The Diffusion of Predictive Analytics for Innovative Interactive Marketing Strategy in International E-Fashion Commerce

What the paper says

Purpose : This research explored the factors prompting the diffusion of predictive analytics (PA) in international e-fashion companies. A typology of motives, advantages, and diffusion challenges was provided, and recommendations on overcoming them were suggested to PA executives. Methodology : Based on integrating the technology – organization – environment (TOE) perspectives into the steps of diffusion of innovation (DOI) theory, a new systemic framework was developed to explain the process of diffusing PA in e-fashion and to help design interactive, innovative marketing strategies that enhanced the customer experience in such an international e-commerce industry. This study adopted an interpretative approach by conducting 20 semi-structured interviews with e-commerce analytics leaders in the top 10 fashion companies between 2020 and the end of 2024. Findings : The findings referred to a range of motives based on intention to use, market niche, and informational, transactional, and transformational values provided by the companies. The challenges emphasized by the participants were complexity, organizational readiness, compatibility, management support, observability, privacy and security, external support, trialability, competitive pressure, and government regulations. Practical Implications : The study offered guidelines for PAs on how to set the right questions, frame their dataset, and set the right interactive, innovative strategy for customers. Originality : A dynamic framework of PA diffusion was provided to reflect the “Linear vs. Cyclical Process,” “Static Factors vs. Dynamic Processes,” “Inclusion of Post-Adoption Benefits,” “Nuanced Understanding of Management Support,” and “Specification of Key Challenges and Pathways.”