Unveiling the economic potential of sports industry in China: A data driven analysis

The article explains the economic dynamics of the sports industry with adoption of deep learning algorithms and data mining methodology. Despite outstanding improvements in research of sports industry, a significant gap prevails with regard to proper quantification of economic benefits of this indus...

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Published in:PloS one 2024-09, Vol.19 (9), p.e0310131
Main Author: Liu, Haishan
Format: Article
Language:English
Subjects:
Algorithms
Biology and Life Sciences
China
Computer and Information Sciences
Data analysis
Data Mining
Database industry
Decision making
Deep Learning
Economic analysis
Economic aspects
Economic development
Economic growth
Economic impact
Economic models
Evaluation
Forecasts and trends
Humans
Industrial development
Industry - economics
Learning algorithms
Machine learning
Marketing
Models, Economic
People and Places
Research and Analysis Methods
Social Sciences
Sports
Sports - economics
Strategic planning
Technology assessment
Trajectory analysis
Trends
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description The article explains the economic dynamics of the sports industry with adoption of deep learning algorithms and data mining methodology. Despite outstanding improvements in research of sports industry, a significant gap prevails with regard to proper quantification of economic benefits of this industry. Therefore, the current research is an attempt to filling this gap by proposing a specific economic model for the sports sector. This paper examines the data of sports industry covering the time span of 2012 to 2022 by using data mining technology for quantitative analyses. Deep learning algorithms and data mining techniques transform the gained information from sports industry databases into sophisticated economic models. The developed model then makes the efficient analysis of diverse datasets for underlying patterns and insights, crucial in realizing the economic trajectory of the industry. The findings of the study reveal the importance of sports industry for economic growth of China. Moreover, the application of deep learning algorithm highlights the importance of continuous learning and training on the economic data from the sports industry. It is, therefore, an entirely novel approach to build up an economic simulation framework using deep learning and data mining, tailored to the intricate dynamics of the sports industry.
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Despite outstanding improvements in research of sports industry, a significant gap prevails with regard to proper quantification of economic benefits of this industry. Therefore, the current research is an attempt to filling this gap by proposing a specific economic model for the sports sector. This paper examines the data of sports industry covering the time span of 2012 to 2022 by using data mining technology for quantitative analyses. Deep learning algorithms and data mining techniques transform the gained information from sports industry databases into sophisticated economic models. The developed model then makes the efficient analysis of diverse datasets for underlying patterns and insights, crucial in realizing the economic trajectory of the industry. The findings of the study reveal the importance of sports industry for economic growth of China. 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subjects Algorithms
Biology and Life Sciences
China
Computer and Information Sciences
Data analysis
Data Mining
Database industry
Decision making
Deep Learning
Economic analysis
Economic aspects
Economic development
Economic growth
Economic impact
Economic models
Evaluation
Forecasts and trends
Humans
Industrial development
Industry - economics
Learning algorithms
Machine learning
Marketing
Models, Economic
People and Places
Research and Analysis Methods
Social Sciences
Sports
Sports - economics
Strategic planning
Technology assessment
Trajectory analysis
Trends
title Unveiling the economic potential of sports industry in China: A data driven analysis
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