Designing smart physical stores using AI-enabled digital twins for an immersive shopping experience

This conceptual article introduces store digital twins (SDTs), an innovative data integration and modeling platform designed to enhance smart retail environments. It presents DT technology as an emerging paradigm bridging physical and digital dimensions, enabling adaptive, data driven and immersive shopping experiences. The article aims to acquaint stakeholders with the SDT concept and demonstrate its potential to optimize smart store design through a human-in-the-loop (HITL) approach that integrates artificial intelligence with human intuition, thereby advancing both decision-making and customer engagement in retail contexts.The article adopts a conceptual and integrative design approach, combining theoretical insights from digital twin (DT) research, design theory and methodology (DTM) and HITL systems. Drawing on multidisciplinary sources in marketing, design and computer science, it develops the H5D-SDT/DTM framework, which merges the five-dimensional DT model with human-centered design principles. This framework is used to conceptualize how data fusion, artificial intelligence and human intuition can jointly inform smart store layout, operation and decision-making. The study relies on synthesis and theoretical modeling rather than empirical testing to establish a foundation for future research and managerial application.The article demonstrates that SDTs can serve as powerful data fusion and decision-support systems for smart retail environments. By synchronizing real-time data from physical and digital sources, SDTs enable continuous optimization of store design, operations and customer experience. Integrating AI analytics with human intuition through a HITL mechanism enhances the adaptability, precision and creativity of design processes. The proposed H5D-SDT/DTM framework reveals how combining technological and human elements fosters more efficient, immersive and customer-centric retail spaces, establishing a conceptual foundation for data-driven and intelligent store design.As a theoretical and conceptual contribution, this study offers a foundational framework rather than empirical validation. While the proposed H5D-SDT/DTM model provides a structured basis for integrating digital and physical store dimensions, its practical implementation remains to be examined. Future research should empirically test the framework across diverse retail contexts, addressing issues of data synchronization, privacy and ethics. Simulation, case study and experimental designs may further refine the model and evaluate its effectiveness in optimizing store design and enhancing customer experience.The proposed SDT framework provides retailers with a structured tool for designing, testing and optimizing smart store environments before real-world implementation. By integrating AI-driven analytics, IoT data and human insights, managers can simulate store layouts, forecast customer behavior and improve operational efficiency with reduced cost and risk. The H5D-SDT/DTM model enables evidence-based decision-making, transforming traditional intuition-driven design into a data-supported process. Practically, it assists retailers in creating immersive, adaptive and customer-centric spaces while supporting predictive maintenance, layout optimization and enhanced consumer engagement across omnichannel retail environments.The integration of SDTs fosters more inclusive and human-centered retail environments. By combining artificial intelligence with human intuition, SDTs support accessibility, personalization and sustainability in physical stores. This approach promotes responsible technology use, enhances consumer well-being through adaptive and transparent shopping experiences, and strengthens the relationship between retailers and society by aligning smart store design with ethical and environmental values.This article is among the first to introduce DT technology into marketing and retail store design. It proposes the H5D-SDT/DTM framework, which integrates digital modeling, design theory and human intuition. By linking the physical and digital dimensions of retail environments, the study offers a structured conceptual foundation for understanding and optimizing smart store design. The framework contributes modestly to both theory and practice by illustrating how data-driven and human-centered approaches can enhance decision-making and customer experience in contemporary retail settings.