Determinants of virtual reality stores influencing purchase intention: An interpretive structural modeling approach

Virtual reality (VR) stores are gaining popularity as they are highly interactive and enhance the consumer experience, allowing consumers to browse, engage, interact, and potentially revolutionize the purchase intention. However, limited scholarly research determines the causal relationship of determinants of VR stores for purchase intention. Thus, this study uses ‘interpretive structural modeling' (ISM) and ‘matrix impact cross-reference multiplication applied to classification (MICMAC) to identify the key determinants that affect purchase intention in VR stores. The study aims to identify the causal relationship between these factors, and by doing so, it examines the phenomena in a multi-level manner as a complex problem. After analyzing the extensive literature review on studies related to VR stores and with the assistance of domain experts, the study identifies ten factors, presenting the five-layered interpretive structure and showcasing the causal relationship between the factors. The study found e-service quality to be the most dominant factor influencing purchase intention in a VR store. Moreover, the MICMAC approach divides the identified factors into four quadrants between driving and dependence power. Thus, by employing the innovative use of methodological perspective, the study contributes to theory and practice by investigating the interrelationship of the determinants of VR stores influencing purchase intention.