A Study on Antitrust Regulation of Platform Economy Based on Evolutionary Game
- DOI
- 10.2991/978-94-6463-408-2_18How to use a DOI?
- Keywords
- Off-Platform Economy; Evolutionary Game; Data Simulation; Anti-Monopoly Behavior
- Abstract
This paper analyzes the selection and evolution process of game strategies by constructing an imperfectly rational government, platform enterprises and practitioners as a model of a three-party evolutionary game, and analyzes the conditions for reaching the optimal evolutionary steady state using numerical simulations. The path of China’s antitrust transformation in the context of the Internet platform economy is studied, and the influence of different antitrust actors on antitrust behavior is quantitatively evaluated, while the key factors of the path of national policy promotion are pointed out. The results show that in the context of the platform economy, the cost of government and the punishment for corporate violations play a key role in the efficiency of antitrust policy implementation. The advancement of antitrust behavior in the platform economy is more beneficial when the cost of government regulation is smaller and the punishment for violating enterprises is stronger.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Meijiao Zhang PY - 2024 DA - 2024/05/07 TI - A Study on Antitrust Regulation of Platform Economy Based on Evolutionary Game BT - Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024) PB - Atlantis Press SP - 153 EP - 163 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-408-2_18 DO - 10.2991/978-94-6463-408-2_18 ID - Zhang2024 ER -