IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2018i1p6-d191919.html
   My bibliography  Save this article

A Management and Environmental Performance Evaluation of China’s Family Farms Using an Ultimate Comprehensive Cross-Efficiency Model (UCCE)

Author

Listed:
  • Yinsheng Yang

    (College of Biological and Agricultural Engineering, Jilin University, Changchun 130020, China)

  • Qianwei Zhuang

    (College of Biological and Agricultural Engineering, Jilin University, Changchun 130020, China)

  • Guangdong Tian

    (Transportation College, Jilin University, Changchun 130020, China)

  • Silin Wei

    (College of Biological and Agricultural Engineering, Jilin University, Changchun 130020, China)

Abstract

Family farm emerged as a new form of agricultural production organization in China in recent years. For the purpose of sustainable development, decision-makers, such as farm owners and policy makers, require the precise information of a family farm’s state of operation to adopt measures for management improvement and agricultural contamination reduction. Considering this, we established two evaluation systems for the measurement of family farms’ management and environmental performance. As demonstrated in several recent studies, data envelopment analysis (DEA) cross efficiency is a useful approach for evaluating and comparing the performance of decision-making units (DMUs). Regarding family farms’ performance evaluation issues, we modified the traditional average cross-efficiency method to be the ultimate comprehensive cross-efficiency approach with the integration of two statistical quantities based on the full consideration of family farms’ unique features, such as vulnerability and seasonality, resulting from the influence of natural and social factors. Our proposed approach presents more excellent characteristics compared with CCR efficiency and average cross efficiency. Several conclusions regarding the operation of China’s family farms are drawn: (i) there is weak positive correlation between family farms’ management and environmental performance; (ii) there is an increasing trend for both management and environmental efficiency, along with the augmentation of the utilized agricultural area of family farms, and management performance is therefore more significant; (iii) demand for timely technological instruction to improve family farms’ management efficiency is expressed by farm owners who are willing to expand; (iv) to improve family farms’ environmental performance, several measures—such as introducing biotechnology, providing subsidies, and environmental education for farmers—should be adopted.

