Building on Keaveney’s work and using related studies from the disciplines of marketing and psychology, a model of service provider switching was developed. It was empirically examined using structural equation modeling with data from customers of mortgage services of various Canadian financial institutions. Factors deemed responsible for switching behavior, along with switching intentions, were measured from mortgage customers. Self-reports of their actual behavior were also collected via telephone.

Although cloud computing has a number of benefits, privacy risks play a critical role in organizations’ decisions to switch to cloud services. However, few studies on cloud adoption have investigated effects of both benefits and costs on switching intention. Based on cost-benefit analysis and technology acceptance model, this study develops a research model to investigate how benefits (perceived usefulness and perceived ease of use) and costs (perceived risk and privacy concerns) influence organizations’ switching intention to cloud Enterprise Resource Planning (ERP). The model also accounts for trust and perceived control in the context of cloud computing. Perceived usefulness, perceived ease of use, and privacy concerns significantly affect switching intention. Trust can enhance perceived usefulness and perceived ease of use and reduce perceived risk. Perceived control can also reduce perceived risk and privacy concerns. The findings are useful to understand switching issues from traditional ERP to cloud ERP for both researchers and practitioners.

Valid measurement scales for predicting user acceptance of computers are in short supply. Most subjective measures used in practice are unvalidated, and their relationship to system usage is unknown. The present research develops and validates new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance. Definitions for these two variables were used to develop scale items that were pretested for content validity and then tested for reliability and construct validity in two studies involving a total of 152 users and four application programs. The measures were refined and streamlined, resulting in two six-item scales with reliabilities of.98 for usefulness and.94 for ease of use. The scales exhibited high convergent, discriminant, and factorial validity. Perceived usefulness was significantly correlated with both self-reported current usage (r=.63, Study 1) and self-predicted future usage (r=.85, Study 2). Perceived ease of use was also significantly correlated with current usage (r=.45, Study 1) and future usage (r=.59, Study 2). In both studies, usefulness had a significantly greater correlation with usage behavior than did ease of use. Regression analyses suggest that perceived ease of use may actually be a causal antecedent to perceived usefulness, as opposed to a parallel, direct determinant of system usage. Implications are drawn for future research on user acceptance.

Understanding the privacy concerns of individuals in the adoption of contact tracing apps is critical for the successful control of pandemics like COVID-19. This paper explores the privacy paradox in the adoption of contact tracing apps in Australia.

In this paper, we report the development of scales to measure the perceived benefits and risks associated with online shopping. Based on an exploratory qualitative inquiry and quantitative assessment, a four-factor scale of perceived benefits and a three-factor scale of perceived risks of online shopping were developed. Results from two national samples support the proposed measures of perceived benefits and risks associated with online shopping in terms of construct, convergent, discriminate, nomological, and predictive validity. Variation of these perceptions over time was also examined to test scale stability over time and to describe the evolution of online shopping.

This paper aims to examine consumers’ behaviors toward personalized services offered by branded mobile apps in the food service industry by applying privacy calculus theory and technology acceptance model (TAM). Further, this research identified the moderating role of technology anxiety.

The lack of consumer confidence in information privacy has been identified as a major problem hampering the growth of e-commerce. Despite the importance of understanding the nature of online consumers' concerns for information privacy, this topic has received little attention in the information systems community. To fill the gap in the literature, this article focuses on three distinct, yet closely related, issues. First, drawing on social contract theory, we offer a theoretical framework on the dimensionality of Internet users' information privacy concerns (IUIPC). Second, we attempt to operationalize the multidimensional notion of IUIPC using a second-order construct, and we develop a scale for it. Third, we propose and test a causal model on the relationship between IUIPC and behavioral intention toward releasing personal information at the request of a marketer. We conducted two separate field surveys and collected data from 742 household respondents in one-on-one, face-to-face interviews. The results of this study indicate that the second-order IUIPC factor, which consists of three first-order dimensions—namely, collection, control, and awareness—exhibited desirable psychometric properties in the context of online privacy. In addition, we found that the causal model centering on IUIPC fits the data satisfactorily and explains a large amount of variance in behavioral intention, suggesting that the proposed model will serve as a useful tool for analyzing online consumers' reactions to various privacy threats on the Internet.

To date, many important threads of information privacy research have developed, but these threads have not been woven together into a cohesive fabric. This paper provides an interdisciplinary review of privacy-related research in order to enable a more cohesive treatment. With a sample of 320 privacy articles and 128 books and book sections, we classify previous literature in two ways: (1) using an ethics-based nomenclature of normative, purely descriptive, and empirically descriptive, and (2) based on their level of analysis: individual, group, organizational, and societal.

Research Summary This paper studies the impact of platform-owner entry threat on complementors in platform-based markets. We examine how app developers on the Android mobile platform adjust innovation efforts (rate and direction) and value-capture strategies in response to the threat of Google's entry into their markets. We find that after Google's entry threat increases, affected developers reduce innovation and raise the prices for the affected apps. However, their incentives to innovate are not completely suppressed; rather, they shift innovation to unaffected and new apps. Given that many apps already offer similar features, Google's entry threat may thus reduce wasteful development efforts. We discuss the implications of these results for platform owners, complementors, and policy makers. Managerial Summary We examine one prevalent source of conflict: platform owners' entry into complementary product spaces. We show that app developers on Google's Android system are strategic and nimble actors. They respond to the threat of Google's entry by adjusting both value-creation and value-capture strategies. We also show that platform owners could use direct entry to shape innovation directions and encourage variety of complements. Overall, on the one hand, Google's entry may have pushed complementors into other areas (which might be less lucrative) and strengthened its position in the mobile market. On the other hand, the entry may have reduced wasteful production efforts in the development of redundant applications. The overall welfare implication is thus ambiguous.