The equivalence of incentive schemes in content platforms: an equilibrium analysis
Purpose For most platforms, a key challenge is to design appropriate incentive mechanisms that effectively motivate relevant participants in an open environment. In this paper, the authors aim to focus on a three-sided content platform involving creators, users and advertisers and investigate the strategic design of such mechanisms. Specifically, this study analyzes and compares three common incentive schemes: content-volume-based, view-volume-based and a hybrid of the previous two. Design/methodology/approach Using a game-theoretic model that captures the interactions among all parties, this study derives closed-form equilibrium solutions for the platform’s optimal incentive fees and advertising prices, as well as for creators’ content-production levels and payoffs. Findings The analysis reveals a striking equivalence among the three schemes: despite their structural differences, they yield identical equilibrium outcomes in content production, user engagement, advertising metrics and platform profit. Moreover, the optimal hybrid incentive fees are simply a convex combination of optimal incentive fees under the two pure schemes, giving managers budgetary flexibility without affecting performance. Originality/value This study contributes to the literature on multisided platforms by demonstrating the strategic substitutability of common incentive structures and by providing a unified framework for understanding platform design when advertising levels and creator competition are endogenous.
Authors
- Q. B. Gou (ORCID: https://orcid.org/0009-0004-4794-6714)
- Xi Zhang (ORCID: https://orcid.org/0000-0002-4638-3997)
- Junkai Hu (ORCID: https://orcid.org/0000-0001-8135-8343)
- Yujia Liu
Institutions
- University of Science and Technology of China (CN)
- Hefei University of Technology (CN)
Publication Details
- Journal
- Journal of Modelling in Management
- Published
- 2026-04-07
- DOI
- https://doi.org/10.1108/jm2-11-2025-0646
- Primary Topic
- Digital Platforms and Economics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China