Competitive Strategies and Operational Optimization of Music Enterprises in the Context of Globalization

Authors

  • Xingang Shi Department of Music, Yuncheng University, Yuncheng 044000, Shanxi, , China

DOI:

https://doi.org/10.70917/ijcisim-2026-0098

Keywords:

evolutionary game theory; music firms; stable equilibrium; Nash equilibrium

Abstract

 In the music market driven by the trend of globalization, different subject music enterprises are limited by their positions and perceptions, and have higher quality strategy needs in competition and operation. This paper adopts the emerging evolutionary game theory to explore the equilibrium stability of decision-making behavior of market players with limited rationality and access to limited information, as well as the factors affecting it. On the basis of the theory of evolutionary games, the mathematical definition of stable equilibrium state under evolutionary stable strategy is designed. At the same time, we further analyze the equilibrium stability of the two-party, two-strategy evolutionary game, and comprehensively construct an analytical model of the evolutionary game. Analyze the development trend of mobile music business in the United States, South Korea, and Japan from 2008 to 2012 as the data samples for the study. The proposed evolutionary game analysis model is used to determine the Nash equilibrium stability zone in the music market competition, and analyze the changes of the average profit of different market players under different parameter values. In particular, when the music producers' concern about fairness is lower than 0.2, the average profit of both the music producers themselves and the music retailers show an upward trend as the music producers' concern about fairness grows.

Downloads

Download data is not yet available.

Downloads

Published

2026-01-23

How to Cite

Xingang Shi. (2026). Competitive Strategies and Operational Optimization of Music Enterprises in the Context of Globalization. International Journal of Computer Information Systems and Industrial Management Applications, 18, 12. https://doi.org/10.70917/ijcisim-2026-0098

Issue

Section

Original Articles