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Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model

Author

Listed:
  • Jian Wang

    (School of Business, Quzhou University, Kecheng District, Quzhou 324000, China
    E-Commerce Research Center, Pingxiang University, Anyuan District, Pingxiang 337055, China)

  • Jin-Chun Huang

    (School of Business, Quzhou University, Kecheng District, Quzhou 324000, China
    E-Commerce Research Center, Pingxiang University, Anyuan District, Pingxiang 337055, China)

  • Shan-Lin Huang

    (Department of Tourism Management, College of Economics and Management, Sanming University, Sanyuan District, Sanming 365004, China
    National Park Center, Sanming University, Sanyuan District, Sanming 365004, China)

  • Gwo-Hshiung Tzeng

    (Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, San Shia District, New Taipei 23741, Taiwan)

  • Ting Zhu

    (Department of Tourism Management, College of Economics and Management, Sanming University, Sanyuan District, Sanming 365004, China)

Abstract

Global warming and extreme weather have increased most people’s awareness of the problem of environmental destruction. In the domain of sustainable development, environmental governance has received considerable scholarly attention. However, protecting and improving the environment requires not only substantial capital investment but also cooperation among stakeholders. Therefore, based on the network structure of stakeholders, the best–worst method (BWM) and modified Vlsekriterijumska Optimizacija I Kompromisno Resenje method were combined to form an environmental co-governance assessment framework that can be used to evaluate the effects of various policies and identify strategies for further improvement through data analysis (henceforth the BWM-mV model). This mechanism is not only useful for evaluating the effectiveness of environmental governance policies but also for generating suggestions to enhance these policies. Hence, the BWM-mV model is particularly suitable for local governments with limited resources in time, money, or labor. Pingxiang City Government is currently subject to such limitations and was therefore selected as the subject of an empirical case study. The results of this study revealed that the aspects (i.e., criteria) the Pingxiang City Government should urgently improve on pertain to a high-quality information communication platform ( C 13 ) and smooth joint decision-making by stakeholders ( C 24 ).

Suggested Citation

  • Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4969-:d:550129
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    1. Athanasios Lapatinas & Anastasia Litina & Eftichios Sophocles Sartzetakis, 2019. "Environmental projects in the presence of corruption," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(1), pages 103-144, February.
    2. Sun, Chuanwang, 2015. "An empirical case study about the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 160(C), pages 383-389.
    3. Gupta, Himanshu, 2018. "Evaluating service quality of airline industry using hybrid best worst method and VIKOR," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 35-47.
    4. Chandra Prakash Garg & Archana Sharma, 2020. "Sustainable outsourcing partner selection and evaluation using an integrated BWM–VIKOR framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1529-1557, February.
    5. Bo-Wei Zhu & Jia-Rui Zhang & Gwo-Hshiung Tzeng & Shan-Lin Huang & Lei Xiong, 2017. "Public Open Space Development for Elderly People by Using the DANP-V Model to Establish Continuous Improvement Strategies towards a Sustainable and Healthy Aging Society," Sustainability, MDPI, vol. 9(3), pages 1-29, March.
    6. Xing Gao & Cheng Shi & Keyu Zhai, 2018. "An Evaluation of Environmental Governance in Urban China Based on a Hesitant Fuzzy Linguistic Analytic Network Process," IJERPH, MDPI, vol. 15(11), pages 1-20, November.
    7. Wynveen, Christopher J. & Sutton, Stephen G., 2015. "Engaging the public in climate change-related pro-environmental behaviors to protect coral reefs: The role of public trust in the management agency," Marine Policy, Elsevier, vol. 53(C), pages 131-140.
    8. Franco Ruzzenenti & Andreas Joseph & Elisa Ticci & Pietro Vozzella & Giampaolo Gabbi, 2015. "Interactions between Financial and Environmental Networks in OECD Countries," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    9. Du, Gang & Lin, Wei & Sun, Chuanwang & Zhang, Dingzhong, 2015. "Residential electricity consumption after the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 157(C), pages 276-283.
    10. Ruxi Wang & Frank Wijen & Pursey P.M.A.R. Heugens, 2018. "Government's green grip: Multifaceted state influence on corporate environmental actions in China," Strategic Management Journal, Wiley Blackwell, vol. 39(2), pages 403-428, February.
    11. Yuanxin Liu & FengYun Li & Yi Wang & Xinhua Yu & Jiahai Yuan & Yuwei Wang, 2018. "Assessing the Environmental Impact Caused by Power Grid Projects in High Altitude Areas Based on BWM and Vague Sets Techniques," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    12. Guilin Gao & Xueting Zeng & Chunjiang An & Lei Yu, 2018. "A Sustainable Industry-Environment Model for the Identification of Urban Environmental Risk to Confront Air Pollution in Beijing, China," Sustainability, MDPI, vol. 10(4), pages 1-22, March.
    13. Wen-Chih Yeh & Ming-Hsun Tseng & Chun-Chang Lee & Cheng Yu, 2020. "The Impact of Relationship Trust, Environmental Protection Awareness, and Regenerative Innovation on Environmental Performance: A Case Study of the Industrial Waste Industry," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
    14. Xin Duan & Shengli Dai & Rui Yang & Ziwei Duan & Yanhong Tang, 2020. "Environmental Collaborative Governance Degree of Government, Corporation, and Public," Sustainability, MDPI, vol. 12(3), pages 1-14, February.
    15. Evans Asante Boadi & Zheng He & Josephine Bosompem & Joy Say & Eric Kofi Boadi, 2019. "Let the Talk Count: Attributes of Stakeholder Engagement, Trust, Perceive Environmental Protection and CSR," SAGE Open, , vol. 9(1), pages 21582440198, January.
    16. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    17. Iuan-Yuan Lu & Tsuanq Kuo & Ting-Syuan Lin & Gwo-Hshiung Tzeng & Shan-Lin Huang, 2016. "Multicriteria Decision Analysis to Develop Effective Sustainable Development Strategies for Enhancing Competitive Advantages: Case of the TFT-LCD Industry in Taiwan," Sustainability, MDPI, vol. 8(7), pages 1-31, July.
    18. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    19. Meilin He & Laura Devine & Jun Zhuang, 2018. "Perspectives on Cybersecurity Information Sharing among Multiple Stakeholders Using a Decision‐Theoretic Approach," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 215-225, February.
    20. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    21. Lei Xiong & Cheng-Lein Teng & Bo-Wei Zhu & Gwo-Hshiung Tzeng & Shan-Lin Huang, 2017. "Using the D-DANP-mV Model to Explore the Continuous System Improvement Strategy for Sustainable Development of Creative Communities," IJERPH, MDPI, vol. 14(11), pages 1-37, October.
    22. Ju, Jingrui & Liu, Luning & Feng, Yuqiang, 2018. "Citizen-centered big data analysis-driven governance intelligence framework for smart cities," Telecommunications Policy, Elsevier, vol. 42(10), pages 881-896.
    23. Blanca L. Delgado-Márquez & J. Alberto Aragón-Correa & Eulogio Cordón-Pozo & Luis Enrique Pedauga, 2016. "Trust when financial implications are not the aim: the integration of sustainability into management education," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 17(6), pages 1172-1188, November.
    24. Schulz, Christopher & Martin-Ortega, Julia & Glenk, Klaus & Ioris, Antonio A.R., 2017. "The Value Base of Water Governance: A Multi-Disciplinary Perspective," Ecological Economics, Elsevier, vol. 131(C), pages 241-249.
    25. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
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