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An Innovative Double-Frontier Approach to Measure Sustainability Efficiency Based on an Energy Use and Operations Management Perspective

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  • Linyan Zhang

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China
    Beijing Key Lab of Green Development Decision Based on Big Data, Beijing 100192, China)

  • Chunhao Xu

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China)

  • Jian Zhang

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China
    Beijing Key Lab of Green Development Decision Based on Big Data, Beijing 100192, China)

  • Bingyin Lei

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China)

  • Anke Xie

    (Yunnan Key Laboratory of Blockchain Application Technology, Kunming 650233, China
    Yunnan Innovation Institute, Beihang University, Kunming 650233, China)

  • Ning Shen

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China)

  • Yujie Li

    (School of Economics and Management, Beijing Information Science & Technology University, Beijing 100192, China
    Research Center for Knowledge Management, Beijing 100192, China)

  • Kaiye Gao

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China
    School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
    Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong 999077, China)

Abstract

China’s economic development has achieved great success in recent years, but the problems of energy scarcity and environmental pollution have become increasingly serious. To enhance the reliability and efficiency between energy, the environment and the economy, sustainable development is an inevitable choice. In the context of measuring sustainability efficiency, a network data envelopment analysis model is proposed to formulate the two-stage process of energy use and operations management. A double frontier is derived to optimize the available energy for sustainable development. Due to nonlinearity, previous linear methods are not directly applicable to identify the double frontier and calculate stage efficiencies for inefficient decision-making units. To address this problem, this study develops the primal-dual relationship between multiplicative and envelopment network models based on the Lagrange duality principle of parametric linear programming. The newly developed approach is used to evaluate the sustainability efficiency of 30 administrative regions in China. The results show that insufficient sustainability efficiency is a systemic problem. Different regions should take different measures to conserve energy and reduce pollutant emissions for sustainable development. To increase sustainability efficiency, regions should support energy-saving and emission-reducing technologies in production processes and strengthen their capacity for technological innovation. Compared with energy use efficiency, operations management efficiency in China has a wider range of changes. During the operations management stage, there is not much difference between the capacity and quantity of each region. Based on benchmark regions at the efficiency frontier, there is an opportunity to improve operations management in the near future. Blockchain technology can effectively improve energy allocation efficiency.

Suggested Citation

  • Linyan Zhang & Chunhao Xu & Jian Zhang & Bingyin Lei & Anke Xie & Ning Shen & Yujie Li & Kaiye Gao, 2024. "An Innovative Double-Frontier Approach to Measure Sustainability Efficiency Based on an Energy Use and Operations Management Perspective," Energies, MDPI, vol. 17(16), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:3972-:d:1453877
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    References listed on IDEAS

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    1. Wu, Jie & Zhu, Qingyuan & Ji, Xiang & Chu, Junfei & Liang, Liang, 2016. "Two-stage network processes with shared resources and resources recovered from undesirable outputs," European Journal of Operational Research, Elsevier, vol. 251(1), pages 182-197.
    2. John S. Liu & Louis Y. Y. Lu & Wen-Min Lu, 2016. "Research Fronts and Prevailing Applications in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 543-574, Springer.
    3. 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.
    4. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    5. Chen, Yao & Cook, Wade D. & Kao, Chiang & Zhu, Joe, 2013. "Network DEA pitfalls: Divisional efficiency and frontier projection under general network structures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 507-515.
    6. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    7. Zhang, Linyan & Chen, Yao, 2018. "Equivalent solutions to additive two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1189-1191.
    8. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.
    9. Chen, Yao & Cook, Wade D. & Zhu, Joe, 2010. "Deriving the DEA frontier for two-stage processes," European Journal of Operational Research, Elsevier, vol. 202(1), pages 138-142, April.
    10. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "DEA-like models for the efficiency evaluation of hierarchically structured units," European Journal of Operational Research, Elsevier, vol. 154(2), pages 465-476, April.
    11. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    12. Oskar Juszczyk & Khuram Shahzad, 2022. "Blockchain Technology for Renewable Energy: Principles, Applications and Prospects," Energies, MDPI, vol. 15(13), pages 1-24, June.
    13. Lim, Sungmook & Zhu, Joe, 2016. "A note on two-stage network DEA model: Frontier projection and duality," European Journal of Operational Research, Elsevier, vol. 248(1), pages 342-346.
    14. Marco Schletz & Ana Cardoso & Gabriela Prata Dias & Søren Salomo, 2020. "How Can Blockchain Technology Accelerate Energy Efficiency Interventions? A Use Case Comparison," Energies, MDPI, vol. 13(22), pages 1-23, November.
    15. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
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