Scaling AI-Based Retail Technologies Across Global Markets: A Multi-Level Study Integrating Consumer Acceptance, Business Networks, and Market Context in Fashion E-Commerce

Abstract

This thesis examines how AI-based virtual fitting room (VFR) technologies are adopted and scaled across international fashion e-commerce markets, with a particular focus on the interplay between consumer attitudes, retailer adoption considerations, and firm-level internationalization. Drawing on technology acceptance theory (TAM), internationalization theory, and business network perspectives, the study develops a multi-level understanding of how VFR technologies are evaluated and implemented while scaling internationally. Using WEON, a Swedish VFR technology provider, as an empirical focal case, the study investigates adoption dynamics across contrasting contexts, comparing digitally mature Scandinavian markets with developing North African markets to examine how adoption varies under different infrastructural, institutional, and retail conditions. The study employs a qualitative multi-level case study design, and is based on semi-structured interviews with representatives of the focal firm as well as their potential retailers and end-consumers across both regional contexts. The findings demonstrate that VFR adoption is shaped not only by perceived usefulness and ease of use, but also by progressive trust formation, operational feasibility, assortment complexity, retailer readiness, and broader market infrastructure. Here, trust emerges as performance-conditioned and developed through repeated successful use, rather than functioning as a pre-existing adoption driver. Furthermore, the findings indicate that cross-cultural market differences are influenced less by broad cultural attitudes towards AI and more by infrastructural and operational conditions such as retailer return logistic, platform legitimacy, regulatory environments, and levels of digital retail maturity. The study contributes to existing literature by integrating consumer-level technology acceptance with retailer-level adoption dynamics and firm-level internationalization processes within a single analytical framework. It further extends research on AI-based retail technologies by identifying assortment variation and garment category complexity as significant yet underexamined factors of VFR adoption. Moreover, the study also contributes to digital internationalization research by showing how AI-based technology providers can rely on pilot-based experimentation, retailer collaboration, and systematic market learning when scaling across international e-commerce environments.