The Impact of Perceived Privacy Benefit and Risk on Consumers’ Desire to Use Internet of Things Technology

This study seeks to identify the dimensions of privacy benefit and risk in the context of Big Data and IoT technology. Based on the theory of privacy calculus, we investigate the impact of privacy benefits and risks on consumers’ desire to use IoT technology. Two dimensions of perceived privacy benefit are identified as direct benefit of customized service and indirect benefit of efficiency innovation of suppliers. Three dimensions of perceived privacy risk are identified as passive user data collection, predictive use of personal data, and market discrimination as a negative consequence of Big Data Analytics. Depending on the types of IoT technology, the effects of perceived privacy benefits on consumers’ desire to use are different. Consumers who perceive more benefit of customized service want more to use smart home appliance, while consumers who perceive more benefit from suppliers’ efficiency innovation want more to use remote home service. Contrary to the hypothesis, the effect of predictive use of privacy risk on consumers’ desire to use IoT technology is positive.