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

AIS Transactions on Human-Computer Interaction (THCI), vol. 8(3), pp. 88–130 (2016)

44 Pages Posted: 20 Sep 2016 Last revised: 4 Oct 2016

See all articles by Mark J. Keith

Mark J. Keith

Brigham Young University - Marriott School

Jeffry Babb

West Texas A&M University

Christopher Furner

West Texas A&M University

Amjad Abdullat

West Texas A&M University

Paul Benjamin Lowry

Virginia Tech - Pamplin College of Business

Date Written: September 15, 2016

Abstract

Mobile Applications (a.k.a. apps) have rapidly grown into a multi-billion-dollar industry. Because they are available through devices that are “always on” and often with the user, mobile apps are often adopted “on the fly” as needed. As a result, the related adoption and disclosure decisions are frequently only based on the information provided through the mobile app delivery platform (e.g., the Apple App Store™ or Google Play™). The fact that mobile app use often requires the disclosure of an unprecedented combination of personal information (e.g., location data, preferences, contacts, calendars, browsing history, music library) means that a very complex risk/benefit tradeoff decision is based on only the small amount of information provided by the mobile app delivery platform — 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 the 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). The results indicate that network size influences not only perceived benefits but also the perceived risks of apps in the absence of perfect information. In addition, we find that integrating a third-party privacy assurance system into the app platform has a significant influence on app adoption and information disclosure. LBS privacy risk perceptions can also be reduced by network size, thus confirming our information cascade hypothesis. We further discuss the implications of these findings for research and practice.

Keywords: Mobile applications, location-based services, network effects, privacy assurance, electronic commerce, information cascades, privacy seals, privacy calculus, information privacy

Suggested Citation

Keith, Mark J. and Babb, Jeffry and Furner, Christopher and Abdullat, Amjad and Lowry, Paul Benjamin, Limited Information and Quick Decisions: Consumer Privacy Calculus for Mobile Applications (September 15, 2016). AIS Transactions on Human-Computer Interaction (THCI), vol. 8(3), pp. 88–130 (2016), Available at SSRN: https://ssrn.com/abstract=2840713

Mark J. Keith

Brigham Young University - Marriott School ( email )

Provo, UT 84602
United States

Jeffry Babb

West Texas A&M University ( email )

Canyon, TX 79016
United States

Christopher Furner

West Texas A&M University ( email )

Canyon, TX 79016
United States

Amjad Abdullat

West Texas A&M University ( email )

Canyon, TX 79016
United States

Paul Benjamin Lowry (Contact Author)

Virginia Tech - Pamplin College of Business ( email )

1016 Pamplin Hall
Blacksburg, VA 24061
United States

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