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A case study in China of the influence mechanism of industrial park efficiency using DEA

Author

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  • Yafen He

    (Jiangxi University of Finance and Economics)

  • Zhenhong Zhu

    (Jiangxi University of Finance and Economics)

  • Hualin Xie

    (Jiangxi University of Finance and Economics)

  • Xinmin Zhang

    (Jiangxi University of Finance and Economics)

  • Meiqi Sheng

    (Jiangxi University of Finance and Economics)

Abstract

Industrial parks are important drivers of economic growth and development. In an increasingly globalized economy, inefficient park development hinders high-quality, sustainable regional and national growth. The transformation and upgrading of industrial parks requires an understanding of the influence mechanism of industrial park efficiency. This study provided a theoretical analysis of the impact of land supply and price, park type, management level, and economic location on industrial parks, and clarified the effect of these factors on industrial park efficiency. Using the case study of Jiangxi Province, a typical underdeveloped area in China, we measured the comprehensive efficiency (CE) of 36 industrial parks from 2010 to 2018 employing data envelopment analysis (DEA). Our study’s findings show that the average CE of industrial parks in Jiangxi Province is low, as most of the parks are inefficient and technical efficiency is a shortcoming. The efficiency of national industrial parks (0.785) is generally higher than that of provincial industrial parks (0.516), whereas the efficiency of the high-tech development zones (0.673) is generally higher than that of the economic–technological development zones (0.603). Industrial parks in prefecture-level cities with superior economic locations are more efficient. Among the 36 industrial parks studied, 14 demonstrated inefficient use of funds, and 10 were provincial industrial parks. We found that the supply of low-priced land affects firms’ investment behavior through the effect of price distortion, which leads to inefficiency. Our study’s findings have implications for policy, practice, theory, and subsequent research for the improvement of industrial park efficiency.

Suggested Citation

  • Yafen He & Zhenhong Zhu & Hualin Xie & Xinmin Zhang & Meiqi Sheng, 2023. "A case study in China of the influence mechanism of industrial park efficiency using DEA," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 7261-7280, July.
    • Handle: RePEc:spr:endesu:v:25:y:2023:i:7:d:10.1007_s10668-022-02290-x
    DOI: 10.1007/s10668-022-02290-x
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    as
    1. Tanaka, Kenta & Managi, Shunsuke, 2021. "Industrial agglomeration effect for energy efficiency in Japanese production plants," Energy Policy, Elsevier, vol. 156(C).
    2. Federica Acerbi & Claudio Sassanelli & Sergio Terzi & Marco Taisch, 2021. "A Systematic Literature Review on Data and Information Required for Circular Manufacturing Strategies Adoption," Sustainability, MDPI, vol. 13(4), pages 1-26, February.
    3. Sun, Yifan & Ma, Anbing & Su, Haorui & Su, Shiliang & Chen, Fei & Wang, Wen & Weng, Min, 2020. "Does the establishment of development zones really improve industrial land use efficiency? Implications for China’s high-quality development policy," Land Use Policy, Elsevier, vol. 90(C).
    4. Dursun, Mehtap & Goker, Nazli & Tulek, Burcu Deniz, 2019. "Efficiency analysis of organized industrial zones in Eastern Black Sea Region of Turkey," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    5. Takayabu, Hirotaka, 2020. "CO2 mitigation potentials in manufacturing sectors of 26 countries," Energy Economics, Elsevier, vol. 86(C).
    6. Richard E. Baldwin, 2011. "Multilateralising Regionalism: Spaghetti Bowls as Building Blocks on the Path to Global Free Trade," Chapters, in: Miroslav N. Jovanović (ed.), International Handbook on the Economics of Integration, Volume I, chapter 2, Edward Elgar Publishing.
    7. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    8. Devereux, Michael P. & Lockwood, Ben & Redoano, Michela, 2008. "Do countries compete over corporate tax rates?," Journal of Public Economics, Elsevier, vol. 92(5-6), pages 1210-1235, June.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Yan, Siqi & Peng, Jianchao & Wu, Qun, 2020. "Exploring the non-linear effects of city size on urban industrial land use efficiency: A spatial econometric analysis of cities in eastern China," Land Use Policy, Elsevier, vol. 99(C).
    11. Michael T. Peddle, 1993. "Planned Industrial and Commercial Developments in the United States: A Review of the History, Literature, and Empirical Evidence Regarding Industrial Parks and Research Parks," Economic Development Quarterly, , vol. 7(1), pages 107-124, February.
    12. Cordero, Rene, 1990. "The measurement of innovation performance in the firm: An overview," Research Policy, Elsevier, vol. 19(2), pages 185-192, April.
    13. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    14. Zhang, Bin & Luo, Yuan & Chiu, Yung-Ho, 2019. "Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 2-9.
    15. Hu, Yong & Fisher-Vanden, Karen & Su, Baozhong, 2020. "Technological spillover through industrial and regional linkages: Firm-level evidence from China," Economic Modelling, Elsevier, vol. 89(C), pages 523-545.
    16. Kahn, Matthew E. & Sun, Weizeng & Wu, Jianfeng & Zheng, Siqi, 2021. "Do political connections help or hinder urban economic growth? Evidence from 1,400 industrial parks in China," Journal of Urban Economics, Elsevier, vol. 121(C).
    17. Rui António Rodigues Ramos & Fernando Pereira Fonseca, 2016. "A methodology to identify a network of industrial parks in the Ave valley, Portugal," European Planning Studies, Taylor & Francis Journals, vol. 24(10), pages 1844-1862, October.
    18. Zhenshan Yang & Gaojian Hao & Zhe Cheng, 2018. "Investigating operations of industrial parks in Beijing: efficiency at different stages," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 31(1), pages 755-777, January.
    19. Lu, Shenghua & Wang, Hui, 2020. "Local economic structure, regional competition and the formation of industrial land price in China: Combining evidence from process tracing with quantitative results," Land Use Policy, Elsevier, vol. 97(C).
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    Cited by:

    1. Zhu Li & Jianhe Ding & Tianqi Tao & Shulian Wang & Kewu Pi & Wen Xiong, 2024. "Novel Evaluation Method for Cleaner Production Audit in Industrial Parks: Case of a Park in Central China," Sustainability, MDPI, vol. 16(6), pages 1-18, March.

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