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How to improve the performance of China's energy-transport-economy-environment system: An analysis based on new strategy parallel-series input-output data envelopment analysis models

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  • Chen, Shanshan
  • Zhang, Ruchuan
  • Li, Peiwen
  • Li, Aijun

Abstract

To the best of our knowledge, all the existing input-output data envelopment analysis (IO-DEA) models adopt parallel structures, without further distinguishing two different production processes (interindustry transaction and value-added). In this regard, overlooking the differences between two production processes may obtain misleading results. To overcome the deficiency, this study develops a new parallel-series IO-DEA model to capture the complex relationships and interactions of two production processes. Furthermore, this study proposes a new framework to perform efficiency analysis and relative priority analysis. Empirically, this study focuses on the energy-transport-economy-environment system in China at national level and provincial level. Such work cannot be found in the existing studies. The main conclusions are summarized as follows. First, there are significant differences between two stages in efficiency-related measures, showing that our new parallel-series model can provide fresh insightful information. Second, China has experienced an overall efficiency regress of energy-transport-economy-environment system and such regress is mainly induced by value-added stage and two sectors (energy and economy sectors). Third, among all sectors, economy sector attracts the highest priority and then it is followed by transport sector. Finally, alternative strategies generate significant impacts on efficiency-related measures. Importantly, strategies tend to reduce overall efficiency, but well-suited one can improve efficiency for some decision-making units.

Suggested Citation

  • Chen, Shanshan & Zhang, Ruchuan & Li, Peiwen & Li, Aijun, 2023. "How to improve the performance of China's energy-transport-economy-environment system: An analysis based on new strategy parallel-series input-output data envelopment analysis models," Energy, Elsevier, vol. 281(C).
    • Handle: RePEc:eee:energy:v:281:y:2023:i:c:s0360544223016298
    DOI: 10.1016/j.energy.2023.128235
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    as
    1. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    2. Tenente, Marcos & Henriques, Carla & da Silva, Patrícia Pereira, 2020. "Eco-efficiency assessment of the electricity sector: Evidence from 28 European Union countries," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 293-314.
    3. Bai, Xue-jie & Zeng, Jin & Chiu, Yung-Ho, 2019. "Pre-evaluating efficiency gains from potential mergers and acquisitions based on the resampling DEA approach: Evidence from China's railway sector," Transport Policy, Elsevier, vol. 76(C), pages 46-56.
    4. Henriques, C.O. & Gouveia, C.M. & Tenente, M. & da Silva, P.P., 2022. "Employing Value-Based DEA in the eco-efficiency assessment of the electricity sector," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 826-844.
    5. Zhang, Ruchuan & Wei, Qian & Li, Aijun & Ren, LiYing, 2022. "Measuring efficiency and technology inequality of China's electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models," Energy, Elsevier, vol. 246(C).
    6. Fenfen Li & Bo Dai & Qifan Wu, 2021. "Dynamic Green Growth Assessment of China’s Industrial System with an Improved SBM Model and Global Malmquist Index," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    7. Heydari, Chiman & Omrani, Hashem & Taghizadeh, Rahim, 2020. "A fully fuzzy network DEA-Range Adjusted Measure model for evaluating airlines efficiency: A case of Iran," Journal of Air Transport Management, Elsevier, vol. 89(C).
    8. Wei Wei & Shuangying Ding & Silin Zheng & Jingjing Ma & Tong Niu & Jinkai Li, 2021. "Environmental Efficiency Evaluation of China’s Power Industry Based on the Two-Stage Network Slack-Based Measure Model," IJERPH, MDPI, vol. 18(23), pages 1-21, November.
    9. Xu, Bin & Chen, Jianbao, 2021. "How to achieve a low-carbon transition in the heavy industry? A nonlinear perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    10. Zha, Jianping & Tan, Ting & Fan, Rong & Xu, Han & Ma, Siqi, 2020. "How to reduce energy intensity to achieve sustainable development of China's transport sector? A cross-regional comparison analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    11. Duygun, Meryem & Prior, Diego & Shaban, Mohamed & Tortosa-Ausina, Emili, 2016. "Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach," Omega, Elsevier, vol. 60(C), pages 2-14.
    12. Xu, Bin & Luo, Yuemei & Xu, Renjing & Chen, Jianbao, 2021. "Exploring the driving forces of distributed energy resources in China: Using a semiparametric regression model," Energy, Elsevier, vol. 236(C).
    13. Kao, Chiang, 2018. "A classification of slacks-based efficiency measures in network data envelopment analysis with an analysis of the properties possessed," European Journal of Operational Research, Elsevier, vol. 270(3), pages 1109-1121.
    14. Jiayu Wang & Ke Wang & Xunpeng Shi & Yi-Ming Wei, 2019. "Spatial heterogeneity and driving forces of environmental productivity growth in China: Would it help to switch pollutant discharge fees to environmental taxes?," CEEP-BIT Working Papers 123, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    15. Yun Cheng & Huan-Li Gao, 2015. "Matrix-Type Network DEA Model with Its Application Based on Input-Output Tables," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, June.
    16. Kai He & Nan Zhu & Wu Jiang & Chuanjin Zhu, 2022. "Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    17. Mahlberg, Bernhard & Luptacik, Mikulas, 2014. "Eco-efficiency and eco-productivity change over time in a multisectoral economic system," European Journal of Operational Research, Elsevier, vol. 234(3), pages 885-897.
    18. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    19. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2016. "Has airline efficiency affected by the inclusion of aviation into European Union Emission Trading Scheme? Evidences from 22 airlines during 2008–2012," Energy, Elsevier, vol. 96(C), pages 8-22.
    20. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    21. Jose L. Zofio & Angel M. Prieto, 2007. "Measuring Productive Efficiency in Input-Output Models by Means of Data Envelopment Analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 21(4), pages 519-537.
    22. Prieto, Angel M. & Zofio, Jose L., 2007. "Network DEA efficiency in input-output models: With an application to OECD countries," European Journal of Operational Research, Elsevier, vol. 178(1), pages 292-304, April.
    23. Yu, Hang & Zhang, Yahua & Zhang, Anming & Wang, Kun & Cui, Qiang, 2019. "A comparative study of airline efficiency in China and India: A dynamic network DEA approach," Research in Transportation Economics, Elsevier, vol. 76(C).
    24. Mallikarjun, Sreekanth, 2015. "Efficiency of US airlines: A strategic operating model," Journal of Air Transport Management, Elsevier, vol. 43(C), pages 46-56.
    25. Xu, Renjing & Xu, Bin, 2022. "Exploring the effective way of reducing carbon intensity in the heavy industry using a semiparametric econometric approach," Energy, Elsevier, vol. 243(C).
    26. 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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