The Role of Mobile-Computing Self-Efficacy in Consumer Information Disclosure

Abstract

Smartphones are increasingly penetrating business and consumer markets, and mobile applications (apps) have engendered a large and innovative market. Whereas apps are useful, they also present new forms of privacy risk associated with users’ personal and location data. However, these dangers do not appear to increase the perceived risk or reduce the trust consumers demonstrate when using apps. Many information technology (IT) trust indicators are well documented, such as the quality of the IT, trust assurances, brand recognition and social influences. However, these traditional indicators appear to have a lesser impact on the adoption of mobile commerce via apps because of the nature of mobile-app adoption and subsequent information disclosure. As a result, we draw from social cognitive theory and its construct of self-efficacy in particular to explain perceived mobile-app risk and provider trust. Through two controlled experiments, we demonstrate the strong direct effect of mobile-computing self-efficacy on users’ initial trust in location-based app vendors as well as their perceived risk of disclosing information – regardless of the actual trustworthiness of the app vendor. The results imply that being skilled in the latest smartphones and apps can cause users to place greater trust in app providers and perceive less risk in the app itself, even when the intentions of the app providers cannot be verified.

Keywords: Mobile-Computing Self-Efficacy, Location-Based Services, Trust, Perceived Risk, Privacy Calculus, Mobile Apps, Smartphones