491
from 4h01m to 
6 hours 615.963 1.412.445 748.615 1.595.827 1.720.346
from 6h01m to 
8 hours 1.822.975 2.193.967 1.710.057 319.094 309.835
from 8h01m to 
10 hours 0 522.542 971.570 308.883 522.542
from 10h01m 
to > 2.733.481 2.156.648 2.361.358 2.327.155 2.617.016
Note  this table identify thousands with the “.” “dot”.
Time range multiple 
categories Copenhagen-Malmo Port Port of Oslo
Port of 
Stockholm 
Port of 
Gothenburg 
from Centre 
of Gravity 
(COG 1)
from 0 to 2 hours 1.096.380 623.966 1.327.069 750.166 547.199
from 0 to 4 hours 2.359.010 1.245.827 1.739.829 2.980.470 2.361.690
from 0 to 6 hours 2.974.973 2.658.272 2.488.444 4.576.297 4.082.036
from 0 to 8 hours 4.797.948 4.852.239 4.198.501 4.895.391 4.391.871
from 0 to 10 hours 4.797.948 5.374.781 5.170.071 5.204.274 4.914.413
from 0 to > 10 hours 7.531.429 7.531.429 7.531.429 7.531.429 7.531.429
Note this table identify thousands with the “.” “dot”.
Pag.  134
11.4 Road-Rail and Emissions calculation 
The potential warehouse location consider the transport network efficiency by truck and 
rail point view. The green house emissions (GHG) are a relevant part for a new 
sustainable warehouse network.
The tool EcotransIT® (Ecological Transport Information Tool for Worldwide Transports) 
that calculates the environmental impacts for any freight transport service, is used. 
EcoTransIT World provides energy consumption and GHG Emissions for trucks, trains, 
ships and airplanes in accordance with the European standard EN 16258:2012 
(ecotransit.org, 2016). For our investigation the truck, rail, and ship are considered as 
transport modes. 
In EcoTransIT the user can select several options from basic to advanced. For our 
purposes the standard option was preferred: 
Input mode: Standard 
Freight: Amount = 1 ; Unit: Container (TEU)
Origin: Coordinates: port or COG latitude/longitude (our table 11.6)
Choose transport mode: truck + train
Destinations: Coordinates: latitude/longitude (our table 11.1)
 Ecotransit® shows the following results: 
Weight: 1 container (TEU)
t/TEU: 10 
Transport Service Truck: 26-40 t, EURO 5 (this is the truck type)
Vehicle type: Class40
Load factor (LF): 95.77%,
Empty run factor (ETF): 20%
Transport Service Train: 
Train Type: container
Train weight: 1000t
Emission class: electrical
Load factor: 49.8%, Empty run factor: 20%,
Ferry routing: Normal
KM: it is not possible to switch in miles. 
The author proceeded with the calculation for different departure points (ports and COG 
latitude and longitude) and the arrival city point (latitude and longitude). The calculation 
doesn’t consider the optimal routing but just the results from point A to point B. Table 11.10 
summarised the results. 
Pag.  135
Table 11.10 Energy consumption from Ports/COG to Cities
Table 11.10 shows the Port of Stockholm as better departure point to satisfy the different 
cities consuming a lower level of kilowatthours (44,636) and GHG emissions CO2e 
(carbon dioxide equivalent) (12.23 tonnes). 
Instead the COG has the lowest total kilometres to satisfy the cities by road. By rail, 
instead, the COG, as a departure point, has the lowest energy consumption in 
kilowathours (17,012) and GHG emissions as CO2e (1,726 tonnes). Instead the Port of 
Gothenburg maintain the best performance in railway network. 
Another consideration to take into account is the transport of the same container (1TEU, 
10t) from each single port to the Centre of Gravity (hypothetical warehouse location). The 
author proceed to calculate the single data and afterwards results have been merged 
(table 11.11). 
Table 11.11 shows the new environmental and network scenario for the considered 
container (1TEU, 10t) from the ports to the COG. 
It appear that the port of Stockholm has better performance (in truck terms) than the other 
ports; and the Port of Gothenburg perform better compared to the others two ports. 
In rail terms, moving the container from the port of Stockholm to COG 1 to the network 
(cities), has a lower environmental impact compared to the other ports. Compared with 
PoG there is a slight difference. By contrast, if the container (1TEU, 10t) is transported 
from the Port of Gothenburg to the COG 1 and afterward to the different cities, there is a 
lower rail GHG emissions levels (CO2e).
Port	of	
Copenhgen	
Port	of	Oslo	
Port	of	
Stockholm	
Port	of	
Gothenburg	
from	COG	1	
to	ci?es	
Truck results 
Energy consumption 
(Detailed) truck  
(kilowatthours) - WTW 
63.013 58.394 44.636 52.615 47.121
GHG emissions as 
CO2e (WTW) - Tonnes 16,47 15,25 12,23 13,77 12,35
Travel by road - KM 20.895,090 17.293,210 13.238,210 15.622,860 12.724,170
Rail results 
Energy consumption 
(Detailed) rail 
(kilowathours) WTW
19.705 19.274 17.327 17.905 17.012
GHG emissions as 
CO2e (WTW) - Tonnes 1,864 1,766 1,744 1,760 1,726
Travel by rail km 30.850,740 25.601,51 25.040,550 23.078,970 25.420,490
Note: this table identify thousands with the “.” “dot”, and decimals with “comma” “,”
Pag.  136
 The total number of km by rail are lower from the Stockholm network. 
Table 11.11 New Scenario with Container Transport from Ports to COG 1 to Cities
In order to perform a “global transport network energy and GHG calculation”, and adding 
extra value to the previous figures, the author decided to investigate the transport 
emissions from China - Shanghai. 
The shipping departure point is Shanghai (latitude 30.626539 and longitude 122.064958) 
to the considered destinations (Class: DryFreight type; via Suez trade (4,7-7k TEU); 
Speed: 25.0% LF:67.0%; (1TEU, 10t); with EcotransIT carbon calculator). Results are 
provided in table 11.12. 
Table 11.12 Emissions and KM from Shanghai to Dedicated Points (ports and COG 1)
Port	of	
Copenhagen-
Malmo
Port	of	Oslo	
Port	of	
Stockholm	
Port	of	
Gothenburg	
Truck results 
Energy consumption 
(Detailed) truck  
(kilowatthours) - WTW 
48.534 48.162 47.522 48.087
GHG emissions as CO2e 
(WTW) - Tonnes 12,71 12,62 12,45 12,60
Travel by road - KM 13.284,98 13.123,78 12.882,06 13.104,86
Rail results 
Energy consumption 
(Detailed) rail 
(kilowathours) WTW
17.216 17.199 17.068 17.138
GHG emissions as CO2e 
(WTW) - Tonnes 1,731560 1,727180 1,727460 1,726910
Travel by rail km 25.965,80 25.875,68 25.569,71 25.768,66
Note: this table identify thousands with the “.” “dot”, and decimals with “comma” “,”
from Shanghai to 
Port	of	
Copenhagen
-Malmo	
Port	of	
Oslo	
Port	of	
Stockholm	
Port	of	
Gothenburg	
COG	1
Sea results 
Energy consumption 
(Detailed)  
(kilowatthours) - WTW 
(total trip)
8.942 10.412 10.542 9.703 10.306
GHG emissions as CO2e 
(WTW) - Tonnes 2,47 2,85 2,88 2,66 2,82
Travel in KM by sea and 
by road (from Hamburg) 20.559,28 21.146,42 21.199,20 20.863,90 21.101,90
Note: this table identify thousands with the “.” “dot”, and decimals with “comma” “,”
Pag.  137
The results from EcotransIT (table 11.12) show the transport from Shanghai to the port of 
Copenhagen-Malmo as the optimal option. However, EcotransIT, when the user select 
longitude and latitude (departure Shanghai and arrival Copenhagen-Malmo Ports), the 
system takes Hamburg (Germany) as discharging port (and it is not possible to modify it), 
and from Hamburg a road transport is provided to the final destination (ports or COG 1). 
Table 11.13 shows merged data from table 11.10 (Energy consumption from Ports/COG to 
Cities) and table 11.12 (Emissions and KM from Shanghai to Dedicated Points (ports and 
COG 1), in order to calculate the most appropriate freight system with the lower level of 
energy consumption, GHG  emissions, and total kilometres (by road or by by rail and 
road).
Table 11.13 Emissions and KM Merged
The results from table 11.13 shows the Port of Stockholm (by sea and truck) as the ideal 
port for the lower level of energy consumption and GHG emissions: arrival (from 
Shanghai) and departure to the different cities. Instead COG 1, is the distribution point 
requiring less kilometres to receive and distribute the container (total 33,826.07 km). 
Instead, considering the following transport modes: Vessel from Shanghai to Hamburg, 
road from Hamburg to dedicated port/COG 1, and from dedicated port/COG 1 to final 
destination (cities); the centre of gravity 1 would generate the lower level of energy 
consumption; with the Port of Copenhagen-Malmo with the lower level of GHG emission; 
from Shanghai to 
dedicated city passion by 
the ports
Port	of	
Copenhagen
-Malmo	
Port	of	
Oslo	
Port	of	
Stockholm	
Port	of	
Gothenburg	
COG
By Sea and Truck 
Energy consumption 
(Detailed)  
(kilowatthours) - WTW 
(total trip)
71.955 68.806 55.178 62.318 57.427
GHG emissions as CO2e 
(WTW) - Tonnes 18,94 18,10 15,11 16,43 15,17
Travel  in KM 41.454,37 38.439,63 34.437,41 36.486,76 33.826,07
By Sea and Rail
Energy consumption 
(Detailed)  
(kilowatthours) - WTW 
(total trip)
36.921 36.473 34.395 35.043 27.318
GHG emissions as CO2e 
(WTW) - Tonnes 4,33 4,62 4,62 4,42 4,55
Travel  in KM (by sea, 
truck (Hamburg) and 
rail )
51.410,02 46.747,93 46.239,75 43.942,87 46.522,39
Note Note: this table identify thousands with the “.” “dot”, and decimals with “comma” “,”
Pag.  138
and the PoG has the lower number of kilometres to distribute the containers (from port to 
cities). 
11.5 Investment Considerations
According to Mulcahy (1994), several parameters have been considered when evaluating 
the most appropriate country.  
Sweden (3rd on global rank) results being the most appropriate choice when considering 
the Networked Readiness Index (NRI) (the performance of 143 economies in leveraging 
information and communication technologies to boost competitiveness and well-being) 
(see definitions), followed by Norway (5th), and Denmark (15th). 
Regarding the corporate tax, Denmark and Sweden maintain the same level equal of 22 
per cent; by contrast Norway has a higher rate (27 per cent). 
The industrial and logistics costs have different prices among the three countries. 
It was mentioned in the previous sections that Oslo is one of the most expensive city 
worldwide for warehouses. 
Considering Denmark, Copenhagen area, official resources weren’t available, and it was 
necessary to investigate third sources. “Colliers”, one of the most reputed real estate 
company worldwide, had two warehouses on sale; the first warehouse is located nearby 
the port are and the second is located in proximity to the international airport.
The first one has a total surface of 1,119sqm2 with the sale cost equal to 152,792.00USD 
(136.54USD, price per square meter). The second warehouse has the total surface equal 
to 1,229sqm2 with the sale cost equal to 176,724.00USD (average cost is 143.79USD per 
square meter) (Collier, 2016). From other sources (PoG) is suggested to identify the rent 
cost dividing the sale price per square metre, and adding 10 per cent margin. The potential 
rental price for the first warehouse (port area) is 150.19USD/sqm2 and the second 
warehouse (airport area) rental cost is 158.17USD/sqm2. 
Official warehouses costs were not available through the Ministry of Foreign Investment 
(Investindk.com ) or other third party agencies.
Swedish warehouses infrastructure cost, in average terms across the country, is 570SEK 
(69USD per square meter per month); the price per square meter is the same for 
Stockholm, Malmo and Gothenburg. 
Certainly one important element to consider is the private negotiation between the parties, 
where are negotiates terms-conditions-benefits.
Pag.  139
Table 11.14 Comparing Three Countries
The utility price, different in Norway, in Denmark and Sweden is one of the factors 
influencing the warehouse location. The example below shows the different electricity 
costs per month. 
It is assumed that the warehouse operates 8 hours a day for 30 days a month, with 
equipment utilized at 80 per cent of capacity on average, and that there are no electricity 
cuts (assumed for simplicity). The subscribed capacity of the warehouse is 140 kVA, with a 
power factor of 1 (1 kVA = 1 kW). The monthly energy consumption is therefore 26,880 
kWh, and the hourly consumption 112 kWh (26,880 kWh/30 days/8 hours).
Denmark Electricity Cost : 26,880 kWh * 14,5 US/cents = 389,760USD/month
Norway Electricity Cost : 26,880 kWh * 12,9 US/cents = 346,752USD/month
Sweden Electricity Cost : 26,880 kWh * 13,3 US/cents = 357,504USD/month
Denmark (2) Norway (3) Sweden (4)
Networked Readiness 
Index’s (NRI) (9) 15 5 3
Corporate tax rate % 22 27 22
Industrial/Logistics cots (10)
(5) Warehouse in Port area (to buy) 
1,119sqm2 = 1,002,000DK = 152,792.00 
USD. Potential rental cost 150.19USD/
sqm2. 
Warehouse in Airport area 1,229sqm2 = 
1,158,954DK = 176,724 USD. Potential 
rental cost 158.17USD/sqm2. 
NA
570SEK/sqm2 = 
69USD average 
Utilities electricity (US cents 
per kWh) 14,5 (6) 12,9 (7) 13,3 (8)
VAT - VALUE ADDED TAX (1) 25 24 25
Reduced VAT no. 2 15 15 12
Reduced VAT no. 3 5 8 6
Labor hours 36 38 40
Note: 
1) USCIB, 2016
2) InvestinDK.com (2016);  considered as main source (if not specified) 
3) Innovasjonnorge.no,  (2016); considered as main source (if not specified) 
4) Business in Sweden (2016); considered as main source (if not specified) 
5) Colliers (2016a) 
6) Doing Business Denmark, (2016a)
7) Doing Business Norway,  (2016b)
8) Doing business Sweden ( (2016c)
9) World Economic Forum (2016)
10) Conversion rate by XE.com on 10 May 2016.
Pag.  140
It results that Norway has the lowest  cost per month (346,752 USD), followed by Sweden 
(357,504USD) and last is Denmark (389,760USD). 
Value Added Tax maintain different levels in the three countries; VAT category 1 refers to 
the electronics or sports equipment; VAT category 2 applies to accommodations, 
entertainment; VAT category 3 applies to basic products as food. 
Labor hours are different in Denmark, Norway and Sweden; in general terms, Sweden has 
the higher number of working hours per week, comparing to the other two countries. 
12.4 Comments 
From the logistics point of view, the warehouse/DC should be seen as part of the global 
supply chain, and not as an independent operation (confirmed by Tompkins and Smith, 
1998). The importance of this consideration is how the products can be delivered from the 
manufacturing country (e.g. Shanghai) and delivered to the Scandinavian consumers in 
amore efficient and effective way.
Lambert and Stock (1993) confirm that the warehouse can be used to receive products 
(containers) from the manufacturing country, and afterwards smaller deliveries can be 
organised to satisfy the needs of many consumers. The authors 
According to Lambert and Stock (1993) the facility location can be considered under the 
macro and micro perspectives. The macro perspective is where PoG belong because 
several geographical areas can be served. From the micro perspective the retailer 
services (sales and delivery) will benefit from this location, offering a quick delivery, and 
able to satisfy a higher percentage of the Scandinavian market (confirmed by Mulcahy, 
1994). 
Panayides and Song (2006) assert that ports can contribute to improve the performance of 
the supply chain as whole. In this case the development of new warehouses in the Port of 
Gothenburg will contribute to a better distribution, compared to the other ports. 
The importance of the warehouse/DC is confirmed by Croucher, Baker and Ruston (2014) 
because necessary to the distribution of several products. The identified warehouse 
location is the Port of Gothenburg because from this location three main markets can be 
served (Norway, Denmark and Sweden) with a shorter delivery time-miles. The location of 
the warehouse at the PoG can be considered as Scandinavian geography (to serve 
multiple geographical - international markets) and the warehouse can be classified for 
finished goods (to be distributed to the potential customers) or even returned goods (after 
purchase). The authors discuss the importance of the product surround; deliver service as 
an important element in determining the final demand for a product. The same author 
confirm that a new distribution system can be established with small deliveries on small 
Pag.  141
vehicles into residential areas. The distribution from the PoG will contribute to those areas 
with frequent deliveries due to the distance and lower time needed to serve dedicate 
consumers.  
