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Measuring Technical Efficiency of Dairy Farms with Imprecise Data: A Fuzzy Data Envelopment Analysis Approach

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  • Mugera, Amin W.
Abstract
This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs data are measured with precision. However, production agriculture takes place in an uncertain environment and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data is known to lie within specified intervals and empirically illustrate this approach using a group of 34 dairy producers in Pennsylvania. Compared to the convectional DEA scores that are point estimates, the computed fuzzy efficiency scores allow the decision maker to trace the performance of a decision-making unit at different possibility levels.
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Suggested Citation

  • Mugera, Amin W., 2013. "Measuring Technical Efficiency of Dairy Farms with Imprecise Data: A Fuzzy Data Envelopment Analysis Approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(4), pages 1-19.
    • Handle: RePEc:ags:aareaj:253473
    DOI: 10.22004/ag.econ.253473
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    Cited by:

    1. Ahmad Hosseinzadeh & Russell Smyth & Abbas Valadkhani & Amir Moradi, 2018. "What determines the efficiency of Australian mining companies?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(1), pages 121-138, January.
    2. Fabio A. Madau & Roberto Furesi & Pietro Pulina, 2017. "Technical efficiency and total factor productivity changes in European dairy farm sectors," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-14, December.
    3. Ebubekir Karabacak & Hüseyin Ali Kutlu, 2024. "Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey," Sustainability, MDPI, vol. 16(1), pages 1-25, January.
    4. Peggy Schrobback & Sean Pascoe & Louisa Coglan, 2014. "Shape Up or Ship Out: Can We Enhance Productivity in Coastal Aquaculture to Compete with Other Uses?," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-25, December.
    5. Sebastián Lozano & Belarmino Adenso-Díaz, 2021. "A DEA approach for merging dairy farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(6), pages 209-219.
    6. Mostafa Mardani Najafabadi & Hanieh Kazmi & Somayeh Shirzadi Laskookalayeh & Abas Abdeshahi, 2023. "Investigating the ability of fuzzy and robust DEA models to apply uncertainty conditions: an application for date palm producers," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 776-801, June.
    7. Stefanos A. Nastis & Thomas Bournaris & Dimitrios Karpouzos, 2019. "Fuzzy data envelopment analysis of organic farms," Operational Research, Springer, vol. 19(2), pages 571-584, June.
    8. Otieno, Wycliffe A. & Nyikal, Rose Adhiambo & Mbogoh, Stephen G. & Rao, Elizaphan J. O., 2024. "Optimizing Costs: How Biosecurity Measures Transform Smallholder Poultry Economics," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344298, International Association of Agricultural Economists (IAAE).
    9. Zoran Ciric P & Dragan Stojic & Otilija Sedlak & Aleksandra Marcikic Horvat & Zana Kleut, 2019. "Innovation Model of Agricultural Technologies Based on Intuitionistic Fuzzy Sets," Sustainability, MDPI, vol. 11(19), pages 1-12, October.

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    More about this item

    Keywords

    Agribusiness; Agricultural and Food Policy; Livestock Production/Industries;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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