Research on Digital Transformation of Small and Medium-Sized
Enterprises Driven by Dual Agent Collaboration
- DOI
- 10.2991/978-94-6463-010-7_45How to use a DOI?
- Keywords
- Digital Transformation; Government; Market; Evolutionary Game
- Abstract
From the perspective of multi-agent collaboration, this paper builds a tripartite evolutionary game model of government-market-enterprise, studies how the government and market cooperate to drive the digital transformation of enterprises, uses MATLAB software to conduct numerical simulation, and analyzes the evolution path. The results show that the choice of an enterprise’s digital transformation strategy is affected by both the government and the market. Enterprise profits, competitive profits, transformation costs, relationship losses, cost synergy coefficient, revenue sharing coefficient, and cost reduction coefficient will all affect the formation of the stable equilibrium point of the enterprise. With the gradual decline of the cost synergy coefficient and the gradual increase of the revenue sharing coefficient and the cost reduction coefficient, enterprises have begun to choose digital transformation.
- Copyright
- © 2023 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 - Hongwei Zhou PY - 2022 DA - 2022/12/02 TI - Research on Digital Transformation of Small and Medium-Sized BT - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022) PB - Atlantis Press SP - 428 EP - 437 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-010-7_45 DO - 10.2991/978-94-6463-010-7_45 ID - Zhou2022 ER -