In order to increase the sales, a faster delivery is necessary and the positive consequence 
is the improved customer service (Ballou, 1999). Watson et al (2008) confirm that the 
warehouse must be located in proximity of the market where the product is consumed; and 
it is confirmed that the PoG is the preferred location to satisfy different markets (cities). 
The proximity to the market is confirmed by Lambert and Stock (1993; from Edgar 
Hoover). Bonacich and Wilson (2008) agree with the proximity to population centres where 
large proportions of goods can be delivered; confirming PoG as the closest place where to 
satisfy millions or potential consumers. 
For example Mulcahy (1994) states that the site selection project must cover a radius of 
150-200 miles (241-321km), and PoG has the higher number of potential consumers 
within this range; PoG is able to cover 42 per cent of the Scandinavian market within 200 
miles, 3,18 millions people. Savills (2013) and NCFRP (2013) focus on central location 
and proximity to consumers, confirming the results of the PoG. 
The centre of gravity identified (COG 1) as suggested by Mulcahy (1994) and Watson et al 
(2013) shows the lower level of total miles needed to satisfy the selected locations. By 
contrast the centre of gravity doesn’t satisfy at all this statement. The COG 1 cannot take 
advantage of true road distance or even travel restrictions; it is a straight-line based on 
latitude and longitude (Watson et al, 2013). Another reason for not accepting COG 1 is the 
present of the sea between Sweden and Finland. In this case the formulas was weighted 
by the population and not other variables were considered (e.g. lake and sea/ocean). 
The PoG is able to satisfy a larger geographical market (euclidean distance) compared 
with the COG 1. 
In order to compare the different destinations, Mulcahy (1994) suggests to use another 
approach: serve-a-cluster-of-customer-method; where time and distance and considered. 
This method confirmed the PoG as location able to satisfy different locations in shorter 
delivery travel time-miles. This is confirmed by Richards (2014) in shorter lead time 
distribution.
NCFRP (2013) asserts that the location is also chosen by the negotiation process with the 
warehouse’s owner. The average rental cost was identified and online-retailers can base 
part of their negotiation on that data.  
Sustainability is a relevant issue in 2016, and the warehouse of the future should take into 
consideration the environment. According to Richards (2014) the warehouse is part of the 
global supply chain and the alternative forms of transport must be considered. From the 
global perspective (Shanghai - Port/COG 1 - Final consumers), the Port of Stockholm 
Pag.  142
seems being the location where there is a lower level of emissions; by contrast COG 1 is 
the location able to use the lower number of kilometres to deliver the container (to the 
identified cities). PoG has the lower level of kilometres, if the distribution is by rail. 
Noteboom and Winkelmans (2001a), UNESCAP and KMI (2005), Bichou and Gray (2004), 
Verhoeven (2010) specify the importance of the ports as value-added logistics services, 
and central links in the complex supply chain, where intermodal transports is able to satisfy 
multiple consumers. The PoG can be seen as distripark, because the location of new 
warehouses facilities in that area will contribute to redefine the port-supply chain 
integration and centre of trade (Branch, 2007; Woo and Pettit, 2009); Nottemboom and 
Rodrigue, 2005). 
Johnson and Wood (1996) consider the logistics centre as cost reduction infrastructure; 
and in our analysis we assume that the lower distance (kilometres and miles) and travel 
time, from the PoG to consumers, contribute to reduce the retailers costs.
According to Robinson (2002) the competition between individual ports is along the 
logistics chain and the geographical location of the PoG (and warehouses located in the 
port) contribute to perform the distribution in a more efficient and effective way compared 
to the other ports. It is confirmed by Song and Panayides (2012) that ports contribute to 
the supply chain through the creation of value added-delivery and competitive advantage, 
and the distribution system from the PoG has a relevant impact for online retailers. 
Mangan et al (2008) discuss about port-centric logistics services such as warehousing, 
contributing to higher profits margins for the port itself. The new warehouses, located in 
the Port of Gothenburg area will contribute to better distraction operations such as no 
double transportation for containers, enable hauliers to reduce wastage and make the 
most efficient use of trucks and drivers’ hours. Carbon and de Martino (2003) confirm that 
the customer is willing to pay for those services contributing to adds value to the product. 
Worldbank (2001) and Talley (2009) define the non-traditional port services who contribute 
to cost reduction; the PoG with the “new” and future port warehousing service will 
contribute to reduce the cost related to distribution (assumption based on kilometres and 
voyage shipping costs). 
Concluding, the delivery service must meet customer expectations otherwise sales can be 
lost (Harrison, Hoek and Skipworth, 2014); nowadays customers expectations are related 
to the same day or next day delivery, and the PoG warehouse's location can contribute to 
have amore efficient distribution and potential sales will not be lost. 
Pag.  143
12. CONCLUSIONS 
This section provides a summary of the conducted research. 
Considering the research questions mentioned at the beginning of this research: 
1) Assuming that all four ports included in the research provide warehouses to e-
retailers, which location has the most convenient distribution (e.g. short lead time and 
large e-buyer customer base)?
2) How can the Port of Gothenburg (PoG) contribute to the success of online retailers?
3) Which factors create a competitive advantage for e-retailers?
4) Which factors influence the choice of location for a warehouse/DC? 
In order to answer to the research questions a literature investigation was conducted 
under several key topics. The considered topics are the supply chain, maritime, 
warehousing, e-commerce and e-buyers.  Image 12.1 shows the research process. 
Image 12.1 Summary Research
Pag.  144
Source: author elaboration
Once the literature review was identified, a proper methodology was necessary in order to 
have the most appropriate data collection methods, and models applied in the analysis. 
The analysis section investigated the followings: 
1) The international trade in order to identify the trade value of goods in Scandinavia and 
the country with higher levels of Import-Export; it was necessary to understand the 
consumptions, the type of goods consumed, the trade value with the world and the 
Import-Export in Scandinavia.
2) The maritime sector, considered the throughput levels by country, region and port; the 
number of vessels per port and related TEUs/containers, ports characteristics, 
efficiency indicators, and voyages costs simulation to identify potential-preferred port.
3) E-Buyers characteristics such as geo-demographic data, country economic overview, 
social classes, the level of internet penetration in the countries, and retailing 
consumptions
4) Warehouse location, investigated the most appropriate location for a warehouse, 
considering the potential consumers (to satisfy) in the shorter lead time and larger 
radius in miles, warehouses prices, and global distribution simulation (from Shanghai 
to dedicated cities in Scandinavia). 
In the analysis section, several comments related to the literature clarified the results. 
It is possible now to answer to the following research questions: 
1) Assuming that all four ports included in the research provide warehouses to e-
retailers, which location has the most convenient distribution (e.g. short lead 
time and large e-buyer customer base)?
The preferred location who better satisfy the higher number of consumers is Gothenburg. 
The Port of Gothenburg, with the new warehouses, will contribute to a more efficient 
distribution penetrating the higher number of potential consumers with a shorter 
distribution time compared to the ports’ competitors; thanks to Gothenburg’s geographical 
location, 5.37 millions of potential consumers can be reached within 500 miles; it means 
that consumers in Norway, Denmark, and Sweden will incur in positive benefits, as faster 
products delivery. 
2) How can the Port of Gothenburg (PoG) contribute to the success of online 
retailers?
The PoG as a central distribution centre for e-retailers will positive influence the global 
supply chain thanks to the higher level of efficiency.
Containers will be discharge at the port and moved directly to the warehouses located 1.5 
km from the container terminal. This activity will contribute to have a lower delivery time to 
the retailer warehouses and the products will be dispatched quicker and sooner to the 
consumers (port-centric logistics). In this case sales will not be lost. 
Pag.  145
Shipping companies will prefer call PoG for the lower voyage costs, lower containers 
handling fees, higher level of efficiency (indicators) compared to the other ports. PoG 
perform higher calls from containerships and Ro-Ros. It means that shipping companies 
prefer PoG to other ports. 
3) Which factors create a competitive advantage for e-retailers?
Sweden has a larger population, compared to the rest of the three countries. The Country 
economy perform better compared to Denmark, Finland and Norway. 
The international trade in Scandinavia is definitely something to take into consideration 
because Swedish consumers are willing to spend more in retailing products. The higher 
income and Scandinavian economy contribute to be a very attractive market. 
The four ports have different infrastructures, dimensions, throughput, containers and TEUs 
flow; the port with a better performance is definitely Gothenburg. 
In total there are ca. 24.7 million E-buyers in Scandinavia, and 19.6 millions can be 
reached from Gothenburg.
Sweden is the country with higher sales in apparel, footwear, beauty, personal care, and 
consumer electronics. 
Market penetration in 2-4 hours by truck to deliver products to the customer
4) Which factors influence the choice of location for a warehouse/DC?
The warehouse location, that is the most relevant part of this research. One important 
element is the customer satisfaction in the shortest lead time. It means that the more 
convenient location is where the company can dispatch several times, during the day, 
products to major urban centres. 
Infrastructure investment costs such as warehouse’s rent price, utilities prices, negotiable 
salaries, working hours, international trade volume, and income of the potential market to 
be served. 
Considering that the final users of the warehouse/DC are e-retailers, is necessary to 
identify if the level of technology of the population. The four countries have pretty young 
population, in average, and particularly Sweden; the habitants have multiple devices, 
multiple internet and mobile subscriptions.  
Pag.  146
12.1 Future Research 
This research is quite extensive and wasn’t possible to cover all the aspect related to e-
retailers, distributions, maritime, E-commerce and e-buyers. 
Starting from the supply chain, some possible investigations are related to the transport 
costs from the manufacturing country, the transport to the first port, and a more detailed 
voyage cost analysis. 
In warehousing, something relevant to investigate is what type of infrastructure the e-
retailer is interested  in; online retailers might be interested in high technological advanced 
“spiders” to collect goods in few minutes (Amazon DC). The level of technology inside the 
distribution centre affect the delivery time. If e-retailers spend 6 hours or even 10 to collect 
the goods in the warehouse, the product can be collected the day after or even 2 days 
later (depending on 3PL distribution and delivery schedule). It interesting to understand the 
reasons why retailers such as Zalando and others, dispatch their products from other 
countries (e.g. Germany) this process influence the delivery time to the Scandinavian 
users, because are necessary 7-10 days to receive an order in Gothenburg. 
Regarding the maritime sector, particular focus can be on port time efficiency. It would be 
interesting identifying the time necessary to discharge a containerships and related costs 
(e.g. labor, cranes, quay cranes, berthing, and pilotage). Several authors identified some 
performance indicators, but due to the lack of informations and time wasn’t possible to 
investigate them. 
The containers flow, inward and outward, wasn’t considered. Containers when moving 
from the port to the retailers’ warehouse, are in stand-by for a certain time, and the 
retailers incur in extra costs for this stand-by. 
Under the e-commerce analysis, it would be interesting investigate in details the order 
delivery; what happen next an order is received by the retailers? how long does it take to 
process the order? how many people can be involved in a single order? how e-retailers 
negotiate with 3PL (e.g. for faster deliveries)?
One thing the author was interested, was the routing optimisation. The identified routes, in 
this research, considered the departure point (Port) and arrival (city). It would be 
interesting to analyse in details the routes optimisation for those cities reachable in the 
same time range (e.g. within 2 hours; or within 200 miles). 
Pag.  147
REFERENCES
Analytiqa (2007), “Portcentric logistics – the supply chain of the future”, available at: 
www.analytiqa.com (accessed 10 December 2007). 
Bapgroup. (2016). Company History | BAP Group LTD. [online] Available at: http://
www.bapgroup.ltd.uk/about-us/company-history/ [Accessed 4 Apr. 2016].
Ballou, R. (1999). Business logistics management. Upper Saddle River, NJ: Prentice Hall.
Beamon, B.M. (1999), ‘Measuring supply chain performance’, International Journal of 
Operations and Production Management, 19, 275–92. 
Bichou, K. and Gray, R. (2004), ‘A logistics and supply chain management approach to 
port performance measurement’, Maritime Policy and Management, 31 (1), 47–67. 
Bigne, E, Ruiz, C and Samz, S (2005) The impact of internet user shopping patterns and 
demographics on consumer mobile buying behaviour, Journal of Electronic Commerce 
Research, 6 (3), pp 193–207 
Bonacich, E. and Wilson, J. (2008). Getting the goods. Ithaca, N.Y.: Cornell University 
Press.
Browne, C. 2010, "Port movements", Timber Trades Journal, Available at: http://
proxy.lib.chalmers.se/login?url=http://search.proquest.com.proxy.lib.chalmers.se/docview/
743959071?accountid=10041 [Accessed 25 Feb. 2016].
Brooks, M.R. (2007), ‘Issues in measuring port devolution program performance: a manag- 
erial perspective’, In M.R. Brooks and K.P.B. Cullinane (eds) Devolution, Port Governance 
and Port Performance, Amsterdam: Elsevier, pp. 619–50. 
Business Sweden. (2016a). Home Page. [online] Available at: http://www.business-
sweden.se/Export/exporthjalp/ [Accessed 2 May 2016].
Business Sweden. (2016). 1st ed. [ebook] p.Business Sweden. Available at: http://
www.business-sweden.se/globalassets/invest-new/retail-guide-sweden-2015-2016.pdf 
[Accessed 8 May 2016].
Butler, S. (2013) “M&S boss under pressure amidst race to upgrade Supply Chain”, The 
Guardian, England, 10 May.  
CMPort.com. (n.d) CMP - Copenhagen Malmö Port. [online] Available at: http://
www.cmport.com [Accessed 17 Apr. 2016].
Pag.  148
CMPort.com. (2016). [online] Available at: http://www.cmport.se/port-info/~/media/docs/
maritime%20service%207/rates/copenhagen/3_prices%20etc%20copenhagen_2016.ashx 
[Accessed 17 Mar. 2016].
Colliers.com. (2016a). Denmark Property Search | Denmark | Colliers International. 
[online] Available at: http://www.colliers.com/en-gb/denmark/properties# [Accessed 4 May 
2016].
Council of Supply Chain Management Professionals, (2016). Homepage | Council of 
Supply Chain Management Professionals. [online] Available at: https://cscmp.org/supply-
chain-management-definitions?XX=1 [Accessed 25 Feb. 2016]. Council of Logistics 
Management; career in logistics  Oak Brook, 3
Christopher, M. (1998) Logistics and Supply Chain Management, 2nd ed., Financial Times, 
London
Christopher, M. (1992), Logistics and Supply Chain Management, 1st ed., Financial Times/
Pitman, London.
Christopher, M., Peck, H. and Towill, D. (2006), “A taxonomy for selecting global supply 
chain strategies”, International Journal of Logistics Management, Vol. 17 No. 2, pp. 
277-87. 
Christopher, M. and Peck, H. (2003) Marketing Logistics, Butterworth-Heineman, London
Christopher, M. and Peck., H. (1998) Fashion Logistics, in Logistics and Retail 
Management, eds Fernie, J and Sparks, L, Kogan Page, London
Christopher, M. and Peck. H (1997) Marketing Logistics, Butterworth Heinemann, Oxford
Coyle, J., Langley, C., Gibson, B., Novack, R. and Bardi, E. (2009). Supply chain 
management. Australia: South-Western.
Cochrane, R.A. (2007), ‘The effects of market differences on the throughput of large con- 
tainer terminals with similar levels of efficiency’, Proceedings of the Annual Conference of 
the International Association of Maritime Economists, Athens, Greece. 
Croucher, P., Baker, P. and Rushton, A. (2014). The Handbook of Logistics and Distribution 
Management: Understanding the Supply Chain. Kogan Page.
Cullinane, K.P.B. and Song, D.-W. (2002), ‘Port privatization policy and practice’, Transport 
Reviews, 22, 55–75. 
Pag.  149
Cullinane, K.P.B., Song, D.-W. and Gray, R. (2002), ‘A stochastic frontier model of the e - 
ciency of major container terminals in Asia: assessing the influence of administrative and 
ownership structures’, Transportation Research Part A, 36, 743–62. 
Cullinane, K. (2002) “The Productivity and Efficiency of Ports and Terminals: Methods and 
Applications”, in C. Grammenos (ed.) The Handbook of Maritime Economics and 
Business, London: Informa, 426–442. 
de Langen, P. W. (2004), ‘Governance in seaport clusters’, Maritime Economics and 
Logistics, 6 (2), 141–56.
de Langen, P. W. and Pallis, A. A. (2005) “Analysis of the Benefits of Intra-Port 
Competition”, a paper presented at the 2005 Annual Meeting of the International 
Association of Maritime Economists, Limassol, Cyprus. 
de Langen, P. (2002), “Clustering and performance: the case of maritime clustering in The 
Netherlands”, Maritime Policy and Management, Vol. 29, pp. 209-21. 
de Lombaerde, P. and Verbeke, A. (1989) “Assessing International Seaport Competition: A 
Tool for Strategic Decision Making”, International Journal of Transport Economics, 16: 
175–192. 
