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Collaborative Management of a Sustainable Supply Chain in a Water Diversion Project

Author

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  • Meng Liu

    (University of Shanghai for Science and Technology)

  • Wenwen Ding

    (North China University of Water Resources and Electric Power)

  • Yali Lu

    (North China University of Water Resources and Electric Power)

Abstract

Measuring the level of collaboration in the sustainable supply chain (SSC) of water diversion projects is of great value to the sustainable operation of the project. To this end, a scientific and reasonable collaboration measurement method must be developed. Given the economic, environmental and social benefits of water diversion projects and based on the theory of the SCC, an order parameter index system for collaboration measurement was constructed in this study. The DEMATEL and analytic network process methods were used to compute the local and global weights of each order parameter. A total of 161 valid questionnaires were collected from residents along the middle route of the South-to-North Water Diversion Project (SNWDP) to measure the collaboration on this project from 2018 to 2020. The results showed that the orderliness of the four flow subsystems of the middle route of the SNWDP increased annually. Compared with the other three flow subsystems, the knowledge flow subsystem showed a lower level of orderliness, suggesting that communication and exchanges among people along the route should be strengthened. These findings can help identify the weak link in the collaborative management of the SSC of water diversion projects and improve collaboration efforts in a targeted manner.

Suggested Citation

  • Meng Liu & Wenwen Ding & Yali Lu, 2022. "Collaborative Management of a Sustainable Supply Chain in a Water Diversion Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2665-2683, June.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:8:d:10.1007_s11269-022-03168-3
    DOI: 10.1007/s11269-022-03168-3
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    References listed on IDEAS

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    1. Li Hongyan, 2017. "Evolutionary Game Analysis of Emergency Management of the Middle Route of South-to-North Water Diversion Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2777-2789, July.
    2. Wenquan Gu & Dongguo Shao & Xuezhi Tan & Chen Shu & Zhen Wu, 2017. "Simulation and Optimization of Multi-Reservoir Operation in Inter-Basin Water Transfer System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3401-3412, September.
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    4. Nicolas Pirsoul & Maria Armoudian, 2019. "Deliberative Democracy and Water Management in New Zealand: a Critical Approach to Collaborative Governance and Co-Management Initiatives," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4821-4834, November.
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    6. Zhisong Chen & Huimin Wang & Xiangtong Qi, 2013. "Pricing and Water Resource Allocation Scheme for the South-to-North Water Diversion Project in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1457-1472, March.
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    Cited by:

    1. Zhe Cheng & Yuntong Zhao & Tao Song & Le Cheng & Wenbin Wang, 2023. "White Elephant or Golden Goose? An Assessment of Middle Route of the South-to-North Water Diversion Project from the Perspective of Regional Water Use Efficiency," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 819-834, January.
    2. Qingsheng Zhu & Kai Gao & Jia-Bao Liu, 2023. "Cloud model for new energy vehicle supply chain management based on growth expectation," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-23, July.

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