Cooperation and privacy-protection strategies for cross platform targeted advertising in competitive markets

Purpose In practice, platform partnerships may be unstable, and privacy protection strategies may vary across platforms. This study examines optimal cooperation and privacy protection strategies for third-party platforms implementing cross-platform targeted advertising in competitive markets. Design/methodology/approach We develop a game-theoretic model involving two competing third-party platforms, one e-commerce platform, consumers, and advertisers. Equilibrium outcomes are derived using backward induction. The model captures platforms' decisions regarding cross-platform cooperation and privacy protection strategies. Findings In cross-platform targeted advertising, cross-platform cooperation does not necessarily confer a competitive advantage on cooperating third-party platforms. Both symmetric and asymmetric cooperation can arise in equilibrium, depending on competition in the consumer and advertiser markets. Privacy protection does not necessarily increase platform profits, and its effects depend on the relative strength of competition along the content and privacy protection dimensions. Third-party platforms do not always choose high levels of privacy protection. Their choices depend on consumer privacy concerns and rivals' strategies, while asymmetric protection can provide a basis for differentiation. Originality/value This study examines competing third-party platforms' decisions on cooperation with an e-commerce platform and privacy protection in cross-platform targeted advertising. It extends platform coopetition research by explaining how vertical data cooperation reshapes horizontal competition and advances privacy strategy research by examining the relative strength of competition along the content and privacy protection dimensions. The findings help third-party platforms assess when cooperation increases profits and which privacy protection strategy is preferable.