Customer Intentions towards Using IoT-based Shopping Applications

The advent of e-commerce puts traditional retail companies under a lot of pressure. One way they try to attract more customers to their physical stores is by offering online services on the retail sales floor. Such services are built on the Internet of Things which denotes the equipment of ordinary objects with digital smartness. One example is a fitting room that automatically detects customers’ product selection and provides additional information (e.g., available colors or sizes) and suitable product recommendations. The implementation of such applications, however, does not come without risks for retailers. This is because many of the services rely on personal information which customers could perceive as potential privacy threat. Against this backdrop, the present paper investigates the tradeoff between customers’ perceived benefits and their perceived privacy concerns towards IoT-based shopping applications. To this end, we propose a model based on the most recent version of the Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Extended Privacy Calculus Theory. The purpose of our study is to develop a better understanding of retail customers’ usage intentions towards such applications. Our results can be leveraged by retailers for the design of shopping applications that customers perceive as valuable instead of privacy-threatening