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Empirical Study on the Green Transformation of the Sports Industry Empowered by New Infrastructure from the Perspective of the Green Total Factor Productivity of the Sports Industry

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  • Yanmei Dong

    (College of Sports Industry and Leisure, Nanjing Sport Institute, Nanjing 210014, China)

Abstract

In this research, under the guidance of scientific and available principles, an evaluation index system for the green total factor productivity of new infrastructure construction and the sports industry was constructed. The evaluation was conducted using Stata16, the DEA-Solver PRO13 software, and GIS technology using the entropy weight method, super-efficiency SBM model, and other methods. The results indicated the following: First, the overall level of new infrastructure in China is low (mean 0.255), being slightly higher than that of information infrastructure (mean 0.230), innovation infrastructure (mean 0.190), and convergence infrastructure (mean 0.555). The level of information infrastructure, especially innovation infrastructure, in eastern China is much higher than that in central and western China, especially western China. Second, the sports industry in most Chinese provinces is effective in terms of technology and scale and is in a constant stage of scale return, while the remaining provinces are in a rising stage of scale return. The mixed efficiency in the sports industry of eastern China is at a higher level than its scale efficiency and pure technical efficiency, while the mixed efficiency levels in the sports industries of central and western China are greater than those of the pure technical efficiency but less than the scale efficiency. Meanwhile, the level of mixed efficiency in the sports industry of northeast China is far lower than that of its pure technology and scale efficiency. There is still room for improvement in the discharge of pollutants and labor practices in the sports industry, especially in the sports service industry. Third, the impact of the new infrastructure and its three subsystems on the sports industry is significantly positive at the 1% level. By region, the marginal effect of information infrastructure in eastern China is the largest (2.469), while the effect of innovation infrastructure in central China (5.113), western China (4.866), and northeast China (3.251) is the largest.

Suggested Citation

  • Yanmei Dong, 2022. "Empirical Study on the Green Transformation of the Sports Industry Empowered by New Infrastructure from the Perspective of the Green Total Factor Productivity of the Sports Industry," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10661-:d:898904
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    References listed on IDEAS

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    1. Mohsin, Muhammad & Hanif, Imran & Taghizadeh-Hesary, Farhad & Abbas, Qaiser & Iqbal, Wasim, 2021. "Nexus between energy efficiency and electricity reforms: A DEA-Based way forward for clean power development," Energy Policy, Elsevier, vol. 149(C).
    2. Jari Lyytimäki & Riina Antikainen & Joonas Hokkanen & Sirkka Koskela & Sirpa Kurppa & Riina Känkänen & Jyri Seppälä, 2018. "Developing Key Indicators of Green Growth," Sustainable Development, John Wiley & Sons, Ltd., vol. 26(1), pages 51-64, January.
    3. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    4. Amoako, Samuel & Insaidoo, Michael, 2021. "Symmetric impact of FDI on energy consumption: Evidence from Ghana," Energy, Elsevier, vol. 223(C).
    5. Liu, Hongwei & Yang, Ronglu & Wu, Jie & Chu, Junfei, 2021. "Total-factor energy efficiency change of the road transportation industry in China: A stochastic frontier approach," Energy, Elsevier, vol. 219(C).
    6. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    2. Mei Yang & Hongling Zhou & Yali Li & Jinyu Zhang, 2023. "Efficiency Evaluation and Influencing Factors of Sports Industry and Tourism Industry Convergence Based on China’s Provincial Data," Sustainability, MDPI, vol. 15(6), pages 1-23, March.

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