Doing Business. (2016a). [online] Available at: http://www.doingbusiness.org/data/
exploreeconomies/denmark [Accessed 2 May 2016].
Doing Business. (2016b). [online] Available at: http://www.doingbusiness.org/data/
exploreeconomies/norway[Accessed 2 May 2016].
Doing Business. (2016c). [online] Available at: http://www.doingbusiness.org/data/
exploreeconomies/sweden [Accessed 2 May 2016].
EcotransIT. (2016). [online] Available at: http://www.ecotransit.org/calculation.en.html# 
[Accessed 9 May 2016].
Eisenmann, T., Hallowell, R. and Tripsas, M. (2002). Internet business models. Boston, 
Mass.: McGraw-Hill/Irwin.
Ec.europa.eu. (n.d.). Ports - Transport. [online] Available at: http://ec.europa.eu/transport/
modes/maritime/ports/ports_en.htm [Accessed 6 Apr. 2016].
Euromonitor (2016). Euromonitor Index [online] Available at: http://
www.portal.euromonitor.com.ezproxy.ub.gu.se/portal/dashboard/index#/ [Accessed 7 May 
2016].
Pag.  150
Eurostat (2013). [online] Available at: http://ec.europa.eu/eurostat/web/transport/data/
database [Accessed 7 May 2016].
Eurostat. (2014). [online] Available at: http://ec.europa.eu/eurostat/web/transport/data/
database [Accessed 7 May 2016].
ESPO. (2015). Fact and Figures. [online] Available at: http://www.espo.be/fact-and-
figures [Accessed 1 May 2016].
Feng, C.-M. and Hsieh, H.-C. (2008) “Creating Value-Driven Port Logistics in Free Trade 
Zones”, a paper presented at the 2008 International Forum on Shipping, Ports and 
Airports, Hong Kong Polytechnic University, Hong Kong. 
Fernie, J. (1994) Quick Response: an international perspective, International Journal of 
Physical Distribution & Logistics Management, 24 (6), pp 38–46
Fernie, J. and Sparks, L. (2015). Logistics and retail management. Johanneshov: MTM.
Fisher, M. (1997), “What is the right supply chain for your product?”, Harvard Business 
Review, March/April.
Fleming, D. K. and Baird, A. J. (1999) “Some Reflections on Port Competition in the United 
States and Europe”, Maritime Policy and Management, 26: 383–394. 
Foreign-trade.com. (2016). Harmonized System Codes (HS Code) Commodity 
Classification - Foreign Trade Online. [online] Available at: http://www.foreign-trade.com/
reference/hscode.htm [Accessed 5 May 2016].                               
Global Internet Report. (2016). 1st ed. [ebook] Available at: http://www.internetsociety.org/
globalinternetreport/assets/download/IS_web.pdf [Accessed 5 Apr. 2016].
Goss, R. (1990), “Economic policies and seaports: 4. Strategies for port authorities”, 
Maritime Policy and Management, Vol. 17 No. 4, pp. 273-87. 
Haralambides, H.E. (2002), ‘Competition, excess capacity and the pricing of port 
infrastructure’, International Journal of Maritime Economics, 4, 323–47.
HAYUTH, Y., 1981, Containerization and the load centre concept. Economic Geography, 
57, 160–176. 
Heaver, T. (2001), ‘The evolving roles of shipping lines in international logistics’, 
International Journal of Maritime Economics, 4, 210–30. 
Haezendonck, E. (2001) Essays on Strategy Analysis for Seaports, Leuven: Garant.
Pag.  151
Hult T., Closs D and Frayer D, (2014). Global Supply Chain Management: Leveraging 
Processes, Measurements, and Tools for Strategic Corporate Advantage. McGraw-Hill.
Jansson, J.O. and Shneerson, D. (1987), Liner Shipping Economics, London: Chapman & 
Hall.
Kurt Salmon Associates (KSA) (1997) Quick Response: meeting customer needs, Atlanta, 
GA
IMRG (2011) United Kingdom E-business Information [online] www.imrg.org (accessed 25 
October)
Internetlivestats.com. (2016). Internet Users by Country (2016) - Internet Live Stats. 
[online] Available at: http://www.internetlivestats.com/internet-users-by-country/ [Accessed 
5 Apr. 2016].
Investindk.com. (2016). Ministry of Foreign Affairs of Denmark - Invest in Denmark. [online] 
Available at: http://www.investindk.com [Accessed 7 May 2016].
Investineu.com. (2016). Invest in Sweden | Invest in EU. [online] Available at: http://
www.investineu.com/content/invest-sweden [Accessed 12 May 2016].
Importservices.co.uk. (2016). Retail Supply Chain Logistics | Import Services. [online] 
Available at: http://importservices.co.uk [Accessed 8 May 2016].
Lambert, D. and Stock, J. (1993). Strategic logistics management. Homewood, IL: Irwin.
Laseter, T, Houston, P, Ching, A, Byrne, S, Turner, M and Devendran, A (2000) The last 
mile to nowhere, Strategy & Business, (20), September 
Limao, N. and Venables, A.J. (2001), ‘Infrastructure, geographical disadvantage, and 
trans- port costs’, World Bank Economic Review, 15, 451–79. 
Lirn, T.C., Thanopoulou H.A., Beynon, M. and Beresford, A.K.C. (2004), ‘An application of 
AHP on transshipment port selection: a global perspective’, Maritime Economics and 
Logistics, 6 (1), 70–91.
Liu, Z. (1995), ‘The comparative performance of public and private enterprises’, Journal of 
Transport Economics and Policy, 29, 263–74.
Livey, P. (2005), “Inland transport by container: why think water?”, paper presented at Sea 
and Water Conference, Hull. 
Pag.  152
Londongateway.com. (2016). London Gateway : Logistics Park. [online] Available at: http://
www.londongateway.com/logistics-park/ [Accessed 6 Apr. 2016].
Luenberger, D. (1992), ‘Bene t function and duality’, Journal of Mathematical Economics, 
21, 461–81.
Lun, Y., Lai, K., Wong, C. and Cheng, T. (2016). Green shipping management. Springer
Mallard, G. and Glaister, S. (2008). Transport economics. Basingstoke [England]: Palgrave 
Macmillan.
Mangan, J., Lalwani, C. and Fynes, B. (2008). Port‐centric logistics. Int Jrnl Logistics 
Management, 19(1), pp.29-41.
Mangan, J., Lalwani, C., & Fynes, B. (2008). Port-centric logistics. International Journal of 
Logistics Management, 19(1), 29-41. doi:http://dx.doi.org/10.1108/09574090810872587
Marlow, P.B. and Paixao Casaca, A.C. (2003), ‘Measuring lean ports performance’, 
International Journal of Transport Management, 1, 189–202.
Marshall, A. (2005), “US-Asia trade boom blighted by logistics bottlenecks”, CILT World, p. 
11. 
Martinez-Budria, E., Diaz-Armas, R., Navarro-Iba ez, M. and Ravelo-Mesa, T. (1999), ‘A 
study of the e ciency of Spanish port authorities using data envelopment analysis’, 
International Journal of Transport Economics, 2, 237–53. 
Matthews, H, Hendrickson, C and Soh, D L (2001) environmental and economic effects of 
e-commerce: a study of book publishing and retail logistics, Transportation Research 
Record, 1763, pp 6–12 
McLeod, F, Cherrett, T and Song, L (2006) Transport impacts of local collection / delivery 
points, International Journal of Logistics: Research and Applications, 9 (3), pp 307–17
McKinnon, A., Browne, M. and Whiteing, A. (2012). Green logistics. London: Kogan Page.
McKinnon, A. & Woodburn, A. 1993, Logistical perspective on the growth of lorry traffic.
McKinnon, A C (1996) The Development of Retail Logistics in the UK: A Position Paper, 
Technology Foresight: Retail and Distribution Panel, Edinburgh, Heriot-Watt University 
Pag.  153
McKinnon, A C and Tallam, D (2003) Unattended delivery to the home: an assessment of 
the security implications, International Journal of Retail and Distribution Management, 31 
(1), pp 30–41
Metapack (1999) Be-ful- lled, Metapack, London
METI (2002) Seni Sangyo no Genjo to Seisaku Taiou (The Current Status of the Japanese 
Textile Industry and the Political Responses), METI (The Japanese Ministry of Economy, 
Trade, and Industry; formerly MITI), Tokyo. 
Mitchell, A (1997) Ef cient Consumer Response: a new paradigm for the European FMCG 
sector, FT Retail & Consumer Publishing, Pearson Professional, London 
MITI (1993) Seni Vision (Textile Vision), MITI (The Japanese Ministry of International 
Trades and Industries), Tokyo 
MITI (1995) Sekai Seni Sangyo Jijo (MITI World Textile Report), MITI, Tokyo 
MITI (1999) Seni Vision (Textile Vision), MITI, Tokyo
Monios J. & Wilmsmeier G. (2012) Port-centric logistics, dry ports and offshore logistics 
hubs: strategies to overcome double peripherality?, Maritime Policy & Management, 39:2, 
207-226, DOI: 10.1080/03088839.2011.650720 
Monios, J., 2011, The role of inland terminal development in the hinterland access 
strategies of Spanish ports. Research in Transportation Economics, 33(1), 59–66. 
Mulcahy, D. (1994). Warehouse distribution and operations handbook. New York: McGraw-
Hill.
Nairn, G (2003) Not Many Happy Returns, Financial Times, 5 February 
NCFRP. (2013). 1st ed. [ebook] NCFRP, p.Freight Facility Location Selection: A Guide for 
Public Officials. Available at: http://onlinepubs.trb.org/onlinepubs/ncfrp/ncfrp_rpt_013.pdf 
[Accessed 14 Apr. 2016].
Notteboom, T.E. (2004), ‘Container shipping and ports: an overview’, Review of Network 
Economics, 3, 86–106. 
Northamptonshire Enterprise Partnership. (2012). [online] Available at: http://
www.northamptonshireep.co.uk/news/ 2012/new-report-reveals-growth-in- uks-logistics-
golden-triangle/ [Accessed 4 Apr. 2016].
Pag.  154
Notteboom, T. (2002) “Consolidation and Contestability in the European Container 
Handling Industry”, Maritime Policy and Management, 29: 257–269. 
Notteboom, T.E. (2002), ‘Consolidation and contestability in the European container 
handling industry’, Maritime Policy and Management, 29, 71–89.
Notteboom, T.E. and Winkelmans, W. (2001), ‘Structural changes in logistics: How will port 
authorities face the challenge?’, Maritime Policy and Management, 28, 71–89.
Notteboom, T. and Rodrigue, J. (2005), “Port regionalisation: towards a new phase in port 
development”, Maritime Policy and Management, Vol. 32 No. 3, pp. 297-313.
O’Leary-Kelly, S. and Flores, B. (2002). The integration of manufacturing and marketing/
sales decisions: impact on organizational performance. Journal of Operations 
Management, 20(3), pp.221-240.
Oldhager, J (2003) Strategic positioning of the order penetration point, International 
Journal of Production Economics, 83 (3), pp 319–29
Paixa  ̃O, A. C. and Marlow, P. B., 2003, Fourth generation ports – a question of agility?  
International Journal of Physical Distribution and Logistics Management, 33, 355–376. 
Panayides, P. M. (2006) “Maritime Logistics and Global Supply Chains: Towards a 
Research Agenda”, Maritime Economics and Logistics, 8: 3–18.
Panayides, P. M. and Song, D. W. (2006) “Port Supply Chain Orientation and 
Performance”, a paper presented at the 2006 International Association of Maritime 
Economists Conference, Melbourne, Australia. 
PD Ports (2016), Warehousing. [online] Pdports.co.uk. Available at: http://
www.pdports.co.uk/en/portcentric/Warehousing/ [Accessed 4 Apr. 2016].
Pettit, S. J. and Beresford, A. K. C., 2009, Port development: From gateways to logistics 
hubs. Maritime Policy and Management, 36, 253–267. 
Port-centric logistics - Integrated supply chain solution. (2009). Focus, April 2009 pp.52-53.
Portofgothenburg.com. (n.d.). Advantages of the geographical location of the port - Port of 
Gothenburg. [online] Available at: http://www.portofgothenburg.com/About-the-port/
Strategic-Location/Advantages-of-the-gAdvantages-of-the-geographical-location-of-the-
port-eographical-location-of-the-port-/ [Accessed 6 Apr. 2016].
Pag.  155
Portofgothenburg.com. (2016). Port Tariff. [online] Available at: http://
www.portofgothenburg.com/about-the-port/port-tariff/ [Accessed 17 Apr. 2016].
Port of Oslo. (2016). Port of Oslo - tariffs. [online] Available at: http://www.yilport.com/
sayfa.asp?mdl=limanlar&id=10&altID=75 [Accessed 17 Apr. 2016].
Port of Stockholm. (2016). 1st ed. [ebook] Port of Stockholm, p.Price and terms. Available 
at: http://www.portsofstockholm.com/siteassets/prislistor/prices-and-terms-2016-
version-201601.pdf [Accessed 17 Apr. 2016].
Port of Stockholm, (2014). Container Terminal Frihamnen, CTF. [online] Available at: http://
www.portsofstockholm.com/stockholm/container-terminal-ctf/ [Accessed 9 May 2016]
Punakivi, M and Tanskanen, K (2002) Increasing the cost ef ciency of e-ful lment using 
shared reception boxes, International Journal or Retail & Distribution Management, 30 
(10), pp 498–507
Ramstedt, L. (2005). Analysing the effects of governmental control policies in transport 
chains using micro-level simulation. Karlskrona: Blekinge Institute of Technology.
Reve, T (1990) The rm as a means of internal and external contracts, in The Firm as a 
Nexus of Treaties, eds Aoki, M et al, Sage, London, pp 136–88 
Richards, G. (2014). Warehouse Management : A Complete Guide to Improving Efficiency 
and Minimizing Costs in the Modern Warehouse Ed. 2. Kogan Page.
Ring, L J and Tigert, D J (2001) Viewpoint: the decline and fall of internet grocery retailers, 
International Journal of Retail & Distribution Management, 29 (6), pp 266–73 
Robinson, R. (2002), ‘Ports as elements in value-driven chain systems: the new paradigm’, 
Maritime Policy and Management, 29, 241–55.
Rodrigue, D. (2016a). Logistic Costs Breakdown. [online] Available at: https://
people.hofstra.edu/geotrans/eng/ch5en/conc5en/logistic_costs_breakdown.html 
[Accessed 16 Mar. 2016].
Rodrigue, D. (2016b). The Geography of Transportation Networks. [online] 
People.hofstra.edu. Available at: https://people.hofstra.edu/geotrans/eng/ch1en/conc1en/
ch1c4en.html [Accessed 16 Mar. 2016].
Rodrigue, D. (2016c). Transport Hub. [online] Available at: https://people.hofstra.edu/
geotrans/eng/ch1en/conc1en/hubnetwork.html [Accessed 16 Mar. 2016].
Pag.  156
Rodrigue, D. (2016d). Green Logistics. [online] People.hofstra.edu. Available at: https://
people.hofstra.edu/geotrans/eng/ch8en/appl8en/ch8a4en.html [Accessed 16 Mar. 2016].
Rodrigue, D. (2016e). Transportation and Space. [online] People.hofstra.edu. Available at: 
https://people.hofstra.edu/geotrans/eng/ch1en/conc1en/ch1c2en.html [Accessed 16 Mar. 
2016].
Rodrigue, D. (2016f). Logistics Goals and Operations. [online] Available at: https://
people.hofstra.edu/geotrans/eng/ch5en/conc5en/logisticsoperations.html [Accessed 2 Apr. 
2016].
Rodrigue, D. (2016g). Network Structure. [online] Available at: https://people.hofstra.edu/
geotrans/eng/ch1en/conc1en/networkstructure.html [Accessed 16 Mar. 2016].
Rodrigue, D. (2016h). Operational Advantages of Foreign Trade Zones (FTZ). [online] 
Av a i l a b l e a t : h t t p s : / / p e o p l e .h o f s t r a . e d u /g e o t r a n s /e n g / c h 4 e n /a p p l 4 e n /
table_foreigntradezones.html [Accessed 16 Mar. 2016].
Rodrigue, D. (2016i). Logistics and Freight Distribution. [online] People.hofstra.edu. 
Available at: https://people.hofstra.edu/geotrans/eng/ch5en/conc5en/ch5c4en.html 
[Accessed 13 Apr. 2016].
Rodrigue, D. (2016l). Evolution of Retail Logistics. [online] Available at: https://
people.hofstra.edu/geotrans/eng/ch5en/conc5en/evol_retail_logistics.html [Accessed 15 
Apr. 2016].
