Complement or Substitute? Optimal Combination of Heterogeneous AI Support Tools and Monetary Incentive Strategies for Competitive UGC Platforms

Authors

• Jie Luo, School of Economics and Management, Beihang University, ChinaFollow
• Jun Wang, School of Economics and Management, Beihang University, ChinaFollow
• Mujiang Deng, School of Economics and Management, Beihang University, ChinaFollow
• Rongxuan Zhuang, School of Economics and Management, Beihang University, ChinaFollow

Abstract

As generative AI spreads and competition for audience attention intensifies, UGC platforms increasingly combine AI support tools with creator payment strategies. This paper develops a game-theoretic model of competing platforms and distinguishes complementary AI, which raises the value of human-created content, from substitutive AI, which adds automated content independently of the human content base. The analysis identifies three optimal strategy regimes. Platforms use only substitutive AI when human content is absent, combine both tools when human content is scarce, and rely only on complementary AI once content exceeds a scarcity threshold. Stronger creator incentives reduce substitutive AI and affect complementary AI nonmonotonically through a scale-margin trade-off. Greater rival attention pressure lowers both support intensities without changing the AI portfolio boundary.

Recommended Citation

Luo, Jie; Wang, Jun; Deng, Mujiang; and Zhuang, Rongxuan, "Complement or Substitute? Optimal Combination of Heterogeneous AI Support Tools and Monetary Incentive Strategies for Competitive UGC Platforms" (2026). ICEB 2026 Proceedings (Beijing, China). 23.
https://aisel.aisnet.org/iceb2026/23