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Examining energy eco-efficiency in China's logistics industry

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  • Yu, Xiaohong
  • Xu, Haiyan
  • Lou, Wengao
  • Xu, Xun
  • Shi, Victor

Abstract

Carbon dioxide (CO2) emission significantly affects sustainability efforts, calling for improvements in energy eco-efficiency (EEE). In this study, we use three methods—input–output indicators, projection pursuit regressions, and neural networks—to investigate the CO2 emission characteristics of the logistics industry in China and its provinces from 2010 to 2019. We find influential factors of carbon emissions and their corresponding efficiencies in various provinces of China. Our results reveal excess inputs and deficient outputs and the relationship between economic development levels and the environmental quality. Based on the results, we provide technical measures and managerial implications for effectively reducing CO2 emissions and improving EEE.

Suggested Citation

  • Yu, Xiaohong & Xu, Haiyan & Lou, Wengao & Xu, Xun & Shi, Victor, 2023. "Examining energy eco-efficiency in China's logistics industry," International Journal of Production Economics, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:proeco:v:258:y:2023:i:c:s0925527323000294
    DOI: 10.1016/j.ijpe.2023.108797
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    1. Muhammed Ashiq Villanthenkodath & Mohini Gupta & Seema Saini & Malayaranjan Sahoo, 2021. "Impact of Economic Structure on the Environmental Kuznets Curve (EKC) hypothesis in India," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-17, December.
    2. Halkos, George Emm. & Tzeremes, Nickolaos G., 2009. "Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis," Ecological Economics, Elsevier, vol. 68(7), pages 2168-2176, May.
    3. Kwon, He-Boong, 2017. "Exploring the predictive potential of artificial neural networks in conjunction with DEA in railroad performance modeling," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 159-170.
    4. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    5. Joseph Sarkis & Srinivas Talluri, 2004. "Ecoefficiency Measurement Using Data Envelopment Analysis: Research And Practitioner Issues," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 91-123.
    6. Brantley Liddle, 2011. "Consumption-Driven Environmental Impact and Age Structure Change in OECD Countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(30), pages 749-770.
    7. Kaika, Dimitra & Zervas, Efthimios, 2013. "The Environmental Kuznets Curve (EKC) theory—Part A: Concept, causes and the CO2 emissions case," Energy Policy, Elsevier, vol. 62(C), pages 1392-1402.
    8. Haein Kim & Minsang Kim & Hyunggeun Kim & Sangkyu Park, 2020. "Decomposition Analysis of CO 2 Emission from Electricity Generation: Comparison of OECD Countries before and after the Financial Crisis," Energies, MDPI, vol. 13(14), pages 1-16, July.
    9. Natalia Porto & Matías Ciaschi, 2021. "Reformulating the tourism-extended environmental Kuznets curve: A quantile regression analysis under environmental legal conditions," Tourism Economics, , vol. 27(5), pages 991-1014, August.
    10. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
    11. Honma, Satoshi & Hu, Jin-Li, 2008. "Total-factor energy efficiency of regions in Japan," Energy Policy, Elsevier, vol. 36(2), pages 821-833, February.
    12. Visani, Franco & Boccali, Filippo, 2020. "Purchasing price assessment of leverage items: A Data Envelopment Analysis approach," International Journal of Production Economics, Elsevier, vol. 223(C).
    13. Lolli, F. & Gamberini, R. & Regattieri, A. & Balugani, E. & Gatos, T. & Gucci, S., 2017. "Single-hidden layer neural networks for forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 116-128.
    14. Zhu Liu & Dabo Guan & Wei Wei & Steven J. Davis & Philippe Ciais & Jin Bai & Shushi Peng & Qiang Zhang & Klaus Hubacek & Gregg Marland & Robert J. Andres & Douglas Crawford-Brown & Jintai Lin & Hongya, 2015. "Reduced carbon emission estimates from fossil fuel combustion and cement production in China," Nature, Nature, vol. 524(7565), pages 335-338, August.
    15. George Vlontzos & Spyros Niavis & Panos Pardalos, 2017. "Testing for Environmental Kuznets Curve in the EU Agricultural Sector through an Eco-(in)Efficiency Index," Energies, MDPI, vol. 10(12), pages 1-15, December.
    16. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    17. Pasten, Roberto & Figueroa B., Eugenio, 2012. "The Environmental Kuznets Curve: A Survey of the Theoretical Literature," International Review of Environmental and Resource Economics, now publishers, vol. 6(3), pages 195-224, December.
    18. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    19. Shahbaz, Muhammad & Nasir, Muhammad Ali & Roubaud, David, 2018. "Environmental degradation in France: The effects of FDI, financial development, and energy innovations," Energy Economics, Elsevier, vol. 74(C), pages 843-857.
    20. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Lin Qiu & Can-can Liu, 2017. "The Annual Maximum Flood Peak Discharge Forecasting Using Hermite Projection Pursuit Regression with SSO and LS Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 461-477, January.
    21. 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.
    22. Mette Asmild & Joseph Paradi & Vanita Aggarwall & Claire Schaffnit, 2004. "Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry," Journal of Productivity Analysis, Springer, vol. 21(1), pages 67-89, January.
    23. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    24. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    25. Damberg, Sarah V. & Hartmann, Julia & Heese, H. Sebastian, 2022. "Does bad press help or hinder sustainable supply chain management? An empirical investigation of US-based corporations," International Journal of Production Economics, Elsevier, vol. 249(C).
    26. Raul Arango Miranda & Robert Hausler & Rabindranarth Romero Lopez & Mathias Glaus & Jose Ramon Pasillas-Diaz, 2020. "Testing the Environmental Kuznets Curve Hypothesis in North America’s Free Trade Agreement (NAFTA) Countries," Energies, MDPI, vol. 13(12), pages 1-13, June.
    27. Atanu Sengupta & Sanjoy De, 2020. "Assessing Performance of Banks in India Fifty Years After Nationalization," India Studies in Business and Economics, Springer, number 978-981-15-4435-4, September.
    28. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    29. Feng Ren & Xin Yu & Quan Li, 2020. "Study on ETFEE in the BTH Region Based on the Window-SBM-Undesirable Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-10, October.
    30. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    31. 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.
    32. Song, Malin & Zheng, Wanping & Wang, Zeya, 2016. "Environmental efficiency and energy consumption of highway transportation systems in China," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 441-449.
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