Publication Type
PhD Dissertation
Version
publishedVersion
Publication Date
12-2025
Abstract
The proliferation of data-driven mergers and acquisitions (M&A) has created a critical tension between the commercial value of integrated data assets and the fundamental privacy rights of users. This dissertation addresses the underexplored micro-foundations of user consent when personal data is transferred wholesale to an acquiring firm. It develops and empirically tests a sequential mediation model, anchored in Privacy Calculus and Signaling Theory, to explain how users' perceptions and intentions are shaped by different corporate data protection strategies.
A between-subjects experimental design was employed (N=532), exposing participants to one of three distinct protection mechanisms: procedural safeguards (emphasizing fairness and control), economic compensation (offering monetary value), or technical protections (highlighting security measures). User perceptions of risk and benefit, willingness for a privacy-convenience trade-off, consent intentions, and future behavioral intentions were measured and analyzed using regression and bootstrap mediation.
The findings reveal several critical insights. First, contrary to common assumptions, the economic compensation mechanism paradoxically heightened users' perceived risk. Second, procedural safeguards, which signal respect for user autonomy, proved to be the most effective strategy for reducing perceived risk and fostering the highest levels of consent. Third, the analysis confirmed an asymmetric privacy calculus, where perceived benefits exerted a substantially stronger positive influence on users' willingness to trade privacy than the negative influence of perceived risks. This research contributes a nuanced, evidence-based framework for understanding user consent in M&A, offering actionable guidance for managers on risk mitigation and for policymakers on refining data governance.
Keywords
Data-Driven M&A, Data Privacy, Privacy Calculus, Signaling Theory, User Consent
Degree Awarded
Doctor of Bus Admin (CKGSB)
Discipline
Business Administration, Management, and Operations
Supervisor(s)
BHATTACHARYA, Shantanu Hiralal
First Page
1
Last Page
121
Publisher
Singapore Management University
City or Country
Singapore
Citation
HU, Jun.
Striking a balance between personal data protection and transactional efficiency in the context of data-driven mergers. (2025). 1-121.
Available at: https://ink.library.smu.edu.sg/etd_coll/825
Copyright Owner and License
Author
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.