Dear Faculty and Fellow Ph.D. Students,

I cordially invite you to attend my dissertation defense scheduled for Friday, July 5th, from 10:30 AM to 12:00 PM EST in Room 222, Scheller College of Business.

You are also welcome to join remotely via Zoom: https://gatech.zoom.us/j/5673200311?pwd=anVYVTFjUzJndEc4cCtxTXRsWHFQQT09

The dissertation abstract is included below. Copies of the dissertation are available upon request.

Chunghan Kang

Ph.D. Candidate

IT Management

Scheller College of Business

Georgia Institute of Technology

800 West Peachtree Street NW

Atlanta, GA 30308

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Area: Information Technology Management

Committee Members: Dr. Lizhen Xu (Co-chair), Dr. Sridhar Narasimhan (Co-chair), Dr. D.J. Wu, Dr. Marius Florin Niculescu, Dr. Ramnath K. Chellappa (Emory University)

Title: Economic Analysis of Mobile Advertising Networks: Targeting Precision, Revenue Sharing, Revenue Models, Heterogeneous Privacy Concerns, and Costly Development of Targeting Precision

Abstract

This dissertation develops a game-theoretic modeling framework involving three-stage decision-making among an ad network, an app developer, and consumers. The ad network determines the optimal levels of targeting precision and revenue sharing. In response, the app developer selects its optimal revenue model from three options: free, paid, and hybrid. Then, consumers with heterogeneous privacy sensitivity make their choices. The dissertation comprises two essays based on this modeling framework.

The first essay investigates whether the free revenue model persists as consumer privacy sensitivity increases. It finds that as more consumers become privacy sensitive, the ad-supported free revenue model arises in equilibrium. Interestingly, the study identifies the existence of economic rents for the app developer when the proportion of highly privacy-sensitive consumers reaches a certain threshold, where consumer surplus is also maximized. However, these economic rents and the superior consumer surplus are diminished if the proportion of privacy-sensitive consumers exceeds this threshold.

The second essay examines whether stricter data privacy regulations are necessary to improve consumer surplus as the costs of developing targeting precision decrease. The findings indicate that as costs decrease, the hybrid revenue model emerges in equilibrium, with the ad network developing a high level of targeting precision, which diminishes consumer surplus. To protect consumers, stronger data privacy regulations are required. However, consumer surplus does not increase linearly with the strength of the regulation. In fact, more stringent privacy regulations can disproportionately disadvantage one type of consumer while benefiting another, leading to the free revenue model in equilibrium. Nonetheless, well-calibrated data privacy regulations can achieve optimal overall consumer surplus by inducing the free revenue model and minimizing disproportionate disadvantages.