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Video Games Market Forecast Based on Linear Regression Model
- 1 Computer and AI, The Hong Kong Polytechnic School, Hong Kong, 999077, China
- 2 School of Artificial Intelligence, Guangxi Minzu University, Guangxi 530000, China
- 3 College of Intelligent Manufacturing, Tianjin College, University of Science and Technology Beijing, Tianjin, 301830, China
* Author to whom correspondence should be addressed.
Abstract
In recent years, the video game industry has been developing rapidly and the global market scale has been expanding. In this case, pre-study of the video game market has important theoretical and practical significance. Based on the Video Game Sales dataset, this study comprehensively analyses the development of the video game market over the last forty years through data analysis and mathematical modelling. This study uses a linear regression model to analyse the trend of the video game market over the past forty years. The paper finds that the scale of its tends to grow year by year, and the growth rate shows a linear trend. The video game market has shown a linear growth trend in the past forty years, and the market size has been expanding. The significance of this study is to provide a new idea and method for the prediction of the video game market, which helps to better understand the market dynamics and trends and provides a decision-making basis for related enterprises and policymakers.
Keywords
Video game market, forecast, data analysis.
[1]. Lin Q Y 2021 Value assessment of video game enterprises based on Schwartz-Moon model (Jiangxi: Jiangxi University of Finance and Economics)
[2]. Wang R 2019 Research on the development and current situation of China's video game industry (Chengdu: Chengdu Information Engineering University)
[3]. Xinhua News 2002 U.S. video game products hot International Economic and Trade News 2002-03-07(004)
[4]. U.S. video game sales jump 16% in October 2021 China and Foreign Toy Manufacturing (12) p 75
[5]. Zhan K 2021 Research on the competitive strategy of R game company in China market (Guangzhou: Guangdong University of Technology)
[6]. Xu X Y and Wu K Z 2023 Global gamers to reach 3.2 billion by 2022. Release of version number revives industry confidence China Business News 2023-01-02(C04)
[7]. Zhou Z X 2022 A brief analysis of game industry based on automatic machine learning Computer Knowledge and Technology 18(24) pp 93–95
[8]. Wang T 2022 Exploration on the development of e-sports industry in China Foreign Trade and Economics (03) p 60–62
[9]. Zhou Z Y 2021 An analysis of the corporate environment and strategy of Nintendo of Japan Modern Enterprise (06) pp 183–184
[10]. Li H 2021 China's e-sports industry develops rapidly with annual output value reaching 140 billion yuan in 2020 Computer and Network 47(02) p 9
Cite this article
Li,X.;Liu,Z.;Xu,G. (2024). Video Games Market Forecast Based on Linear Regression Model. Applied and Computational Engineering,97,139-144.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation
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