Date of Award

8-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Management

Committee Chair/Advisor

William J. Kettinger (Committee Chair)

Committee Member

Zhihong Ke (Co-Chair)

Committee Member

Jiahui Mo

Committee Member

Russell L. Purvis

Abstract

This dissertation examines how data privacy practices and complaint response strategies influence user behavior and market outcomes in digital marketplaces. The first study analyzes the impact of Google Play’s Data Safety Label, launched in April 2022 to standardize data collection, third-party sharing, and security disclosures. Grounded in signaling and prospect theories, the label is treated as a compound signal users interpret holistically. A difference-in-differences analysis of 23,877 top Android apps over two years shows that disclosures increase user app adoption. Internal data collection boosts adoption, while third-party sharing reduces it, reflecting behavioral loss aversion. Security disclosures moderate these effects by enhancing trust and offsetting shared concerns. The findings extend signaling theory by showing how multi-attribute disclosures jointly shape user behavior. The second study investigates how public responses to user complaints affect user app adoption. Drawing on service-dominant logic and the literature on service failure and recovery, the study analyzes over 7.6 million user reviews and 2.7 million developer responses across 22,998 apps. Complaints are categorized as processes (e.g., access or payment issues) or outcomes (e.g., bugs or quality). Collaborative responses—acknowledging issues and offering solutions—increase adoption for process complaints but reduce it for outcome complaints, especially when peer-endorsed. Complaint type thus emerges as a boundary condition for effective symbolic recovery, informing scalable strategies for public user engagement. These studies show how transparency and responsiveness are trust signals in digital marketplaces. By integrating theory with large-scale data, the dissertation offers practical insights for enhancing user app adoption, addressing privacy concerns, and improving developer-user dynamics.

Available for download on Monday, August 31, 2026

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