Rodrigue, D. (2016m) Logistics Facilities Supporting E-commerce. [online] Av ailable at: 
https://people.hofstra.edu/geotrans/eng/ch5en/conc5en/
table_logstics_facilities_ecommerce.html [Accessed 14 Apr. 2016].
Rodrigue, J., Comtois, C. and Slack, B. (2013). The geography of transport systems. 
Routledge.
Rodrigue, J. and Hesse, M. (2007) in Leinbach, T. and Capineri, C. (Eds), Globalized 
Freight Transport, Edward Elgar, London. 
Roll, Y. and Hayuth, Y. (1993), ‘Port performance comparison applying data envelopment 
analysis (DEA)’, Maritime Policy and Management, 20, 153–61. 
Sanchez, R., Hoffmann, J., Micco, A., Pizzolitto, G., Sgut, M. and Wilmsweier, G. (2003), 
“Port efficiency and international trade: port efficiency as a determinant of maritime 
transport costs”, Maritime Economics and Logistics, Vol. 5, pp. 199-218. 
Pag.  157
Sang-Hun, C. (2006), “A tale of 2 ports”, International Herald Tribune, December. 
Savills (2013) E-tailing and the impact on distribution warehouses, available at http://
www.transportintelligence.com/white_papers.php?page=2 (accessed 30 March 2016) 
Ship2Shore (2007), “Port-centric logistics”, Ship2Shore, No. 1, customer magazine of 
Hutchinson Ports. 
SeaRates. (2016). Transit Time, Distance calculator & Port to port distances. [online] 
Available at: https://www.searates.com/reference/portdistance/?
K=ChIJOfBn8mFuQUYRmh4j019gkn4&A=ChIJMzz1sUBwsjURoWTDI5QSlQI&D=706&G
=33977&shipment=1&container=40st&weight=1& [Accessed 8 May 2016]
Sea-web.com. (2016). Sea-web. [online] Available at: http://sea-web.com [Accessed 9 May 
2016].
Sea-web.com. 2016a. Port of Copenhagen development. [online] Available at: http://
www.sea-web.com.proxy.lib.chalmers.se/authenticated/authenticated_handler.aspx?
control=portovw&WorldPortNumber=PO1422 [Accessed 9 May 2016].
Sea-web.com. (2016b). Port of Malmo development. [online] Available at: http://www.sea-
web.com.proxy. l ib .chalmers.se/authent icated/authent icated_handler.aspx?
control=portovw&WorldPortNumber=PO3225 [Accessed 9 May 2016].
Sea-web.com. (2016c). Port  of Oslo development. [online] Available at: http://www.sea-
web.com.proxy.lib.chalmers.se/authenticated/authenticated_handler.aspx?
control=portovw&WorldPortNumber=PO2303 [Accessed 9 May 2016].
Sea-web.com, (2016d). Norway project looks to spur port and ship electrification. [online] 
Available at: http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/
authenticated_handler.aspx?
control=articledisplay&articlename=dn0020151021000004&WorldPortNumber=PO2303 
[Accessed 9 May 2016].
Sea-web. (2016e). Port of Stockholm. [online] Available at: http://www.sea-
web.com.proxy.lib.chalmers.se/authenticated/authenticated_handler.aspx?
control=portovw&WorldPortNumber=PO2626 [Accessed 9 May 2016].
Sea-web.com, (2016f). Gothenburg to build terminal, use not yet decided. [online] 
Available at: http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/
authenticated_handler.aspx?
control=articledisplay&articlename=dn0020160303000006&WorldPortNumber=PO2582 
[Accessed 9 May 2016].
Pag.  158
Sea-web.com. (2016g). Port of Gothenburg. [online] Available at: http://www.sea-
web.com.proxy.lib.chalmers.se/authenticated/authenticated_handler.aspx?
control=portovw&WorldPortNumber=PO2582#6 [Accessed 9 May 2016].
Sea-web.com, (2015a). Gothenburg switches to simpler call notification system. [online] 
Available at: http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/
authenticated_handler.aspx?
control=articledisplay&articlename=dn0020151005000013&WorldPortNumber=PO2582 
[Accessed 9 May 2016].
Sea-web.com, (2015b). Gothenburg to build SEK4 billion logistics park. [online] Available 
at: http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/
authenticated_handler.aspx?
control=articledisplay&articlename=dn0020150624000016&WorldPortNumber=PO2582 
[Accessed 9 May 2016].
Sea-web.com, (2015c). Port of Gothenburg environmental discount attracts green ships. 
[online] Available at: http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/
authenticated_handler.aspx?
control=articledisplay&articlename=dn0020151002000011&WorldPortNumber=PO2582 
[Accessed 9 May 2016].
Sea-web.com, (2015d,). Port of Gothenburg freezes tariffs for 2016. [online] Available at: 
http://www.sea-web.com.proxy.lib.chalmers.se/authenticated/authenticated_handler.aspx?
control=articledisplay&articlename=dn0020151009000008&WorldPortNumber=PO2582 
[Accessed 9 May 2016].
Sheehan William G., 1989, “Contract warehousing: The evolution an Industry “, Journal go 
Business Logistics 10, no. 1 (2989), p. 31
Slack, B. (2006a) “An Economic Theory of the Port”, in K. Cullinane and W. K. Talley (eds) 
Port Economics: Research in Transportation Economics, 16, Amsterdam: Elsevier, 43–65.
Slack, B. (2006b) “Optimum Port Throughput”, in L. Shuguang and Y. Jinkai (eds) 
Approaches to Maritime Industrial Economy, Beijing, China: Economic Science Press, 21–
32.
Slack, B. and Wang, J. J., 2002, The challenge of peripheral ports: An Asian perspective. 
Geojournal, 56, 159–166. 
Pag.  159
Slack, B., Comtois, C., Mccalla, R.J. and Guy, E. (2001), ‘Global reach: the evolving 
pattern of container shipping networks’, World Conference on Transportation Research, 
Seoul. 
Slack, B., Comtois, C. and Sletmo, G. (1996), ‘Shipping lines as agents of change in the 
port industry’, Maritime Policy and Management, 23, 289–300.
Slack, B., (1994) “Performance Indicators and Port Performance Evaluation”, Logistics and 
Transportation Review, 30: 339–352.
Slack, B. (1985) “Containerization, Inter-Port Competition and Port Selection”, Maritime 
Policy and Management, 12: 293–303. 
Sparks, L (1998) The Retail Logistics Transformation, in Logistics and Retail Management, 
eds Fernie, J and Sparks, L, London, Kogan Page 
Sparks, L (2010) Supply Chain Management and Retailing, Supply Chain Forum – an 
international journal, 11 (4), pp 4–12 
Statista. (2016). B2C e-commerce: revenue in Europe 2012-2018 | Statistic. [online] 
Available at: http://www.statista.com/statistics/435843/b2c-e-commerce-revenue-europe/ 
[Accessed 20 Mar. 2016].
Stopford, M. (1997), Maritime Economics, Routledge, London, p. 29. 
Song, D. and Panayides, P. (2012). Maritime logistics. London: Kogan Page.
Suykens, F. (1986) “Ports Should Be Efficient (Even When This Means That Some of 
Them Are Subsidized)”, Maritime Policy and Management, 13: 105–126. 
Talley, W. (2009). Port economics. London: Routledge.
Talley, W.K. (1994), ‘Performance indicators and port performance evaluation’, Logistics 
and Transportation Review, 30, 339–52. 
Talley, W. K. (1986) “A Comparison of Two Methodologies for Selecting Transit 
Performance Indicators”, Transportation, 13: 201–210.
Tongzon, J. (2001), ‘E ciency measurement of selected Australian and other international 
ports using DEA’, Transportation Research Part A, 35, 113–28. 
Unctadstat.unctad.org. (2016a). UNCTADstat - Container port throughput, annual, 
2008-2014. [online] Available at: http://unctadstat.unctad.org/wds/TableViewer/
tableView.aspx?ReportId=13321 [Accessed 7 Mar. 2016].
Pag.  160
Unctadstat.unctad.org. (2016b). UNCTADstat - Liner Connectivity Index. [online] Available 
at: http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=92 [Accessed 
30 Mar. 2016].
Unctadstat.unctad.org. (2016c). UNCTADstat - Liner shipping bilateral connectivity index, 
annual, 2006-2015. [online] Available at: http://unctadstat.unctad.org/wds/TableViewer/
tableView.aspx?ReportId=96618 [Accessed 30 Mar. 2016]. 
UNCTAD (1976), ‘Port performance indicators’, TD/B/C.4/131/Supp.1/Rev.1, New York: 
United Nations Conference on Trade and Development. 
UNCTAD (1982), Improving Port Performance: Management of General Cargo Operations 
(Trainee’s Workbook), Cardi : Drake Educational Associates. 
Universal Cargo Management, I. (2016). Warehousing and Distribution. [online] 
Universalcargo.com. Available at: http://www.universalcargo.com/Warehousing-and-
Distribution [Accessed 18 Apr. 2016].
USCIB. (2016). VAT Per Country | Value Added Tax Rates By Country | USCIB. [online] 
Available at: http://www.uscib.org/valueadded-taxes-vat-ud-1676/ [Accessed 15 May 
2016].
Verdict Research (2000) Electronic Shopping, UK, Verdict, London
Verdict Research (2004) Verdict on Home Delivery and Ful lment, London
Verhoeff, J. (1981), “Seaport competition: some fundamental and political aspects”, 
Maritime Policy and Management, Vol. 8 No. 1, pp. 49-60. 
Virum, H. (1993): “Third Party Logistics Development in Europe”. Logistics and 
Transportation Review, Vol. 29, no. 4. 
Wall, G. (2007), “Heading for the coast: is port-centric logistics the way forward”, Focus, 
October, pp. 42-4. 
Wang, T.-F. and Cullinane, K.P.B. (2006), ‘The e ciency of European container terminals 
and implications for supply chain management’, Maritime Economics and Logistics, 8, 82–
99.
Watson, M., Lewis, S., Cacioppi, P. and Jayaraman, J. (2013). Supply chain network 
design. Upper Saddle River, N.J.: FT Press.
Pag.  161
Weltevreden, J W J (2008) B2C e-commerce logistics: the rise of collection and delivery 
points in the Netherlands, International Journal of Retail and Distribution Management, 36 
(8), 638–60
Wright, R. (2007), “Hong Kong’s port faces a rising tide of competition”, Financial Times, 
April. 
Williamson, O E (1979) Transaction-cost economics: the governance of contractual 
relations, Journal of Law and Economics, 22, pp 232–61
Williamson, O E (1990) The rm as a nexus of treaties: an introduction, in The Firm as a 
Nexus of Treaties, eds Aoki, M et al, Sage, London 
World Bank (2001) World Bank Port Reform Tool Kit: Module 1. Available online at http://
rru.worldbank.org/Documents/Toolkits/ports_fulltoolkit.pdf (accessed 25 February 2016). 
World Economic Forum. (2016). Networked Readiness Index 2015. [online] Available at: 
https://widgets.weforum.org/gitr2015/ [Accessed 5 May 2016].
Xing, Y and Grant, D (2006) Developing a framework for measuring physical distribution 
service quality of multi-channel and ‘pure player’ internet retailers, International Journal of 
Retail & Distribution Management, 34 (4/5), pp 278–89 
Zhang, A. (2008), ‘The impact of hinterland access conditions on rivalry between ports’, 
Discussion paper no. 2008-8, Joint Research Centre, OECD and ITF. 
Zhang, A. (2008) “The Impact of Hinterland Access Conditions on Rivalry Between Ports”, 
a paper presented at the International Forum on Shipping, Ports and Airports, Hong Kong 
Polytechnic University, Hong Kong. 
Pag.  162
APPENDIX “A” - HS CODES 
The Appendix “A” refers about the Harmonised system codes, applied during the import/export 
analysis. 
Below are classified the categories by type of products (HS Codes by category): 
HS from 01 to 05  Animal & Animal Products
HS from 06 to15  Vegetable Products
HS from 16 to 24  Foodstuffs
HS from 25 to 27  Mineral Products 
HS from 28 to 38  Chemicals & Allied Industries 
HS from 39 to 40  Plastics / Rubbers 
HS from 41 to 43  Raw Hides, Skins, Leather, & Furs
HS from 44 to 49  Wood & Wood Products
HS from 50 to 63  Textiles 
HS from 64 to 67  Footwear / Headgear
HS from 68 to 71  Stone / Glass 
HS from 72 to 83  Metals 
HS from 84 to 85  Machinery / Electrical
HS from 86 to 89  Transportation 
HS from 90 to 97  Miscellaneous 
HS from 98 to 99  Service 
Source: Foreign-Trade.com (2016)
The author’s classification is focused primarily on the main trade categories, classified by the Port 
of Gothenburg, because the products are part of the e-commerce (B2C). 
The author’s analysis was focused primarily on each single code data (e.g. HS 30 import-export-
country), afterwards all the categories belonging to the HS range (e.g. 28-38) were merged and 
summed, in order to provide a general overview about the HS range category. 
 
A detailed analysis is presented in the Appendix A-B-C-D-E-F. 
Pag.  163
Table A.1 Selected HS Codes by Range (macro category) and by Description (sub-category)
HS range 
HS 
cod
e 
HS Description
28-38  Chemicals & Allied Industries 30 Pharmaceutical Products
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes
37 Photographic Or Cinematographic Goods
41-43  Raw Hides, Skins, Leather, & 
Furs 42
Articles Of Leather, Saddlery & Harness, Travel Goods, 
Handbags, Articles Of Gut
44-49  Wood & Wood Products 48 Paper & Paperboard, Articles Of Paper Pulp
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans
50-63  Textiles 57 Carpets & Other Textile Floor Coverings
60 Knitted Or Crocheted Fabrics
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags
64-67  Footwear / Headgear 64  Footwear, Gaiters, & The Like
65 Headgear & Other Parts
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts
68-71  Stone / Glass 69 Ceramic Products
72-83  Metals 71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins
84-85  Machinery / Electrical 84 Nuclear Reactors, Boilers, Machinery & Mechanical Appliances, Computers
only selected sub category 8467 Tools for working in the hand, pneumatic etc, pts
only selected sub category 8468 Machines, solder etc, gas surf temper machines, pt
only selected sub category 8469 Typewriters & word processing machines
only selected sub category 8470 Calculating & account machines, cash registers etc
85 Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound Recorders, Television Recorders
Pag.  164
If the reader is interested in a deeper investigation about HS codes’ categories, is 
suggested to review the following link www.foreign-trade.com/reference/hscode.htm; in 
opposite World Custom Organisation provide the official source (www.wcoomd.org)
