The "Internet of Things Intitiative" (IoT-i)

This initial report contributes to the overall objective of IoT-i to evaluate the social acceptance and regulatory impact of IOT applications. Accordingly, the relevance of privacy issues in combination with IT artefacts, and in particular IOT-based applications, has been addressed by prior research (Anderson and Moore, 2009; Angst and Agarwal, 2009; Dinev and Hart, 2006; Kosta and Dumortier, 2008; Little, 2008; Malhotra et al., 2004; Pramatari and Theotokis, 2009; Spiekermann, 2009; Weber, 2010). However, no empirical privacy instrument has been adapted to the class of IoT services. In order to address this lack of research, a corresponding research model with a focus on privacy issues is proposed and empirically evaluated by a first user study with domain experts. This research model comprises critical privacy factors that predict the behavioural acceptance of IOT applications and the individuals' willingness to provide personal information for those applications. In addition, an instrument is presented and employed to measure the impact on legislative and regulatory aspects.

Internet of Things (IoT) services provide new privacy challenges in our everyday life. Although privacy research has been addressed to a great extent in the Information Systems discipline, there still exists no robust instrument for the evaluation of IoT services. The contribution of this chapter is therefore to propose and test such an instrument in order to provide policy makers, IT developers and IS researchers with recommendations on how to design privacy-aware IoT services. The current research is based on utility maximization theory and integrates theoretical constructs from the Extended Privacy Calculus Model and the Technology Acceptance Model. An empirical study with 92 subjects is conducted to test this instrument. Results indicate that the acceptance of IoT services is influenced by various contradicting factors such as perceived privacy risks and personal interests. It is further assumed that legislation, data security and transparency of information influences the adoption behaviour. Further research will focus on these factors to enable the development of useful and secure IoT services in the very near future.

When objects can sense the environment and communicate, they become powerful tools for understanding complexity and responding to it effectively. Though such smart objects can interact with humans, they are likely to be interacting even more with each other automatically, without human intervention, updating themselves their daily schedules... (Foreword by Gérald Santucci)

Internet of Things (IOT) services - namely sensor-based IS services facilitated by identification technologies such as barcode, radio frequency, IPv6, or global satellite communication - provide new security and privacy challenges in private and business situations of our everyday life. Accordingly, the relevance of privacy and security has been addressed in prior Information Systems research and, as a result, design methodologies, guidelines and policies have been discussed and proposed. However, there still exists no robust empirical instrument that has been developed and successfully tested for the class of IOT services and that combines critical privacy factors and IT acceptance research. Thus, privacy factors need to be identified that have an impact on the behavioural intention to use IOT services, individuals' willingness to pay for these services and their willingness to provide personal information in business situations and private situations. The contribution of this report is therefore to address this lack of knowledge in order to provide policy makers, IT developers and IS researchers with recommendations on how to design IOT services. The proposed underlying research model is based on utility maximization theory and integrates theoretical constructs from the Extended Privacy Calculus Model and the Technology Acceptance Model. This model is empirically tested with 92 IT-savvy subjects via an online survey. Results indicate that behavioural intentions to use IOT services are influenced by various contradicting success factors such as perceived privacy risks and personal interests. That is, the driver of adoption results from the trade-off between these factors. Additionally, success factors depend on the underlying usage situation be it a business situation or a private situation. It can be further stated that contextual factors such as legislation and data security as well as transparency of information use influence the adoption of IOT services. Accordingly, further research must focus on a better understanding of these success factors to increase the adoption of both useful and secure IOT services in the future.