IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i20p9028-d1501587.html
   My bibliography  Save this article

Cultural Industry Agglomeration and Carbon Emission Performance: Empirical Analysis Based on 276 Cities in China

Author

Listed:
  • Tinglei Hao

    (School of Management, Wuhan Polytechnic University, Wuhan 430048, China)

  • Jiajie Ren

    (School of Management, Wuhan Polytechnic University, Wuhan 430048, China)

  • Chuanming Sun

    (National Research Center of Cultural Industries, Central China Normal University, Wuhan 430079, China)

  • Lu Chen

    (School of Management, Wuhan Polytechnic University, Wuhan 430048, China)

  • Tao Liu

    (National Research Center of Cultural Industries, Central China Normal University, Wuhan 430079, China)

Abstract

This study investigated the influence of cultural industry agglomeration on the energy carbon emission performance (CEP). Based on panel data from 276 cities in China, we used the Super-SBM model to measure the CEP. We then used the Tobit regression model to calculate the influence coefficient of cultural industry agglomeration and eight control variables on the CEP and analyzed the complex effects of cultural industry agglomeration on the CEP. The results showed that there is the phenomenon of “diseconomies of agglomeration” in cultural industry agglomeration, which cannot improve the CEP. For each unit of cultural industry agglomeration increase, the CEP decreases by 0.055; however, this phenomenon is not linear. Further research showed that the effects of cultural industry agglomeration showed a trend from good to inferior in the order of east, central, and west and did not improve with time. Finally, we used the panel quantile regression model and found that as the CEP levels rise, the negative impact of cultural industry agglomeration improves. Our research results show that strengthening the technical level to promote the upgrading of the cultural industry is the best way to achieve sustainable development. Governments at all levels should pay attention to the emission reduction potential of cultural industry agglomeration under high CEP levels and strengthen the benign agglomeration of the cultural industry.

Suggested Citation

  • Tinglei Hao & Jiajie Ren & Chuanming Sun & Lu Chen & Tao Liu, 2024. "Cultural Industry Agglomeration and Carbon Emission Performance: Empirical Analysis Based on 276 Cities in China," Sustainability, MDPI, vol. 16(20), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9028-:d:1501587
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/20/9028/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/20/9028/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Umar, Muhammad & Mirza, Nawazish & Hasnaoui, Jamila Abaidi & Rochoń, Małgorzata Porada, 2022. "The nexus of carbon emissions, oil price volatility, and human capital efficiency," Resources Policy, Elsevier, vol. 78(C).
    2. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    3. C. Cindy Fan & Allen J. Scott, 2003. "Industrial Agglomeration and Development: A Survey of Spatial Economic Issues in East Asia and a Statistical Analysis of Chinese Regions," Economic Geography, Taylor & Francis Journals, vol. 79(3), pages 295-319, July.
    4. Kunpeng Ai & Ning Xu, 2023. "Does Regional Integration Improve Carbon Emission Performance?—A Quasi-Natural Experiment on Regional Integration in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    5. Yang, Zikun & Zhang, Mingming & Liu, Liyun & Zhou, Dequn, 2022. "Can renewable energy investment reduce carbon dioxide emissions? Evidence from scale and structure," Energy Economics, Elsevier, vol. 112(C).
    6. Grebitus, Carola & Steiner, Bodo & Veeman, Michele M., 2016. "Paying for sustainability: A cross-cultural analysis of consumers’ valuations of food and non-food products labeled for carbon and water footprints," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 50-58.
    7. Erli Dan & Jianfei Shen & Xinyuan Zheng & Peng Liu & Ludan Zhang & Feiyu Chen, 2023. "Asset Structure, Asset Utilization Efficiency, and Carbon Emission Performance: Evidence from Panel Data of China’s Low-Carbon Industry," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    8. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    9. Liu, Xiaoxi & Razzaq, Asif & Shahzad, Mohsin & Irfan, Muhammad, 2022. "Technological changes, financial development and ecological consequences: A comparative study of developed and developing economies," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Haibo Chen & Jiawei Lu, 2023. "Does Cultural Agglomeration Affect Green Total Factor Productivity? Evidence from 279 Cities in China," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    11. Abdullah A. Aljughaiman & Ngan D. Cao & Mohammed S. Albarrak & Abdulateif A. Almulhim, 2024. "Influence of Cultural and Environmental Values of CEOs on Greenhouse Gas Emission Intensity," Sustainability, MDPI, vol. 16(2), pages 1-24, January.
    12. Wang, Yafei & Bai, Ying & Quan, Tianshu & Ran, Rong & Hua, Lei, 2023. "Influence and effect of industrial agglomeration on urban green total factor productivity—On the regulatory role of innovation agglomeration and institutional distance," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1158-1173.
    13. Wen, Yuyuan & Yu, Zilong & Xue, Jingjing & Liu, Yang, 2024. "How heterogeneous industrial agglomeration impacts energy efficiency subject to technological innovation:Evidence from the spatial threshold model," Energy Economics, Elsevier, vol. 136(C).
    14. 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.
    15. Polemis, Michael L. & Stengos, Thanasis & Tzeremes, Panayiotis & Tzeremes, Nickolaos G., 2021. "Quantile eco-efficiency estimation and convergence: A nonparametric frontier approach," Economics Letters, Elsevier, vol. 202(C).
    16. Guangliang Li & Chunlan Tan & Weikun Zhang & Wolin Zheng & Yong Liu, 2023. "Carbon Emission Efficiency, Technological Progress, and Fishery Scale Expansion: Evidence from Marine Fishery in China," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    2. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    3. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    4. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    5. Le Sun & Congmou Zhu & Shaofeng Yuan & Lixia Yang & Shan He & Wuyan Li, 2022. "Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emission Performance in China," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    6. Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    7. Can Zhang & Jixia Li, 2024. "The Impact of Official Promotion Incentives on Urban Ecological Welfare Performance and Its Spatial Effect," Sustainability, MDPI, vol. 16(7), pages 1-29, April.
    8. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    9. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    10. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    11. Shang, Hua & Jiang, Li & Pan, Xianyou & Pan, Xiongfeng, 2022. "Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 114(C).
    12. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    13. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    14. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    15. Chenchen Su & Jinchuan Shen & Fei Wang, 2024. "Can income growth and environmental improvements go hand in hand? An empirical study of Chinese agriculture," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(7), pages 321-333.
    16. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    17. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    18. Zhou, Lin & Fan, Jianshuang & Hu, Mingzhi & Yu, Xiaofen, 2024. "Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities," Energy Economics, Elsevier, vol. 133(C).
    19. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    20. Nguyen Thi Kim Lien & Luyen Le Anh, 2024. "Adopting SBM-Max and Super SBM-Max to Evaluate the Efficiency of Freight Transportation Arrangement Providers: A Study in Vietnam," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 15(1), pages 73-84.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9028-:d:1501587. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.