90-97  Miscellaneous 90
Optical, Photographic, Cinematographic, Measuring, 
Checking, Precision, Medical Or Surgical Instruments & 
Accessories
91 Clocks & Watches & Parts Thereof
92 Musical Instruments, Parts & Accessories
94
Furniture, Bedding, Cushions, Lamps & Lighting Fittings 
Nesoi, Illuminated Signs, Nameplates & The Like, 
Prefabricated Buildings
95  Toys, Games & Sports Equip, Parts & Acces.
96 Miscellaneous Manufactured Articles
Source: Foreign-Trade.com, 2016
HS 
cod
e 
HS DescriptionHS range 
Pag.  165
APPENDIX “B” - OVERVIEW TRADE COUNTRIES
Table B.1 Import-Export Value Selected Countries
Table B.2 Export - Selected HS Codes by Country
1) Import (Trade in USD) Export (Trade in USD) Total (USD)
Denmark 85.275.438.764 94.425.784.552 179.701.223.316
Finland 60.174.387.730 59.682.311.206 119.856.698.936
Norway 76.979.322.634 106.251.085.040 183.230.407.674
Sweden 137.986.741.780 140.089.772.744 278.076.514.524
Source: UN	Comtrade,	2015
HS 
codes HS Description Sweden Finland Denmark Norway 
28-38 Chemicals & Allied 
Industries 
8.443.048.244 1.127.514.058 12.659.737.628 834.793.149
41-43 Raw Hides, Skins, 
Leather, & Furs
211.428.561 34.433.673 201.023.900 13.642.689
44-49 Wood & Wood 
Products
8.988.436.856 8.236.355.044 1.237.368.831 507.833.302
50-63 Textiles 2.066.164.806 368.473.432 4.296.400.450 123.968.088
64-67 Footwear / Headgear 348.046.409 117.598.048 619.801.848 23.160.046
68-71 Metals 1.225.121.467 656.972.372 408.112.125 501.144.176
84-85 Machinery / Electrical 15.895.580.086 5.175.400.498 5.274.490.072 2.967.785.766
90-97 Miscellaneous 7.742.468.820 3.244.270.981 7.837.449.258 2.721.165.950
Total 44.920.295.249 18.961.018.106 32.534.384.112 7.693.493.166
Source: UN	Comtrade,	2015
Pag.  166
Table B.3 Import - Selected HS codes by Country
HS 
codes HS Description Sweden Finland Denmark Norway 
28-38 Chemicals & Allied 
Industries 
5.345.119.519 2.796.001.394 4.943.932.835 2.879.054.102
41-43 Raw Hides, Skins, 
Leather, & Furs
480.539.116 177.773.552 373.306.306 275.791.578
44-49 Wood & Wood 
Products
1.820.695.233 717.156.570 1.765.214.555 1.413.451.958
50-63 Textiles 4.612.020.740 1.618.216.918 4.877.269.456 2.707.999.190
64-67 Footwear / Headgear 1.019.245.504 396.859.937 1.024.446.899 709.933.125
68-71 Metals 609.609.362 255.478.727 524.884.341 558.381.408
84-85 Machinery / Electrical 17.613.259.480 5.920.572.519 8.382.165.235 7.008.866.893
90-97 Miscellaneous 8.054.959.383 3.331.098.527 5.797.264.615 6.611.223.602
Total 39.555.448.337 15.213.158.144 27.688.484.242 22.164.701.856
Source: UN	Comtrade,	2015
Pag.  167
APPENDIX “C” - DETAIL TRADE DENMARK 
Table C.1 Denmark Import - Export 2015
Table C.2 Denmark - Top 5 Import Countries (Value in USD)
Table C.3 Denmark - Top 5 Export Countries (Value in USD)
Import (Trade in 
USD)
Export (Trade in 
USD)
Total (USD)
85.275.438.764 94.425.784.552 179.701.223.316
Source: UN Comtrade, 2015
Denmark - top 5 Import Countries Trade in USD 2015
Germany 17.400.249.204
Sweden 10.498.794.750
Netherlands 6.815.631.900
China 6.374.960.249
United Kingdom 3.831.320.193
Source: UN	Comtrade,	2015
Denmark - top 5 Export  Countries Trade in USD  2015
Germany 15.291.829.247
Sweden 10.446.351.869
United	Kingdom 5.417.966.597
Norway 6.007.744.956
USA 5.219.600.875
Source: UN	Comtrade,	2015
Pag.  168
Table C.4 Denmark, Import/Export 2015 Neighbours countries
Table C.5.1 Denmark Import Data 2015 by HS category
Denmark - Import/Export 
Neighbours countries Trade in USD 2015 
Sweden 20.945.146.619
Import 10.498.794.750
Export 10.446.351.869
Norway 10.000.714.488
Import 3.992.969.532
Export 6.007.744.956
Finland 3.430.167.664
Import 1.107.212.473
Export 2.322.955.191
Source: UN	Comtrade,	2015
HS groups - Import 2015 Description Total trade in USD
28-38 Chemicals & Allied Industries 4.943.932.835
41-43 Raw Hides, Skins, Leather, & 
Furs 373.306.306
44-49 Wood & Wood Products 1.765.214.555
50-63 Textiles 4.877.269.456
64-67 Footwear / Headgear 1.024.446.899
68-71 Metals 524.884.341
84-85 Machinery / Electrical 8.382.165.235
90-97 Miscellaneous 5.797.264.615
Source: UN Comtrade, 2015
Pag.  169
Pag.  170
Figure C.1 Import Denmark selected HS codes 2015 
(value in USD) (table C.5.1)
20,94%
30,27%
1,90%3,70%
17,61%
6,38%
1,35%
17,86%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table C.5.2 Denmark Import Data 2015 by HS Category (Detail)
HS 
code HS description
Trade Value 
(US$) 2015 
30 Pharmaceutical Products 3.846.069.412
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 636.266.721
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 419.584.612
37 Photographic Or Cinematographic Goods 42.012.090
42 Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of Gut 373.306.306
48 Paper & Paperboard, Articles Of Paper Pulp 1.399.430.863
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 365.783.692
57 Carpets & Other Textile Floor Coverings 83.918.682
60 Knitted Or Crocheted Fabrics 38.562.817
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 1.977.621.465
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 2.325.413.639
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 451.752.853
64  Footwear, Gaiters, & The Like 948.528.852
65 Headgear & Other Parts 58.169.290
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 17.748.757
69 Ceramic Products 304.248.035
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 220.636.306
8467 Tools for working in the hand, pneumatic etc, pts 191.973.671
8468 Machines, solder etc, gas surf temper machines, pt 4.132.588
8469 Typewriters & word processing machines 134.926
8470 Calculating & account machines, cash registers etc 17.167.900
85 Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound Recorders, Television Recorders 8.168.756.150
90 Optical, Photographic, Cinematographic, Measuring, Checking, Precision, Medical Or Surgical Instruments & Accessories 2.419.001.699
91 Clocks & Watches & Parts Thereof 135.034.584
92 Musical Instruments, Parts & Accessories 26.432.696
94 Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated Signs, Nameplates & The Like, Prefabricated Buildings 2.081.219.411
95  Toys, Games & Sports Equip, Parts & Acces. 876.003.832
96 Miscellaneous Manufactured Articles 259.572.393
Source: UN Comtrade, 2015
Pag.  171
Table C.6.1 Export Denmark selected HS codes 2015 (value in USD)
HS groups Export DK 2015 Description Total trade in USD
28-38 Chemicals & Allied Industries 12.659.737.628
41-43 Raw Hides, Skins, Leather, & 
Furs
201.023.900
44-49 Wood & Wood Products 1.237.368.831
50-63 Textiles 4.296.400.450
64-67 Footwear / Headgear 619.801.848
68-71 Metals 408.112.125
84-85 Machinery / Electrical 5.274.490.072
90-97 Miscellaneous 7.837.449.258
Source: UN Comtrade, 2015
Pag.  172
Figure C.2 Export Denmark selected HS 
codes 2015 (value in USD) (table C.6.1)
24,09%
16,21%
1,25%
1,91%
13,21%
3,80%
0,62%
38,91%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table C.6.2 Export Denmark selected HS Codes 2015 (value in US$)
HS 
code HS description
Trade Value (US
$) 2015
30 Pharmaceutical Products 11.689.501.202
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 420.633.703
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 539.735.303
37 Photographic Or Cinematographic Goods 9.867.420
42 Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of Gut 201.023.900
48 Paper & Paperboard, Articles Of Paper Pulp 708.929.350
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 327.415.581
57 Carpets & Other Textile Floor Coverings 173.734.115
60 Knitted Or Crocheted Fabrics 47.091.291
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 1.702.210.536
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 2.106.652.950
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 266.711.558
64  Footwear, Gaiters, & The Like 583.105.924
65 Headgear & Other Parts 30.789.906
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 5.906.018
69 Ceramic Products 206.095.965
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 202.016.160
8467 Tools for working in the hand, pneumatic etc, pts -881.343.960,7
8468 Machines, solder etc, gas surf temper machines, pt -1.104.901.269
8469 Typewriters & word processing machines -1.328.458.578
8470 Calculating & account machines, cash registers etc 6.739.758
85 Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound Recorders, Television Recorders 8.582.454.122
90 Optical, Photographic, Cinematographic, Measuring, Checking, Precision, Medical Or Surgical Instruments & Accessories 3.887.464.625
91 Clocks & Watches & Parts Thereof 46.222.365
92 Musical Instruments, Parts & Accessories 21.263.277
94 Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated Signs, Nameplates & The Like, Prefabricated Buildings 2.673.363.475
95  Toys, Games & Sports Equip, Parts & Acces. 874.565.498
96 Miscellaneous Manufactured Articles 334.570.018
Source: UN Comtrade, 2015
Pag.  173
APPENDIX “D” - DETAIL TRADE FINLAND
Table D.1 Finland Import - Export 2015
Table D.2 Finland - Top 5 Import Countries (Value in USD)
Table D.3 Finland - Top 5 Export Countries (Value in USD)
Import (Trade in 
USD)
Export (Trade in 
USD)
Total (USD)
60.174.387.730 59.682.311.206 119.856.698.936
Source: UN Comtrade, 
2015
Country Trade in USD 2015
Germany 8.990.539.819
Sweden 6.744.042.668
Russian	Federa?on 6.587.281.553
China 4.368.658.494
Netherlands 3.167.943.473
Source: UN Comtrade, 2015
Country Trade in USD 2015
Germany 8.099.889.695
Sweden 6.049.930.545
USA 4.003.917.948
Netherlands 3.825.796.158
Russian	Federa?on 3.443.649.012
Source: UN Comtrade, 2015
Pag.  174
Table D.4 Finland, Import/Export 2015 Neighbours countries
Table D.5.1 Finland Import Data 2015 by HS Category
Country Trade in USD 2015 
Sweden 12.793.973.213
Import 6.744.042.668
Export 6.049.930.545
Norway 2.799.577.917
Import 1.089.040.375
Export 1.710.537.542
Denmark 2.924.759.588
Import 1.914.137.937
Export 1.010.621.651
Source: UN Comtrade, 2015
HS description Total value USD
28-38 Chemicals & Allied Industries 2.796.001.394
41-43 Raw Hides, Skins, Leather, & Furs 177.773.552
44-49 Wood & Wood Products 717.156.570
50-63 Textiles 1.618.216.918
64-67 Footwear / Headgear 396.859.937
68-71 Metals 255.478.727
84-85 Machinery / Electrical 5.920.572.519
90-97 Miscellaneous 3.331.098.527
Source: UN Comtrade, 2015
Pag.  175
Pag.  176
Figure D.1 Finland Import Data 2015 by HS category (table 
D.5.1)
22%
39%
2%
3%
11%
5%
1%
18%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table D.5.2 Finland Import Data 2015 by HS Category (detail)
HS code HS description
Trade Value (US$) 
2015
30 Pharmaceutical Products 2.198.839.844
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 270.269.048
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 308.671.680
37 Photographic Or Cinematographic Goods 18.220.822
42
Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of 
Gut
177.773.552
48 Paper & Paperboard, Articles Of Paper Pulp 565.119.752
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 152.036.818
57 Carpets & Other Textile Floor Coverings 66.483.013
60 Knitted Or Crocheted Fabrics 16.061.218
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 648.324.545
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 711.175.173
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 176.172.969
64  Footwear, Gaiters, & The Like 338.568.381
65 Headgear & Other Parts 52.478.130
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 5.813.426
69 Ceramic Products 166.356.611
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 89.122.116
8467 Tools for working in the hand, pneumatic etc, pts 154.302.831
8468 Machines, solder etc, gas surf temper machines, pt 8.183.755
8469 Typewriters & word processing machines 14.591
8470 Calculating & account machines, cash registers etc 29.665.880
85
Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound 
Recorders, Television Recorders 5.728.405.462
90
Optical, Photographic, Cinematographic, Measuring, Checking, Precision, 
Medical Or Surgical Instruments & Accessories 1.681.259.243
91 Clocks & Watches & Parts Thereof 96.079.817
92 Musical Instruments, Parts & Accessories 30.020.221
94
Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated 
Signs, Nameplates & The Like, Prefabricated Buildings 990.514.319
95  Toys, Games & Sports Equip, Parts & Acces. 369.550.686
96 Miscellaneous Manufactured Articles 163.674.241
Source: UN Comtrade, 2015
Pag.  177
Table D.6.1 Finland Export Data 2015 by HS Category 
Finland Top 10 HS - 
Export HS description Trade Value (US$) 2015
28-38 Chemicals & Allied Industries 1.127.514.058
41-43 Raw Hides, Skins, Leather, & Furs 34.433.673
44-49 Wood & Wood Products 8.236.355.044
50-63 Textiles 368.473.432
64-67 Footwear / Headgear 117.598.048
68-71 Metals 656.972.372
84-85 Machinery / Electrical 5.175.400.498
90-97 Miscellaneous 3.244.270.981
Source: UN Comtrade, 2015
Pag.  178
Figure D.2 Finland Export Data 2015 by HS 
Category (table D.6.1)
17%
27%
3%
1%
2%
43%
6%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table D.6.2 Finland Export Data 2015 by HS Category (detail)
HS 
code HS description
Trade Value 
(US$) 2015
30 Pharmaceutical Products 942.293.452
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 62.393.176
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 120.476.131
37 Photographic Or Cinematographic Goods 2.351.299
42 Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of Gut 34.433.673
48 Paper & Paperboard, Articles Of Paper Pulp 8.061.651.259
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 140.270.112
57 Carpets & Other Textile Floor Coverings 10.846.082
60 Knitted Or Crocheted Fabrics 9.523.235
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 96.412.710
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 199.939.728
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 51.751.677
64  Footwear, Gaiters, & The Like 108.291.682
65 Headgear & Other Parts 8.627.423
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 678.943
69 Ceramic Products 74.803.518
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 582.168.854
8467 Tools for working in the hand, pneumatic etc, pts 87.351.450
8468 Machines, solder etc, gas surf temper machines, pt 407.789
8469 Typewriters & word processing machines 276
8470 Calculating & account machines, cash registers etc 1.924.015
85 Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound Recorders, Television Recorders 5.085.716.968
90 Optical, Photographic, Cinematographic, Measuring, Checking, Precision, Medical Or Surgical Instruments & Accessories 2.618.054.573
91 Clocks & Watches & Parts Thereof 44.156.406
92 Musical Instruments, Parts & Accessories 1.488.789
94 Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated Signs, Nameplates & The Like, Prefabricated Buildings 454.526.018
95  Toys, Games & Sports Equip, Parts & Acces. 109.445.474
96 Miscellaneous Manufactured Articles 16.599.721
Source: UN Comtrade, 2015
Pag.  179
APPENDIX “E” - DETAIL TRADE NORWAY
Table E.1 Norway Import Export 2015
Table E.2 Norway - Top 5 Import Countries (Value in USD)
Table E.3 Norway - Top 5 Export Countries (Value in USD)
Import (Trade in 
USD)
Export (Trade in 
USD)
Total (USD)
76.979.322.634 106.251.085.040 183.230.407.674
Source: UN Comtrade, 2015
Country Trade in USD 2015
Sweden 8.863.712.690
Germany 8.711.615.499
China 8.019.352.303
United	Kingdom 4.942.683.167
USA 4.843.748.237
Source: UN Comtrade, 2015
Country Trade in USD 2015
United	Kingdom 23.157.203.189
Germany 18.680.629.157
Netherlands 10.531.232.767
France 6.922.624.963
Sweden 6.321.703.951
Source: UN Comtrade, 2015
Pag.  180
Table E.4 Norway Import/Export 2015 Neighbours Countries
Table E.5.1 Norway Import Data 2015 by HS Category
Country Trade in USD 2015 
Denmark 8.313.278.320
Import 4.414.250.424
Export 3.899.027.896
Finland 2.874.673.563
Import 1.730.863.844
Export 1.143.809.719
Sweden 15.185.416.641
Import 8.863.712.690
Export 6.321.703.951
Source: UN Comtrade, 2015
HS code HS description Total value USD
28-38 Chemicals & Allied Industries 2.879.054.102
41-43 Raw Hides, Skins, Leather, & Furs 275.791.578
