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Efficiency Evaluation of a Forestry Green Economy under a Multi-Dimensional Output Benefit in China—Based on Evidential Reasoning and the Cross Efficiency Model

Author

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  • Yan Huang

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    The Collective Forestry Reform and Development Research Center of New Types of Think Tanks with Universities in Fujian, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Xiao He

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    The Collective Forestry Reform and Development Research Center of New Types of Think Tanks with Universities in Fujian, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Shizhen He

    (School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    The Collective Forestry Reform and Development Research Center of New Types of Think Tanks with Universities in Fujian, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Yongwu Dai

    (School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    The Collective Forestry Reform and Development Research Center of New Types of Think Tanks with Universities in Fujian, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

Abstract

The efficiency evaluation of forestry green economy development is related to the direction of forestry development and plays an important role in balancing the economic and environmental issues within that forestry development. The existing research faces three challenges: first, the output indicator is singular; second, the perspective of a self-assessment is extremely limited; and third, the multi perspective fusion method is not in line with the mechanism of the cross efficiency evaluation model. To address these challenges and the characteristics of forestry development output, we constructed multi-level output indicators from four aspects: ecology, economy, society, and sustainability and used evidence reasoning to combine the output indicators. Based on the perspective of a cross evaluation among peers, four different cross efficiency values are defined from the evaluation relationship between the different decision-making units to obtain economic–aggressive, social–neutral, ecological–benevolent, sustainable–neutral, and comprehensive–neutral cross efficiencies. According to the relationship between self- and cross evaluation, an order conditional entropy cross efficiency aggregation model has been proposed and used to analyze the development efficiency of the forestry green economy in 31 Chinese provinces in 2019. Considering the uneven distribution of the forestry resources in China, the development in the 31 provinces and cities is divided into four types by discussing the relationship between the output indicators and efficiency, while the reasons for the unbalanced development and the poor comprehensive development are discussed according to five cross efficiencies.

Suggested Citation

  • Yan Huang & Xiao He & Shizhen He & Yongwu Dai, 2022. "Efficiency Evaluation of a Forestry Green Economy under a Multi-Dimensional Output Benefit in China—Based on Evidential Reasoning and the Cross Efficiency Model," Sustainability, MDPI, vol. 14(21), pages 1-25, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13881-:d:953192
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    References listed on IDEAS

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    1. Chen, Lei & Wang, Ying-Ming, 2020. "DEA target setting approach within the cross efficiency framework," Omega, Elsevier, vol. 96(C).
    2. 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.
    3. Y M Wang & S Wang, 2013. "Approaches to determining the relative importance weights for cross-efficiency aggregation in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(1), pages 60-69, January.
    4. Yang, Jian-Bo, 2001. "Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties," European Journal of Operational Research, Elsevier, vol. 131(1), pages 31-61, May.
    5. Yang, Guo-liang & Yang, Jian-bo & Liu, Wen-bin & Li, Xiao-xuan, 2013. "Cross-efficiency aggregation in DEA models using the evidential-reasoning approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 393-404.
    6. Kallio, A. Maarit I. & Hänninen, Riitta & Vainikainen, Nina & Luque, Sandra, 2008. "Biodiversity value and the optimal location of forest conservation sites in Southern Finland," Ecological Economics, Elsevier, vol. 67(2), pages 232-243, September.
    7. Yang, Feng & Ang, Sheng & Xia, Qiong & Yang, Chenchen, 2012. "Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis," European Journal of Operational Research, Elsevier, vol. 223(2), pages 483-488.
    8. Lisa Reyes Mason & Colleen Cummings Melton & Darian Gray & Andrea L. Swallow, 2022. "Climate Change, Social Work, and the Transition Away from Fossil Fuels: A Scoping Review," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    9. Lee, Chien-Chiang & Wang, Chih-Wei & Ho, Shan-Ju, 2022. "The dimension of green economy: Culture viewpoint," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 122-138.
    10. Markowski-Lindsay, Marla & Borsuk, Mark E. & Butler, Brett J. & Duveneck, Matthew J. & Holt, Jonathan & Kittredge, David B. & Laflower, Danelle & MacLean, Meghan Graham & Orwig, David & Thompson, Jona, 2020. "Compounding the Disturbance: Family Forest Owner Reactions to Invasive Forest Insects," Ecological Economics, Elsevier, vol. 167(C).
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