Suggested Citation

  • Yinsheng Yang & Qianwei Zhuang & Guangdong Tian & Silin Wei, 2018. "A Management and Environmental Performance Evaluation of China’s Family Farms Using an Ultimate Comprehensive Cross-Efficiency Model (UCCE)," Sustainability, MDPI, vol. 11(1), pages 1-25, December.
  • Handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:6-:d:191919
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/1/6/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/1/6/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Yang & Zhang, Xiao & Wu, Lei & Yin, Shijiu & Lu, Jiao, 2017. "Resource basis, ecosystem and growth of grain family farm in China: Based on rough set theory and hierarchical linear model," Agricultural Systems, Elsevier, vol. 154(C), pages 157-167.
    2. Jintao Zhan & Xu Tian & Yanyuan Zhang & Xinglong Yang & Zhongqiong Qu & Tao Tan, 2017. "The Effects of Agricultural R&D on Chinese Agricultural Productivity Growth: New Evidence of Convergence and Implications for Agricultural R&D Policy," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 65(3), pages 453-475, September.
    3. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    4. 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.
    5. Hédi Essid & Janet Ganouati & Stephane Vigeant, 2018. "A mean-maverick game cross-efficiency approach to portfolio selection: An application to Paris stock exchange," Post-Print hal-01916529, HAL.
    6. 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.
    7. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2018. "A performance-based subsidy allocation of ferry transportation: A data envelopment approach," Transport Policy, Elsevier, vol. 68(C), pages 13-19.
    8. Graeub, Benjamin E. & Chappell, M. Jahi & Wittman, Hannah & Ledermann, Samuel & Kerr, Rachel Bezner & Gemmill-Herren, Barbara, 2016. "The State of Family Farms in the World," World Development, Elsevier, vol. 87(C), pages 1-15.
    9. Nikolaou, Paraskevas & Dimitriou, Loukas, 2018. "Evaluation of road safety policies performance across Europe: Results from benchmark analysis for a decade," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 232-246.
    10. da Silva e Souza, Geraldo & Gomes, Eliane Gonçalves, 2015. "Management of agricultural research centers in Brazil: A DEA application using a dynamic GMM approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 819-824.
    11. Burak R. Uras & Ping Wang, 2017. "Production Flexibility, Misallocation and Total Factor Productivity," NBER Working Papers 23970, National Bureau of Economic Research, Inc.
    12. D K Despotis, 2002. "Improving the discriminating power of DEA: focus on globally efficient units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(3), pages 314-323, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nan Chen & Xinglong Yang & Nicola Shadbolt, 2020. "The Balanced Scorecard as a Tool Evaluating the Sustainable Performance of Chinese Emerging Family Farms—Evidence from Jilin Province in China," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
    2. Zhiping Huang & Tianran Wang & Na Li, 2022. "Reciprocal and Symbiotic: Family Farms’ Operational Performance and Long-Term Cooperation of Entities in the Agricultural Industrial Chain—From the Evidence of Xinjiang in China," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    3. Yu, Peiheng & Fennell, Shailaja & Chen, Yiyun & Liu, Hui & Xu, Lu & Pan, Jiawei & Bai, Shaoyun & Gu, Shixiang, 2022. "Positive impacts of farmland fragmentation on agricultural production efficiency in Qilu Lake watershed: Implications for appropriate scale management," Land Use Policy, Elsevier, vol. 117(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feng Li & Han Wu & Qingyuan Zhu & Liang Liang & Gang Kou, 2021. "Data envelopment analysis cross efficiency evaluation with reciprocal behaviors," Annals of Operations Research, Springer, vol. 302(1), pages 173-210, July.
    2. Dai, Qianzhi & Li, Yongjun & Lei, Xiyang & Wu, Dengsheng, 2021. "A DEA-based incentive approach for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 292(2), pages 675-686.
    3. Carrillo, Marianela & Jorge, Jesús M., 2018. "Integrated approach for computing aggregation weights in cross-efficiency evaluation," Operations Research Perspectives, Elsevier, vol. 5(C), pages 256-264.
    4. Lei Chen & Ying-Ming Wang & Yan Huang, 2020. "Cross-efficiency aggregation method based on prospect consensus process," Annals of Operations Research, Springer, vol. 288(1), pages 115-135, May.
    5. Ramin Gharizadeh Beiragh & Reza Alizadeh & Saeid Shafiei Kaleibari & Fausto Cavallaro & Sarfaraz Hashemkhani Zolfani & Romualdas Bausys & Abbas Mardani, 2020. "An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies," Sustainability, MDPI, vol. 12(3), pages 1, January.
    6. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    7. Liu, Hui-hui & Song, Yao-yao & Liu, Xiao-xiao & Yang, Guo-liang, 2020. "Aggregating the DEA prospect cross-efficiency with an application to state key laboratories in China," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    8. D K Despotis, 2005. "A reassessment of the human development index via data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 969-980, August.
    9. Muhammet Enis Bulak & Murat Kucukvar, 2022. "How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 817-832, October.
    10. Meng, Fanyong & Xiong, Beibei, 2021. "Logical efficiency decomposition for general two-stage systems in view of cross efficiency," European Journal of Operational Research, Elsevier, vol. 294(2), pages 622-632.
    11. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    12. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(C).
    13. Tavana, Madjid & Izadikhah, Mohammad & Toloo, Mehdi & Roostaee, Razieh, 2021. "A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures," Omega, Elsevier, vol. 102(C).
    14. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "Assessing well-being in European regions. Does government quality matter?," Working Papers 2018/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    15. Yongjun Shen & Qiong Bao & Elke Hermans, 2020. "Applying an Alternative Approach for Assessing Sustainable Road Transport: A Benchmarking Analysis on EU Countries," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    16. Shabani, Amir & Visani, Franco & Barbieri, Paolo & Dullaert, Wout & Vigo, Daniele, 2019. "Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights," Omega, Elsevier, vol. 87(C), pages 57-70.
    17. Victoria Vicario-Modroño & Rosa Gallardo-Cobos & Pedro Sánchez-Zamora, 2023. "Sustainability evaluation of olive oil mills in Andalusia (Spain): a study based on composite indicators," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6363-6392, July.
    18. Boris Radovanov & Branislav Dudic & Michal Gregus & Aleksandra Marcikic Horvat & Vincent Karovic, 2020. "Using a Two-Stage DEA Model to Measure Tourism Potentials of EU Countries and Western Balkan Countries: An Approach to Sustainable Development," Sustainability, MDPI, vol. 12(12), pages 1-12, June.
    19. 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).
    20. Angel Higuerey & Christian Viñan-Merecí & Zulema Malo-Montoya & Valentín-Alejandro Martínez-Fernández, 2020. "Data Envelopment Analysis (DEA) for Measuring the Efficiency of the Hotel Industry in Ecuador," Sustainability, MDPI, vol. 12(4), pages 1-18, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:6-:d:191919. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.