44-49 Wood & Wood Products 1.413.451.958
50-63 Textiles 2.707.999.190
64-67 Footwear / Headgear 709.933.125
68-71 Metals 558.381.408
84-85 Machinery / Electrical 7.008.866.893
90-97 Miscellaneous 6.611.223.602
Source: UN Comtrade, 2015
Pag.  181
Pag.  182
Figure E.1 Norway Import Data 2015 by HS 
Category (value in USD) (table E.5)
30%
32%
3%
3%
12%
6%
1%
13%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table E.5.2 Norway Import Data 2015 by HS Category (detail) 
HS 
code HS description
Trade Value (US$) 
2015
30 Pharmaceutical Products 1.824.053.858
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 611.017.071
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 412.677.994
37 Photographic Or Cinematographic Goods 31.305.179
42 Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of Gut 275.791.578
48 Paper & Paperboard, Articles Of Paper Pulp 926.186.062
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 487.265.896
57 Carpets & Other Textile Floor Coverings 92.353.167
60 Knitted Or Crocheted Fabrics 16.757.504
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 1.074.764.947
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 1.162.695.160
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 361.428.412
64  Footwear, Gaiters, & The Like 632.461.103
65 Headgear & Other Parts 66.917.536
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 10.554.486
69 Ceramic Products 287.942.038
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 270.439.370
8467 Tools for working in the hand, pneumatic etc, pts 183.857.067
8468 Machines, solder etc, gas surf temper machines, pt 7.482.334
8469 Typewriters & word processing machines 209.881
8470 Calculating & account machines, cash registers etc 19.115.124
85
Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound 
Recorders, Television Recorders
6.798.202.487
90
Optical, Photographic, Cinematographic, Measuring, Checking, Precision, Medical 
Or Surgical Instruments & Accessories 2.723.529.291
91 Clocks & Watches & Parts Thereof 94.742.685
92 Musical Instruments, Parts & Accessories 48.806.291
94
Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated Signs, 
Nameplates & The Like, Prefabricated Buildings 2.891.703.799
95  Toys, Games & Sports Equip, Parts & Acces. 596.281.966
96 Miscellaneous Manufactured Articles 256.159.570
Source: UN Comtrade, 2015
Pag.  183
Table E.6.1 Norway Export Data 2015 by HS Category
Finland Top 10 HS - 
Export HS description Trade Value (US$) 2015
28-38 Chemicals & Allied Industries 834.793.149
41-43 Raw Hides, Skins, Leather, & Furs 13.642.689
44-49 Wood & Wood Products 507.833.302
50-63 Textiles 123.968.088
64-67 Footwear / Headgear 23.160.046
68-71 Metals 501.144.176
84-85 Machinery / Electrical 2.967.785.766
90-97 Miscellaneous 2.721.165.950
Source: UN Comtrade, 2015
Pag.  184
Figure E.2 Norway Export Data 2015 by HS category 
(value in USD) (table E.6.1)
35%
39%
7%
2%
7%
11%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table E.6.2 Norway Export Data 2015 by HS Category (detail)
HS 
code HS description
Trade Value 
(US$) 2015
30 Pharmaceutical Products 716.142.182
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 42.295.041
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 76.054.631
37 Photographic Or Cinematographic Goods 301.295
42 Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of Gut 13.642.689
48 Paper & Paperboard, Articles Of Paper Pulp 427.131.776
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 67.058.837
57 Carpets & Other Textile Floor Coverings 957.691
60 Knitted Or Crocheted Fabrics 989.953
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 54.328.755
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 25.610.063
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 42.081.626
64  Footwear, Gaiters, & The Like 17.276.160
65 Headgear & Other Parts 5.327.114
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 556.772
69 Ceramic Products 20.582.571
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 480.561.605
8467 Tools for working in the hand, pneumatic etc, pts 48.151.005
8468 Machines, solder etc, gas surf temper machines, pt 3.406.896
8469 Typewriters & word processing machines 34.892
8470 Calculating & account machines, cash registers etc 1.329.001
85 Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound Recorders, Television Recorders 2.914.863.972
90
Optical, Photographic, Cinematographic, Measuring, Checking, Precision, 
Medical Or Surgical Instruments & Accessories 2.138.049.309
91 Clocks & Watches & Parts Thereof 12.686.663
92 Musical Instruments, Parts & Accessories 2.119.544
94 Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated Signs, Nameplates & The Like, Prefabricated Buildings 509.089.879
95  Toys, Games & Sports Equip, Parts & Acces. 55.628.641
96 Miscellaneous Manufactured Articles 3.591.914
Source: UN Comtrade, 2015
Pag.  185
APPENDIX “F” - DETAIL TRADE SWEDEN
Table F.1 Sweden Import/Export 2015
Table F.2 Sweden - Top 5 Import Countries (Value in USD)
Table F.3 Sweden - Top 5 Export Countries (Value in USD)
Import (USD) Export (USD) Total (USD)
137.986.741.780 140.089.772.744 278.076.514.524
Source: UN Comtrade, 2015
Country Trade in USD 2015
Germany 24.773.079.351
Netherlands 11.421.002.899
Norway 11.323.719.790
Denmark 10.618.591.078
United	Kingdom 7.614.114.734
Source: UN Comtrade, 2015
Country Trade in USD 2015
Norway 14.108.114.814
Germany 13.982.231.920
USA 10.160.876.437
United	Kingdom 9.818.620.833
Denmark 9.509.120.496
Source: UN Comtrade, 2015
Pag.  186
Table F.4 Sweden Import/Export 2015 Neighbours Countries
Table F.5.1 Sweden Import Data 2015 by HS Category (value in USD)
Country Trade in USD 2015 
Denmark 20.127.711.574
Import 10.618.591.078
Export 9.509.120.496
Norway 25.431.834.604
Import 11.323.719.790
Export 14.108.114.814
Finland 15.629.212.928
Import 6.362.885.839
Export 9.266.327.089
Source: UN Comtrade, 2015
HS code HS description Total value USD
28-38 Chemicals & Allied Industries 5.345.119.519
41-43 Raw Hides, Skins, Leather, & Furs 480.539.116
44-49 Wood & Wood Products 1.820.695.233
50-63 Textiles 4.612.020.740
64-67 Footwear / Headgear 1.019.245.504
68-71 Metals 609.609.362
84-85 Machinery / Electrical 17.613.259.480
90-97 Miscellaneous 8.054.959.383
Source: UN Comtrade, 2015
Pag.  187
Pag.  188
Figure F.1 Sweden Import Data 2015 by HS Category 
(value in USD) (table F.5.1)
20%
45% 2%
3%
12%
5%
1%
14%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table F.5.2 Sweden Import Data 2015 by HS category (value in USD) (detail) 
HS 
code HS description
Trade Value (US
$) 2015
30 Pharmaceutical Products 3.843.033.416
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 789.767.066
34
Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental 
Waxes 660.676.544
37 Photographic Or Cinematographic Goods 51.642.493
42
Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, 
Articles Of Gut 480.539.116
48 Paper & Paperboard, Articles Of Paper Pulp 1.443.950.489
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 376.744.744
57 Carpets & Other Textile Floor Coverings 195.598.980
60 Knitted Or Crocheted Fabrics 26.440.489
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 1.822.876.958
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 2.022.466.715
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 544.637.598
64  Footwear, Gaiters, & The Like 886.426.130
65 Headgear & Other Parts 113.326.493
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 19.492.881
69 Ceramic Products 360.551.959
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 249.057.403
8467 Tools for working in the hand, pneumatic etc, pts 350.672.777
8468 Machines, solder etc, gas surf temper machines, pt 6.888.203
8469 Typewriters & word processing machines 2.316.897
8470 Calculating & account machines, cash registers etc 35.708.314
85
Electrical Machinery & Equip. & Parts, Telecommunications Equip., 
Sound Recorders, Television Recorders 17.217.673.289
90
Optical, Photographic, Cinematographic, Measuring, Checking, Precision, 
Medical Or Surgical Instruments & Accessories 3.474.826.093
91 Clocks & Watches & Parts Thereof 230.476.815
92 Musical Instruments, Parts & Accessories 49.025.609
94
Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, 
Illuminated Signs, Nameplates & The Like, Prefabricated Buildings 2.959.860.783
95  Toys, Games & Sports Equip, Parts & Acces. 936.579.715
96 Miscellaneous Manufactured Articles 404.190.368
Source: UN Comtrade, 2015
Pag.  189
Table F.6.1 Sweden Export Data 2015 by HS category (value in USD)
Finland Top 10 HS - 
Export
HS description Trade Value (US$) 2015
28-38 Chemicals & Allied Industries 8.443.048.244
41-43 Raw Hides, Skins, Leather, & Furs 211.428.561
44-49 Wood & Wood Products 8.988.436.856
50-63 Textiles 2.066.164.806
64-67 Footwear / Headgear 348.046.409
68-71 Metals 1.225.121.467
84-85 Machinery / Electrical 15.895.580.086
90-97 Miscellaneous 7.742.468.820
Source: UN Comtrade, 2015
Pag.  190
Figure F.2 Sweden Export Data 2015 by HS category 
(value in USD) (table F.6.1)
17%
35%
3%
1%
5%
20%
19%
Chemicals & Allied Industries Raw Hides, Skins, Leather, & Furs
Wood & Wood Products Textiles
Footwear / Headgear Metals 
Machinery / Electrical Miscellaneous 
Table F.6.2 Sweden Export Data 2015 by HS category (value in USD) detail
HS 
code HS description
Trade Value 
(US$) 2015
30 Pharmaceutical Products 7.341.552.552
33 Oils & Resinoids, Perfumery, Cosmetic Or Toilet Preparations 521.151.621
34 Soaps, Waxes, Scouring Products, Candles, Modeling Pastes, Dental Waxes 561.617.051
37 Photographic Or Cinematographic Goods 18.727.020
42
Articles Of Leather, Saddlery & Harness, Travel Goods, Handbags, Articles Of 
Gut 211.428.561
48 Paper & Paperboard, Articles Of Paper Pulp 8.410.748.031
49 Printed Books, Newspapers, Pictures, Manuscripts, Typescripts & Plans 366.260.264
57 Carpets & Other Textile Floor Coverings 96.041.887
60 Knitted Or Crocheted Fabrics 49.880.173
61 Articles Of Apparel & Clothing Accessories-Knitted Or Crocheted 684.559.120
62 Articles Of Apparel & Clothing Accessories-Not Knitted Or Crocheted 980.600.708
63 Made-Up Textile Articles Nesoi, Needlecraft Sets, Worn Clothing, Rags 255.082.918
64  Footwear, Gaiters, & The Like 282.169.414
65 Headgear & Other Parts 60.286.498
66 Umbrellas, Sun Umbrellas, Walking-Sticks, Whips, Riding-Crops & Parts 5.590.497
69 Ceramic Products 146.813.665
71 Pearls, Stones, Prec. Metals, Imitation Jewelry, Coins 1.078.307.802
8467 Tools for working in the hand, pneumatic etc, pts 680.384.540
8468 Machines, solder etc, gas surf temper machines, pt 4.995.619
8469 Typewriters & word processing machines 318.549
8470 Calculating & account machines, cash registers etc 10.921.624
85
Electrical Machinery & Equip. & Parts, Telecommunications Equip., Sound 
Recorders, Television Recorders 15.198.959.754
90
Optical, Photographic, Cinematographic, Measuring, Checking, Precision, 
Medical Or Surgical Instruments & Accessories 3.875.930.990
91 Clocks & Watches & Parts Thereof 180.334.587
92 Musical Instruments, Parts & Accessories 51.424.293
94
Furniture, Bedding, Cushions, Lamps & Lighting Fittings Nesoi, Illuminated 
Signs, Nameplates & The Like, Prefabricated Buildings 2.593.282.517
95  Toys, Games & Sports Equip, Parts & Acces. 429.658.246
96 Miscellaneous Manufactured Articles 611.838.187
Source: UN Comtrade, 2015
Pag.  191
APPENDIX “G” - PORTS CHARACTERISTICS 
Table G.1 shows the port’s characteristics by categories. The source is the National 
Geospatial Intelligence Agency. The macro categories are available at the following link 
(http://msi.nga.mil/NGAPortal/MSI.portal). The table wasn’t used in our analysis because is 
not descriptive and reliable; exact measures are not provided; in opposite, it provides a 
general overview about the four ports. Each single port has two column; the first one (with 
letters) is the macro category (classified by msi.nga.mil) and the second is the relative 
conversion (e.g. harbour size 7.9-9.1 meters). 
Table G.1 Ports’ Characteristics a General Overview 
Table G.1 Oslo Malmo Copenhagen Stockholm Gothenburg 
Harbor Size L
7.9-9.1 
meters
L
7.9-9.1 
meters
L
7.9-9.1 
meters
L
7.9-9.1 
meters
L
7.9-9.1 
meters
Harbor Type CN
Coastal 
natural 
CB
Coastal 
Breakwa
ter
CB
Coastal 
Breakwater
CB
Coastal 
Breakwat
er
RT
River Tide 
Gate 
Shelter 
Afforded 
G Good G Good E Excellent G Good G Good
Entrance 
Restriction
s Tide N N N N N
Swell N N N N N
Ice N Y Y
Other Y Y L 7.9-9.1 
meters
Y Y
Overhead 
Limits 
Y Y Y Y
Channel 
Depth 
J
11-12.2 
m
L
7.9-9.1 
meters
L
7.9-9.1 
meters
K
9.4-10.7 
meters
L
7.9-9.1 
meters
Anchorage 
Depth 
E
17.1-18
.2 
meters
K
9.4-10.7 
meters
F
15.5 - 
16.8 
meters
A
23.2 - 
Over 
(meters)
Cargo Pier 
Depth 
N 4.9 - 
6.1 
meters
N
4.9 - 6.1 
meters
M
6.4 - 7.6 
meters
M
6.4 - 7.6 
meters
N
4.9 - 6.1 
meters
Maximum 
Vessel Size 
L
OVER 
500' 
LENGT
H
M
UP TO 
500' 
LENGTH
L
OVER 500' 
LENGTH
M
UP TO 
500' 
LENGTH
L
OVER 
500' 
LENGTH
Good 
Holding 
Ground 
Y N Y Y
Turning 
Area
Y Y Y
First Port of 
Entry 
Y Y Y Y Y
Pilotage 
Compulsory Y Y Y Y
Pag.  192
Available Y Y Y Y Y
Tugs 
Salvage 
Y Y
Tugs Assist Y Y Y Y Y
Air Y Y Y Y Y
Rail Y Y Y Y Y
Load/
OffloadWharves Y Y Y Y Y
Anchor Y Y Y Y
Ice Moor
Garbage 
Disposal 
Y Y Y Y Y
Dirty Ballast Y Y Y Y Y
Cranes 
Fixed Y Y Y Y Y
Mobile Y Y Y Y Y
Floating Y Y Y
Lifts
200 Tons + Y Y Y Y
50-200 Tons Y Y Y Y Y
25-49 Tons Y Y Y Y
0-24 Tons Y Y Y
Services 
Longshore Y Y Y Y
Steam Y Y
Repair A Major A Major A Major A Major 
Dry dock S Small L Large M Medium
Railway L Large L Large L Large M Medium L Large
Oslo Malmo Copenhagen Stockholm Gothenburg Table G.1 
Pag.  193
Table G.2 Ports’ Characteristics Details 
Table G.2 Malmo Copenhagen Oslo Stockholm Gothenburg 
Port details
Port Number (1) PO3225 PO1422 PO2303 PO2626 P2582
UNLOCODE SEMMA DKCPH NOOSL SESTO SEGOT 
Latitude 55° 37' N 55° 42' N 59° 54' N 59° 20' N 57° 41' N 
Latitude 
decimals 55.616667 55.700000 59.900000 59.333333 57.683333
Longitude 12° 59' E 12° 38' E 10° 44' E 18° 3' E 11° 51' E 
Longitude 
decimals 12.983333 12.633333 10.733333 18.050000 11.850000
Max Draught 12.5 11.5 11 11 19.05 
Max LOA 260 NA NA 295 350
Max Offshore 
BCM NA NA NA NA NA
Max Beam 45 NA NA 32.3 NA
MAX DWT NA NA NA NA 225.000
Port Facilities 
Container 
Facilities Y Y Y Y Y
RoRo Facilities Y Y Y Y Y
Port Description
Location
Malmo is located on the southern tip of Sweden at the 
entrance to the Baltic Sea, approx 14nm ESE of 
Copenhagen. 
Copenhagen is located on the E coast of Sjaelland 
and the harbour is formed by a branch of the Sound 
that runs between the islands of Amager and 
Sjaelland.
Oslo is situated 
in the heart of S 
Norway and 
forms a natural 
junction for sea 
and land 
transport.
Stockholm is 
situated on the E 
coast of 
Sweden.
Gothenburg is 
situated on the 
W coast of 
Sweden
Load line zone 
Summer Zone for ships over 100m 
in length and Winter Zone for ships 
of 100m or less in length. Winter 
Nov 1 to Mar 31, Summer Apr 1 to 
Oct 31. 
Summer Zone 
for ships over 
100m in length 
and Winter 
Zone for ships 
of 100m or less 
in length. Winter 
Nov 1 to Mar 
31, Summer Apr 
1 to Oct 30. 
North Atlantic 
Winter Seasonal 
Zone II, Winter 
Nov 1 to Mar 31, 
Summer Apr 1 to 
Oct 31.
Summer Zone 
for ships over 
100m in length 
and Winter Zone 
for ships of 
100m or less. 
Winter Nov 1 to 
Mar 31, Summer 
Apr 1 to Oct 31. 
North Atlantic 
Winter Seasonal 
Zone II, Winter 
Nov 1 to Mar 31, 
Summer Apr 1 to 
Oct 31.
Number of 
vessels 8000 Approx 9,020 - -
Pag.  194
Tons of cargo 14,400,000t cargo 
5,820,000t of 
cargo  
Approx 
8,500,000 of 
cargo, 
38,200,000t of 
cargo 
TEUs 141,000TEU 202,500TEU 27,840TEU 820,000TEU 
MAX size LOA 260m, beam 45m, draught 
12.5m 
Provestenen 
Harbour: 
Draught 11.5m. 
Max draught in 
Drobak Passage 
is 12.0m, 
alongside 11.0m.
Largest vessels 
handled: 
Passenger and 
dry cargo 
vessels: LOA 
295m, beam 
32.3m, draught 
11.0m.
Hammerby Lock: 
Length 115m, 
width 17.4m, 
depth 6.5m. 
