The Impacts of Privacy Rules on Users' Perception on Internet of Things (IoT) Applications: Focusing on Smart Home Security Service

Department of Management EngineeringAs communication and information technologies advance, the Internet of Things (IoT) has changed the way people live. In particular, as smart home security services have been widely commercialized, it is necessary to examine consumer perception. However, there is little research that explains the general perception of IoT and smart home services. This article will utilize communication privacy management theory and privacy calculus theory to investigate how options to protect privacy affect how users perceive benefits and costs and how those perceptions affect individuals??? intentions to use of smart home service. Scenario-based experiments were conducted, and perceived benefits and costs were treated as formative second-order constructs. The results of PLS analysis in the study showed that smart home options to protect privacy decreased perceived benefits and increased perceived costs. In addition, the perceived benefits and perceived costs significantly affected the intention to use smart home security services. This research contributes to the field of IoT and smart home research and gives practitioners notable guidelines.ope

Intention To Disclose Personal Information Via Mobile Applications: A Privacy Calculus Perspective

This study aimed to investigate the issue of consumer intention to disclose personal information via mobile applications (apps). Drawing on the literature of privacy calculus theory, this research examined the factors that influence the trade-off decision of receiving perceived benefits and being penalized with perceived risks through the calculus lens. In particular, two paths of the direct effects on perceived benefits and risks that induce the ultimate intention to disclose personal information via mobile apps were proposed and empirically tested. The analysis showed that self-presentation and personalized services positively influence consumers’ perceived benefits, which in turn positively affects the intention to dis- close personal information. Perceived severity and perceived control serve as the direct antecedents of perceived risks that negatively affect the intention of consumers to disclose personal information. Compared with the perceived risks, the perceived benefits more strongly influence the intention to disclose personal information. This study extends the literature on privacy concerns to consumer intention to disclose personal information by theoretically developing and empirically testing four hypotheses in a research model. Results were validated in the mobile context, and implications and discussions were presented

Continued Usage and Location Disclosure of Location-Based Applications: A Necessity for Location Intelligence

Location-based applications (LBA) have been widely accepted and used for different purposes ranging from navigation to dating or gaming. Most LBAs ask users to provide access to location data for more efficient and personalized location-based services. Location intelligence as an emerging area of business intelligence relies heavily on disclosing location information by users. This research builds a continuance usage and location disclosure model from the expectation-confirmation perspective. The effect of benefit expectations on usefulness and satisfaction is hypothesized. In addition, the positive effect of usefulness on satisfaction and continuance intention is postulated. After collecting survey data from main LBA users, the results of the analysis support the proposed model. Findings contribute to the current literature in business intelligence by focusing on location disclosure behavior in the context of LBAs and the necessity of this type of information for location intelligence