Limited Information and Quick Decisions: Consumer Privacy Calculus for Mobile Applications

Mobile applications (also known as “apps”) have rapidly grown into a multibillion-dollar industry. Because they are available through devices that are “always on” and often with the user, users often adopt mobile apps “on the fly” as they need them. As a result, users often base their adoption and disclosure decisions only on the information provided through the mobile app delivery platform (e.g., the Apple App Store™ or Google Play™). The fact that using a mobile app often requires one to disclose an unprecedented combination of personal information (e.g., location data, preferences, contacts, calendars, browsing history, music library) means that one makes a complex risk/benefit tradeoff decision based on only the small amount of information that the mobile app delivery platform provides—and all in a short period of time. Hence, this process is much shorter and much riskier than traditional software adoption. Through two experiments involving 1,588 mobile app users, we manipulated three primary sources of information provided by a platform (app quality ratings, network size, and privacy assurances) to understand their effect on perceptions of privacy risks and benefits and, in turn, how they influence consumer adoption intentions and willingness to pay (WTP). We found that network size influenced not only perceived benefits but also the perceived risks of apps in the absence of perfect information. In addition, we found that integrating a third party privacy assurance system into the app platform had a significant influence on app adoption and information disclosure. We also found that a larger network size reduces LBS privacy risk perceptions, which confirms our information cascade hypothesis. We discuss the implications of these findings for research and practice

PRIVACY ASSURANCE AND NETWORK EFFECTS IN THE ADOPTION OF LOCATION-BASED SERVICES: AN IPHONE EXPERIMENT

The use of geospatially aware mobile devices and applications is increasing, along with the potential for the unethical use of personal location information. For example, iPhone apps often ask users if they can collect location data in order to make the program more useful. The purpose of this research is to empirically examine the significance of this new and increasingly relevant privacy dimension. Through a simulation experiment, we examine how the assurance of location information privacy (as well as mobile app quality and network size) influences users\u27 perceptions of location privacy risk and the utility associated with the app which, in turn, affects their adoption intentions and willingness-to-pay for the app. The results indicate that location privacy assurance is of great concern and that assurance is particularly important when the app’s network size is low or if its quality cannot be verified