The advance of information technologies and the Internet have been enabling the transformation of physical products into smart products by embedding information technologies into the products and thereby making them intelligent. The movement to the ‘Internet of Things’ is accelerating connection of the products to the net. While those changes could enhance value propositions of products, they might also cause consumer privacy concerns, which might hinder smart product adoption, because the smartness of the product mainly takes advantage of personal information about the users. This study aims to investigate consumers’ intention to adopt smart products. Building on previous studies on smart products and privacy literature, we propose a research model that explains factors influencing consumers’ intention to adopt smart products. The proposed research model is empirically tested using data from an online survey of consumers. The overall results validate the proposed research model of smart product adoption. Specifically, perceived personalization is found to positively affect consumers’ intention to adopt smart products, whereas information privacy risk decreases the intention. We also find that the attributes of personal information are critical antecedents of consumers’ risk-benefit assessment. The sensitivity of information increases information privacy risk while the congruency of information enhances perceived personalization. Based on the results, theoretical and managerial implications are discussed.
Lee, Dong-Joo and Kim, Myoung-Soo, "An Empirical Investigation of Smart Product Adoption" (2016). ICEB 2016 Proceedings. 4.