Vessels 
transiting Lake 
Maleran max 
airdraught 
25.2m. 
LOA 350m, 
tanker draught 
19.05m (18.6m if 
water level low), 
container 
draught 11.5m, 
225,000DWT. 
Max airdraught 
in Inner harbour 
45m. 
Gota River: LOA 
89m, beam 
13.4m, draught 
4.7m, with 
special 
permission up to 
5.4m. Airdraught 
27.0m. 
Bohus: LOA 
135m, beam 
16.5m. 
Trollhattan 
Kanal: LOA 
125m and beam 
16.5m. 
Navigation 
Charts BA 3194. Admiralty Pilot NP18, 
NP286(2).
BA 902, 903, 
3194, 790, 
2595. Danish 
133 and 134. 
Admiralty Pilot 
NP18, 
NP286(2).
BA 3154, 3159, 
3712. Admiralty 
Pilot NP56, 
NP286(2).
BA 3114. 
Admiralty Pilot 
NP19, 
NP286(2).
BA 858, 857. 
Admiralty Pilot 
NP18, NP286(2).
Dock density 1010 1005 1025. 1005. Average 1013.
Weather 
Prevailing winds: Malmo: NW'ly-
SE'ly. Although the harbour is 
practically never closed by ice, drift 
ice can be encountered in the outer 
part of the dredged channels even 
during normal winters. 
Prevailing 
winds: W'ly. 
Prevailing winds: 
N'ly winter; S'ly 
summer. 
Prevailing winds: 
W-SW’ly.
Ice: Navigation 
is maintained 
throughout the 
year with the 
assistance of 
icebreakers. 
However, branch 
passages are 
often closed 
during severe 
periods of icing. 
Prevailing winds: 
SW to NW'ly. 
Ice: The harbour 
is generally ice 
free, although it 
may have ice in 
the period 
January to 
March in hard 
winters.
Malmo Copenhagen Oslo Stockholm Gothenburg Table G.2
Pag.  195
G.1 Port description
G.1.1 General Overview 
Port of Malmo : Malmo's new Northern Harbour opened in 2011. Three new terminals 
were opened increasing freight capacity by five times. (Sea-web, 2016)
Port of Copenhagen: The port extends to 1,108ha with a land area of 413ha and a total 
quayage length of 39,651m. 3 sections: The North Harbour, The Inner Harbour and The 
Provestenen Harbour; Free Port is located in the North Harbour. (Sea-web, 2016)
Port of Oslo: The port is a well sheltered major harbour built around the mainland coast of 
the bay in the NE corner of Oslofjorden. The harbour is divided into Eastern and Western 
harbours by a group of islands lying in the entrance to the bay and joined by channels. 
The port serves a considerable industrial and commercial centre, handling a large part of 
the country's foreign trade, both imports and exports. There are extensive Ro-Ro, ferry and 
cruise facilities including two floating Ro-Ro ramps with three daily ferry arrivals from 
Denmark and Germany. It has excellent road and rail connections with the rest of Norway 
and is equipped to handle most types of cargoes including oil, salt, cement, stone, timber, 
newsprint, vehicles, grain and animal feeds. (Sea-web, 2016)
Port of Stockholm: The quays, which includes 10 cruise berths, have a total length of 
16km extending approx 10km from W to E. The area of the harbour is approx 1,750ha. 
The waterway Hammarbyleden, connecting Lake Malaren with the sea, has a length of 
6,550m from Danviksbron to Reimersholme with a depth of 6.1m. There is a lock 
connection, Hammarby Lock, max vessel dimensions LOA 110m, beam 15m and draught 
5.6m at MW. (Sea-web, 2016) 
Tugs 3
Compulsory for 
vessels over 
100m in length, 
passing through 
bridges. 
Tugs are 
available by 
arrangement 
with vessel's 
agent prior to 
arrival/departure. 
The largest tugs 
are equipped for 
fire fighting 
2 ("Tug" 
2,400hp, 30 
board pull; ”Ted" 
1,400hp,  15 
bollard pull )
Tankers of 
30,000DWT or 
more are 
required to use 
at least 2 tugs 
when berthing or 
leaving 
Torshamnen 
crude oil jetty 
and 1 tug on 
arrival if over 
5,000DWT 
(Berth Nos 800 
and 801). This 
rule applies to 
both laden and 
empty vessels.
Note 1) Source: Sea-web 2016
Malmo Copenhagen Oslo Stockholm Gothenburg Table G.2
Pag.  196
Port of Gothenburg: The port is the largest port in the Nordic countries 
The port is also the central Nordic port for liner shipping with about 30% of its general 
cargo imports and exports being transit cargo to or from other Nordic countries. 
The port is also the central Nordic port for liner shipping with about 30% of its general 
cargo imports and exports being transit cargo to or from other Nordic countries. 
Direct calling deep sea container or Ro-Ro liners connect Gothenburg to all continents with 
their base at the Scandia Terminal. Ro-Ro ferry liner operations to Continental Europe and 
UK calls at the Alvsborg Terminal. The total complex of a unit load centre of 2,000,000m2 
with 2,500m of quay length and 11 container cranes including 2 post Panamax and 3 
super post Panamax with a lifting capacity of 103t each. In addition, the port also has 
cruise liner facilities with berths dedicated to cruise vessels. 
Traffic can also navigate the Gota River and via locks to Lake Vanern where channel depth 
is 6.1m. (Sea-web, 2016) 
Pag.  197
Table G.3 Berth Length - Depth Analysis 
Malmo Copenhagen Oslo Stockholm Gothenburg 
Berth 
length
Depth 
(m)
Berth 
length
Depth 
(m)
Berth 
length
Depth 
(m)
Berth 
length
Depth 
(m)
Berth 
length
Depth 
(m)
175 7,2 27 9 463 8,9 200 7,5 203 9,8
180 7,2 173 9 165 7,2 200 7,5 47 9,8
120 9,1 200 9 304 12 180 8,5 225 9,8
185 8,1 210 7 287 9,45 298 8,25 200 11,0
500 9,2 72 9,5 367 8 149 11,0
325 10,0 72 6 110 7,5 232 11,0
190 9,0 98 6 222 8 265 11,0
245 8,5 130 9,5 240 8,75 210 11,0
245 8,5 33 9,5 190 9,5
245 8,5 105 9,5 135 14,2
150 9,2 100 9,5 95 14,2
150 9,2 100 9,5 190 14,2
112 9,5 190 14,2
100 9,5 190 14,2
100 9,5 190 14,2
98 9,5 190 14,2
100 6 570 14,2
150 6 135 14,2
100 6 170 14,2
100 6 60 9
115 6,7 138 9
100 6,3 137 9
147 6 140 9
Total 
length 
2710 2542 1219 1817 4251
Weighted 
Mean 
8,75 7,91 9,57 8,05 12,12
Port of 
Copenhange-
Malmo Weighted 
average
8,34
Pag.  198
The total weighted mean identified, taking into consideration all berth length and depth is 
65,90. 
Pag.  199
APPENDIX “H” - CONTAINERSHIPS BY PORT 
Table H.0 Gross Tonnage by Country and by Port
Table H.1 Number of Containerships in Specified Ports (inwards) (2014)
Note: (1) Eurostat 2014
2014 % by country
Denmark 23.595 -
Københavns Havn 3.432 14,55
Norway 21.933 -
Oslo 3.283 14,97
Sweden 37.776 -
Malmö 488 1,29
Stockholm 1.725 4,57
Göteborg 21.373 56,58
Note: 1) Eurostat 
The “dot” :.” is used for 
thousand and the “comma” “,” 
for decimals.  
Flow 2014 / Vessel Type (GT) (1) Port of Oslo 
Port of 
Copenhagen-
Malmo
Port of 
Stockholm 
Port of 
Gothenburg
From 2 000 to 2 999 gross tonnage 25 5 0 0
From 3 000 to 3 999 gross tonnage 0 3 1 12
From 5 000 to 5 999 gross tonnage 1 2 24 42
From 6 000 to 6 999 gross tonnage 1 63 16 47
From 7 000 to 7 999 gross tonnage 111 40 21 245
From 8 000 to 8 999 gross tonnage 101 50 5 32
From 9 000 to 9 999 gross tonnage 81 146 7 162
From 10 000 to 19 999 gross tonnage 65 46 91 119
From 20 000 to 29 999 gross tonnage 1 34 0 20
From 40 000 to 49 999 gross tonnage 0 0 0 4
From 50 000 to 79 999 gross tonnage 0 0 0 4
From 80 000 to 99 999 gross tonnage 0 0 0 41
From 100 000 to 149 999 gross tonnage 0 0 0 6
From 150 000 to 199 999 gross tonnage 0 0 0 53
Total 386 389 165 787
Pag.  200
Table H.2 Containerships by GT Calculus
 
The total number of containerships is 1.727 (in 2014) for the selected ports. The port of 
Oslo received 386 calls (equal 22,35 per cent of total), the Port of Copenhagen-Malmo 
received 389 calls (equal to 22,52 per cent of total), the Port of Stockholm received 165 
calls (equal to 9,55 per cent), and finally the PoG received 787 calls (equal 45,57 per 
cent). The recent data (2016) show a an increase number of calls for the segment 100.000 
to 199.999 GT (PoG source).
In the column “A” - the table H.2 - are reported the total percentages, but in the table H.5 
are reported the specific data by port and category.
Table H.3, shows the different performance by port and by category. The percentage was 
calculated by the single category in the table H.1 (by port) divided by the total calls by port. 
For example the value for Oslo was calculated by (category 2.000 - 2.9999): 
[(25)/(386)*100] = 6,48 % (result in table H.3.)
Total number of 
containerships  calls 1727
Percentge of containerships 
by port (on total no.) (column 
A)
Average no. 
containerships 30,84 Port of Oslo 
22,35%
Port of Copenhagen-Malmo 22,52%
Port of Stockholm 9,55%
Port of Gothenburg 45,57%
Pag.  201
The data are highlight the ships calls main segment by GT. 
Table H.3 Port’s Calls Performance 
Note: (1) Eurostat 2014
Table H.4, shows the different performance by port and by (single) category. 
The percentage, by category and by port was calculated taking into consideration the the 
single value (e.g. 25, Port of Oslo, category 2000-2999) and divided by the total number of 
calls for the specified category. 
For example the value of 83,33 per cent (Port of Oslo) was calculated as below: 
= [(25/30 total by category)*100] 
 
The PoG receive a larger number of calls in different categories (total 10 out of 14). 
Instead the Port of Oslo receive calls (25) for the segment 2.000-2.999 (83,33 per cent), 
and 101 (segment 8.000-8.999) equal to 53,72 per cent. In the other side the Port of 
Copenhagen-Malmo (CMP) receive 63 calls for the segment 6.000-6.999, equal to 49,61 
per cent of the total segment; CMP perform better in the segment 20.000-29.999 with 34 
calls, equal to 61,82 per cent of the total segment. 
Performance port by containership/
by total port Port of Oslo 
Port of 
Copenhagen-
Malmo
Port of 
Stockholm 
Port of 
Gothenburg
From 2 000 to 2 999 gross tonnage 6,48% 1,29% 0,0% 0,0%
From 3 000 to 3 999 gross tonnage 0,00% 0,77% 0,6% 1,5%
From 5 000 to 5 999 gross tonnage 0,26% 0,51% 14,5% 5,3%
From 6 000 to 6 999 gross tonnage 0,26% 16,20% 9,7% 6,0%
From 7 000 to 7 999 gross tonnage 28,76% 10,28% 12,7% 31,1%
From 8 000 to 8 999 gross tonnage 26,17% 12,85% 3,0% 4,1%
From 9 000 to 9 999 gross tonnage 20,98% 37,53% 4,2% 20,6%
From 10 000 to 19 999 gross tonnage 16,84% 11,83% 55,2% 15,1%
From 20 000 to 29 999 gross tonnage 0,26% 8,74% 0,0% 2,5%
From 40 000 to 49 999 gross tonnage 0,00% 0,00% 0,0% 0,5%
From 50 000 to 79 999 gross tonnage 0,00% 0,00% 0,0% 0,5%
From 80 000 to 99 999 gross tonnage 0,00% 0,00% 0,0% 5,2%
From 100 000 to 149 999 gross 
tonnage 0,00% 0,00% 0,0% 0,8%
From 150 000 to 199 999 gross 
tonnage 0,00% 0,00% 0,0% 6,7%
Total 100,00% 100,00% 100,0% 100,0%
Pag.  202
Table H.4 Port's performance by GT category 
Note: (1) Eurostat 2014
Table H.5, shows the different performance by port and by category. The percentage was 
calculated by the single category in the table H.5 (by port) divided by the total calls in table 
H.2. For example the value for Oslo was calculated for the category 2.000 - 2.9999: 
[(25 calls) / (1727 total calls)*100] = 1,45 % (results in table H.5). 
Flow 2014 / Vessel Type (GT) (1) 
by category Port of Oslo 
Port of 
Copenhagen-
Malmo
Port of 
Stockholm Port of Gothenburg
Total 
by 
categor
y
From 2 000 to 2 999 gross tonnage 25 83,33% 5 16,67% 0 0,00% 0 0,00% 30
From 3 000 to 3 999 gross tonnage 0 0,00% 3 18,75% 1 6,25% 12 75,00% 16
From 5 000 to 5 999 gross tonnage 1 1,45% 2 2,90% 24 34,78% 42 60,87% 69
From 6 000 to 6 999 gross tonnage 1 0,79% 63 49,61% 16 12,60% 47 37,01% 127
From 7 000 to 7 999 gross tonnage 111 26,62% 40 9,59% 21 5,04% 245 58,75% 417
From 8 000 to 8 999 gross tonnage 101 53,72% 50 26,60% 5 2,66% 32 17,02% 188
From 9 000 to 9 999 gross tonnage 81 20,45% 146 36,87% 7 1,77% 162 40,91% 396
From 10 000 to 19 999 gross 
tonnage 65 20,25% 46 14,33% 91 28,35% 119 37,07% 321
From 20 000 to 29 999 gross 
tonnage 1 1,82% 34 61,82% 0 0,00% 20 36,36% 55
From 40 000 to 49 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 4 100,00% 4
From 50 000 to 79 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 4 100,00% 4
From 80 000 to 99 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 41 100,00% 41
From 100 000 to 149 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 6 100,00% 6
From 150 000 to 199 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 53 100,00% 53
Total 386 389 165 787 863,00% 1727
Pag.  203
Table H.5 Total port performance - calls by GT category 
Table H.6, data 2015, shows the performances by port with the total TEUs flow 
(1.245.210). The PoG 
Table H.6: Port TEUs flows and performance on total
Flow 2014 / Vessel Type (GT) (1)
Port of Oslo 
Port of 
Copenhagen-
Malmo
Port of 
Stockholm Port of Gothenburg
From 2 000 to 2 999 gross tonnage 25 1,45% 5 0,29% 0 0,00% 0 0,00%
From 3 000 to 3 999 gross tonnage 0 0,00% 3 0,17% 1 0,06% 12 0,69%
From 5 000 to 5 999 gross tonnage 1 0,06% 2 0,12% 24 1,39% 42 2,43%
From 6 000 to 6 999 gross tonnage 1 0,06% 63 3,65% 16 0,93% 47 2,72%
From 7 000 to 7 999 gross tonnage 111 6,43% 40 2,32% 21 1,22% 245 14,19%
From 8 000 to 8 999 gross tonnage 101 5,85% 50 2,90% 5 0,29% 32 1,85%
From 9 000 to 9 999 gross tonnage 81 4,69% 146 8,45% 7 0,41% 162 9,38%
From 10 000 to 19 999 gross 
tonnage 65 3,76% 46 2,66% 91 5,27% 119 6,89%
From 20 000 to 29 999 gross 
tonnage 1 0,06% 34 1,97% 0 0,00% 20 1,16%
From 40 000 to 49 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 4 0,23%
From 50 000 to 79 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 4 0,23%
From 80 000 to 99 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 41 2,37%
From 100 000 to 149 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 6 0,35%
From 150 000 to 199 999 gross 
tonnage 0 0,00% 0 0,00% 0 0,00% 53 3,07%
Total 386 22,35% 389 22,52% 165 9,55% 787 45,57%
Note: (1) Eurostat 2014
Port of 
Copenhagen-
Malmo(2-3) 
Port of 
Stockholm (1) 
Port of Oslo  (1) Gothenburg 
(1) 
Total 
(3)
TEUs Flow 145.000 51.000 212.579 836.631 1.245.210
Percentage (4) 11,64% 4,10% 17,07% 67,19% 100%
Source:
1) Maritime Insight 2015
2) Eurostat 2015
3) Author elaboration 
4) Author elaboration 
Pag.  204
The Liner Shipping Connectivity Index captures how well countries are connected to 
global shipping networks. It is computed by the United Nations Conference on Trade and 
Development (UNCTAD) based on five components of the maritime transport sector: 
number of ships, their container-carrying capacity, maximum vessel size, number of 
services, and number of companies that deploy container ships in a country's ports. For 
each component a country's value is divided by the maximum value of each component in 
2004, the five components are averaged for each country, and the average is divided by 
the maximum average for 2004 and multiplied by 100. The index generates a value of 100 
for the country with the highest average index in 2004. The underlying data come from 
Containerisation International Online.
