Title:
Economic Analysis of Mobile Advertising Networks: Targeting Precision, Revenue Models, Heterogeneous Privacy Concerns, and Costly Development of Targeting Capability
Economic Analysis of Mobile Advertising Networks: Targeting Precision, Revenue Models, Heterogeneous Privacy Concerns, and Costly Development of Targeting Capability
Author(s)
Kang, Chunghan
Advisor(s)
Xu, Lizhen
Narasimhan, Sridhar
Narasimhan, Sridhar
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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 decides the optimal levels of targeting precision and revenue sharing; the app developer responds by choosing its optimal revenue model among three options, which are the free, the paid, and the hybrid; and consumers with heterogeneous privacy sensitivity make their choices. It contains two essays based on the developed modeling framework. The first essays investigates whether the free revenue model persists as more consumers become privacy sensitive. We find that as more consumers become privacy sensitive, the ad-supported free revenue model prevails in equilibrium. Interestingly, we identify the existence of economic rents for the app developer when the proportion of highly privacy-sensitive consumers reaches a certain threshold. Consumer surplus is also maximized at this threshold. The second essay studies whether more stricter data privacy regulations are necessary to improve consumer surplus. We find that the hybrid revenue model is induced as costs decrease, where consumers obtain suboptimal surplus. By applying more stronger data privacy regulations, the optimal revenue model shifts back to free where consumer surplus could be maximized. This shift, however, could disproportionately disadvantage one consumer type while benefiting the other, necessitating a subtle calibration of the strength of data privacy regulations.
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Date Issued
2024-07-26
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Text
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Dissertation