Liner shipping bilateral connectivity index
The table presents the liner shipping bilateral connectivity index (LSBCI), which indicates a 
country pair's integration level into global liner shipping networks. The LSBCI is an 
extension of UNCTAD’s country-level Liner Shipping Connectivity Index (LSCI) and based 
on a proper bilateralization transformation.
Transport connectivity is a crucial determinant of bilateral exports. UNCTAD's Liner 
Shipping Bilateral Connectivity Index is meant to reflect specifically the liner shipping 
connectivity between pairs of countries. 
The current version of the LSBCI includes 5 components. For any pair of countries A and B 
represented in our sample, the LSBCI is based on: 
1) the number of transshipments required to get from country A to country B; 
2) the number of direct connections common to both country A and B; 
3) the geometric mean of the number of direct connections of country A and of country B; 
4) the level of competition on services that connect country A to country B; 
5) the size of the largest ships on the weakest route connecting country A to country B. 
The data are derived from Containerisation International Online and Lloyd’s List 
Intelligence.
 
In order to establish a unit free index, all components are normalized using the standard 
formula:
Normalized_Value = (Raw - Min(Raw)) / (Max(Raw) - Min(Raw)).
This formula rather than the Raw/Max(Raw) formula has been chosen essentially because 
of the existence of minimum values which differ from zero. If all minimum values for all 
components were zero both formulas would be equivalent and would generate identical 
normalized values. 
The LSBCI is computed by taking the simple average of the five normalized components. 
As a consequence, the LSBCI can only take values between 0 (minimum) and 1 
(maximum). As to the first component, we simply take its complement to unity that is 1-
Normalized_Value to respect the correspondence between higher values and stronger 
connectivity.
Pag.  205
APPENDIX “I” - VOYAGE COSTS 
Table I.1 Voyage Costs Shanghai - Copenhagen 
Pag.  206
Shanghai to 
Copenhagen via Suez-Gibraltar
via Cape of Good 
hope via Cape Horn 
Northern Sea 
Route (passing 
by: 70° 26' 47"N 
171° 39' 57"W
Costs
1 Fixed costs (Time Chartered) (USD) $60.000 $60.000 $60.000 $60.000
2 Average Fuel 
consumption per day 
(mt) at 20 knots  
190 190 190 190
3 IFO  0380 price USD/mt $233,00 $233,00 $233,00 $233,00
4 MGO price USD/mt $465,00 $465,00 $465,00 $465,00
Navigation data
5 (1) Distance  (nm) 11.371 14.761,00 18.051,00 7.705,00
6  (2) SECA (nm) 1.177 1.177 1.177 760,00
7 (3) Distance in open sea 10.194 13.584 16.874 6.945
8 (4) Days 23,7 30,80 37,61 16,10
Assumptions
9 total consumption (2*8) 4.503 5.852 7.146 3.059
10 Average nautical (5/8) 480 479 480 479
11 cost per day IFO0380 (2*3) $44.270,00 $44.270,00 $44.270,00 $44.270,00
12
Price per nautical 
mile IFO0380 
(11/10)
$92,27 $92,37 $92,24 $92,50
13 Cost per day MGO (2*4) $88.350,00 $88.350,00 $88.350,00 $88.350,00
14 Price per nautical mile MGO ( $184,14 $184,35 $184,08 $184,61
15 Total Fuel price IFO0380 (12*7) $940.597,54 $1.254.793,13 $1.556.430,15 $642.443,60
16 Total Fuel Price MGO (14*6) $216.736,82 $216.979,12 $216.663,17 $140.305,07
17 Total Fuel price route (15+16) $1.157.334,36 $1.471.772,25 $1.773.093,31 $782.748,67
18 Total voyage cost  (1*8) $1.422.000,00 $1.848.000,00 $2.256.600,00 $966.000,00
19 Chartered voyage cost $2.579.334,36 $3.319.772,25 $4.029.693,31 $1.748.748,67
Charges 
20 Port Charges (9,000 
containers, 
2tonnes/each), 
price in DKK, VAT 
excluded 
DKK3.780.000,00 DKK3.780.000,00 DKK3.780.000,00 DKK3.780.000,00
21 20 converted in 
USD 
(1 DKK = 0.150015 
USD); source: 
xe.com (10 May 
2016)
$567.057,07 $567.057,07 $567.057,07 $567.057,07
Total Cost $3.146.391,43 $3.886.829,32 $4.596.750,38 $2.315.805,74
Table I.2 Voyage Costs Shanghai - Oslo
Pag.  207
Shanghai to Oslo
via Suez-Gibraltar via Cape of Good hope via Cape Horn 
Northern Sea 
Route (passing by: 
70° 26' 47"N 171° 
39' 57"W
Costs
1 Fixed costs (Time Chartered) (USD) $60.000 $60.000 $60.000 $60.000
2 Average Fuel 
consumption per day 
(mt) at 20 knots  
190 190 190 190
3 IFO  0380 price USD/mt $233,00 $233,00 $233,00 $233,00
4 MGO price USD/mt $465,00 $465,00 $465,00 $465,00
Navigation data
5 (1) Distance  (nm) 11.177 14.508,00 17.798,00 7.420,00
6  (2) SECA (nm) 923 924 924 475,00
7 (3) Distance in open sea 10.254 13.584 16.874 6.945
8 (4) Days 23,16 30,23 37,08 15,50
Assumptions
9 total consumption (2*8) 4.400 5.744 7.045 2.945
10 Average nautical (5/8) 483 480 480 479
11 cost per day IFO0380 (2*3) $44.270,00 $44.270,00 $44.270,00 $44.270,00
12
Price per nautical 
mile IFO0380 
(11/10)
$91,73 $92,24 $92,23 $92,48
13 Cost per day MGO (2*4) $88.350,00 $88.350,00 $88.350,00 $88.350,00
14 Price per nautical mile MGO ( $183,07 $184,09 $184,07 $184,56
15 Total Fuel price IFO0380 (12*7) $940.624,18 $1.253.048,25 $1.556.309,93 $642.258,06
16 Total Fuel Price MGO (14*6) $168.974,65 $170.101,88 $170.077,57 $87.665,35
17 Total Fuel price route (15+16) $1.109.598,83 $1.423.150,14 $1.726.387,51 $729.923,41
18 Total voyage cost  (1*8) $1.389.600,00 $1.813.800,00 $2.224.800,00 $930.000,00
19 Chartered voyage cost $2.499.198,83 $3.236.950,14 $3.951.187,51 $1.659.923,41
Charges 
20 Port Charges 
(18,000 TEUs, NOK 
124/TEU)
NOK2.232.000 NOK2.232.000 NOK2.232.000 NOK2.232.000
21 20 converted in 
USD 
(1 NOK = 0.119762 
USD); source: 
xe.com (10 May 
2016)
$267.309,00 $267.309,00 $267.309,00 $267.309,00
Total Cost $2.766.507,83 $3.504.259,14 $4.218.496,51 $1.927.232,41
Table I.3 Voyage Costs Shanghai - Stockholm 
Pag.  208
Shanghai to 
Stockholm via Suez-Gibraltar via Cape of Good hope via Cape Horn 
Northern Sea 
Route (passing 
by: 70° 26' 47"N 
171° 39' 57"W
Costs
1 Fixed costs (Time Chartered) (USD) $60.000 $60.000 $60.000 $60.000
2 Average Fuel 
consumption per day 
(mt) at 20 knots  
190 190 190 190
3 IFO  0380 price USD/mt $233,00 $233,00 $233,00 $233,00
4 MGO price USD/mt $465,00 $465,00 $465,00 $465,00
Navigation data
5 (1) Distance  (nm) 11.725 15.115,00 18.405,00 8.059,00
6  (2) SECA (nm) 1.531 1.531 1.531 1.114,00
7 (3) Distance in open sea 10.194 13.584 16.874 6.945
8 (4) Days 24,43 31,49 38,34 16,80
Assumptions
9 total consumption (2*8) 4.642 5.983 7.285 3.192
10 Average nautical (5/8) 480 480 480 480
11 cost per day IFO0380 (2*3) $44.270,00 $44.270,00 $44.270,00 $44.270,00
12
Price per nautical 
mile IFO0380 
(11/10)
$92,24 $92,23 $92,22 $92,29
13 Cost per day MGO (2*4) $88.350,00 $88.350,00 $88.350,00 $88.350,00
14 Price per nautical mile MGO ( $184,08 $184,06 $184,04 $184,18
15 Total Fuel price IFO0380 (12*7) $940.296,39 $1.252.857,58 $1.556.122,76 $640.928,96
16 Total Fuel Price MGO (14*6) $281.833,34 $281.803,42 $281.772,13 $205.172,84
17 Total Fuel price route (15+16) $1.222.129,72 $1.534.660,99 $1.837.894,88 $846.101,80
18 Total voyage cost  (1*8) $1.465.800,00 $1.889.400,00 $2.300.400,00 $1.008.000,00
19 Chartered voyage cost $2.687.929,72 $3.424.060,99 $4.138.294,88 $1.854.101,80
Charges 
20 Port Charges (9,000 
containers, SEK 
425/unit) (VAT 
excluded)
SEK3.825.000 SEK3.825.000 SEK3.825.000 SEK3.825.000
21 20 converted in 
USD 
(1 SEK = 0.120195 
USD); source: 
xe.com (10 May 
2016)
$459.744,60 $459.744,60 $459.744,60 $459.744,60
Total Cost $3.147.674,32 $3.883.805,59 $4.598.039,48 $2.313.846,40
Table I.4 Voyage Costs Shanghai - Gothenburg 
Pag.  209
Shanghai to 
Gothenburg via Suez-
Gibraltar
via Cape of 
Good hope via Cape Horn 
Northern Sea 
Route (passing 
by: 70° 26' 47"N 
171° 39' 57"W
Costs
1 Fixed costs (Time Chartered) (USD) $60.000 $60.000 $60.000 $60.000
2 Average Fuel 
consumption per day 
(mt) at 20 knots  
190 190 190 190
3 IFO  0380 price USD/mt $233,00 $233,00 $233,00 $233,00
4 MGO price USD/mt $465,00 $465,00 $465,00 $465,00
Navigation data
5 Distance  (nm) 11.054 14.445,00 17.734,00 7.388,00
6 SECA (nm) 860 860 860 443,00
7 Distance in open sea 10.194 13.585 16.874 6.945
8 Days 23,03 30,09 36,95 15,40
Assumptions
9 total consumption (2*8) 4.376 5.717 7.021 2.926
10 Average nautical (5/8) 480 480 480 480
11 cost per day IFO0380 (2*3) $44.270,00 $44.270,00 $44.270,00 $44.270,00
12 Price per nautical mile IFO0380 (11/10) $92,23 $92,22 $92,24 $92,28
13 Cost per day MGO (2*4) $88.350,00 $88.350,00 $88.350,00 $88.350,00
14 Price per nautical mile MGO ( $184,07 $184,04 $184,08 $184,16
15 Total Fuel price IFO0380 (12*7) $940.218,15 $1.252.777,10 $1.556.450,47 $640.878,36
16 Total Fuel Price MGO (14*6) $158.299,48 $158.274,02 $158.311,60 $81.583,83
17 Total Fuel price route (15+16) $1.098.517,62 $1.411.051,13 $1.714.762,07 $722.462,19
18 Total voyage cost  (1*8) $1.381.800,00 $1.805.400,00 $2.217.000,00 $924.000,00
19 Chartered voyage cost $2.480.317,62 $3.216.451,13 $3.931.762,07 $1.646.462,19
Charges 
21 Port Charges 
(194,849GT)
SEK140.424,50 SEK140.424,50 SEK140.424,50 SEK140.424,50
22 20 converted in 
USD 
(1 SEK = 0.120195 
USD); source: 
xe.com (10 May 
2016)
$16.879,00 $16.879,00 $16.879,00 $16.879,00
Total Cost $2.497.196,62 $3.233.330,13 $3.948.641,07 $1.663.341,19
APPENDIX “L” - POPULATION DETAILS
Table L.1 Digital Users
Table L.2 Social Classes, Population And Median Income 
Denmark % Finland % Norway % Sweden %
Internet subscribers 9.055,1 22,23% 9.613,2 23,60% 7.267,3 17,84% 14.800,1 36,33%
Internet users 5.184,1 22,24% 4.842,3 20,78% 4.698,5 20,16% 8.581,3 36,82%
Mobile internet 
subscriptions
6.664,4 21,51% 7.805,7 25,20% 5.108,4 16,49% 11.398 36,80%
Mobile telephone 
subscriptions
7.249,6 21,56% 7.799,6 23,19% 6.063,3 18,03% 12.518,2 37,22%
personal computers (%) 92 - 90,8 - 96 - 94,3 -
Tablets (%) 50 - 41,7 - 37 - 35,5 -
smartphones (%) 77 - 68,4 - 74 - 74,9 -
Source: Euromonitor (2015)
Note: this table identify thousands with the “.” “dot”, and decimals with “comma “,”
Denmark Finland Norway Sweden 
Median Disposable Income per 
Household (USD) 47,324.5 47.426,1 64.001,9 51.236,8
Saving ratio (% of disposal income) 2,9 6,5 9,1 11,3
Social class A (‘000) 443,7 396,6 362,0 594,6
Social Class B (‘000) 479,8 472,5 417,3 792,8
Social class C (‘000) 914,3 984,1 947,9 3
Social Class D (‘000) 1.602,4 1.646,0 1.651,3 3.258,2
Social Class E (‘000) 1.403,5 1.179,0 1.099,0 1.763,6
Urban Consumer Expenditure 133,742.4 117,306.3 136,703.4 218,621.5
Population aged 0-14 938,6 910,2 977,0 1.814,9
Population Aged 15-64 3.682,3 3.434,1 3.546,1 6.249,8
Population aged 65+ 1.161,4 1.244,1 931,4 2.068,1
Urban popualtion 5.122,7 4.742,5 4.455,3 8.765,8
Total popualtion 5782,3 5588,4 5454,5 10.132,8
Source: Euromonitor (2015)
Note: this table identify thousands with the “.” “dot”, and decimals with “comma “,”
Pag.  210
Social Class A presents data referring to the number of individuals with a gross income 
over 200% of an average gross income of all individuals aged 15+.
Social Class B presents data referring to the number of individuals with a gross income 
between 150% and 200% of an average gross income of all individuals aged 15+.
Social Class C presents data referring to the number of individuals with a gross income 
between 100% and 150% of an average gross income of all individuals aged 15+.
Social Class D presents data referring to the number of individuals with a gross income 
between 50.0% and 100% of an average gross income of all individuals aged 15+.
Social Class E presents data referring to the number of individuals with a gross income 
less than 50.0% of an average gross income of all individuals aged 15+.
Table L.3 Retailing Analysis 
Table L.4 Sales by Sector
Note: this table identify thousands with “comma “,” , and decimals with “.” “dot”. 
Source: Euromonitor (2015)
retailing analysis
$USmn, constant 
prices, fixed 
exchange rate 
Denmark Finland Norway Sweden 
Retailing (2015) 42.766,7 38.965,6 52.924,9 71.847,6
Retailing forecast 
2020 44.410,9 40.948,8 56.195,2 77.756,5
Internet Retailing 
(2015) 5.401,4 3.894,8 4.657,7 5.475,7
Internet Retailing 
(forecast 2020) 7.297,4 4.649,8 6.275,0 7.645,3
Direct selling 2015 72,8 179,8 164,9 236,6
Direct selling 
(forecast 2020) 77,2 202,9 167,5 211,5
this table identify thousands with the “.” “dot”, and decimals with “comma “,”
Source: Euromonitor (2015)
$USmn, constant prices, fixed 
exchange rate 
Denmark Finland Norway Sweden 
Apparel and Footwear (2015) 5,142.9 NA 7,123.6 11,539.4
Apparel and Footwear (2020) 4,990.2 NA 7,377.0 12,052.6
Beauty and Personal Care (2015) 1,388.8 1,151.5 1,519.5 2,393.5
Beauty and Personal Care (2015) 1,452.8 1,225.1 1,590.7 2,498.6
Consumer electronics (2015) 6,391.7 NA 6,190.1 8,821.4
Consumer electronics (2020) 5,884.0 NA 5,709.7 10,556.1
Pag.  211