IDEAS home Printed from https://ideas.repec.org/p/ags/ubgc50/161805.html
   My bibliography  Save this paper

Economic Efficiency Of Dairy Farms With Intensive And Grazing Production Systems

Author

Listed:
  • Popovic, Rade

Abstract

The objective of this research was to examine efficiency of the most common milk production systems in central Serbia. Sample with 8 farms is not statistically representative, but allows use of Data envelopment analysis (DEA). Such technique allows measurement of whole farm efficiency and gives benchmarks for further farm analysis. DEA compare levels of input and outputs for a given dairy farm with all other analysed dairy farms, determining levels of efficiency for all farms with collected consistent data set. A DEA model to measure economic efficiency was developed. It measure efficiency of producing physical (milk) and economic outputs (income) by use of physical (labour and cows) and economic inputs (feed cost). Results revealed that economic efficiency was achieved by three from eight farms. In total, milk production system with grazing period had higher level of efficiency 0,796 comparing with intensive production system with 0,579. But, in intensive milk production system one farm showed efficiency. This indicates that some other input variables like farmer’s management capabilities influenced on efficiency.

Suggested Citation

  • Popovic, Rade, 2013. "Economic Efficiency Of Dairy Farms With Intensive And Grazing Production Systems," 50th Anniversary Seminar, Agriculture and Rural Development -Challenges of Transition and Integration Processes, September 27, 2013 161805, University of Belgrade, Department of Agricultural Economics, Faculty of Agriculture.
  • Handle: RePEc:ags:ubgc50:161805
    DOI: 10.22004/ag.econ.161805
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/161805/files/16-Popovic-Finall.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.161805?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jeffrey, Scott R. & Grant, Heather-Ann R., 2001. "An Economic Analysis Of Productive Efficiency In Alberta Dairy Production," Project Report Series 24064, University of Alberta, Department of Resource Economics and Environmental Sociology.
    2. Kelly, E & Shalloo, L & Geary, U & Kinsella, A. & Thorne, F & Wallace, M, 2013. "An analysis of the factors associated with technical and scale efficiency of Irish dairy farms," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 2(3), pages 1-11, April.
    3. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, December.
    Full references (including those not matched with items on IDEAS)

    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. Artur Wilczynski & Ewa Koloszycz & Michal Switlyk, 2020. "Technical Efficiency of Dairy Farms: An Empirical Study of Producers in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 117-127.
    2. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    3. Christian Growitsch & Tooraj Jamasb & Christine Müller & Matthias Wissner, 2016. "Social Cost Efficient Service Quality: Integrating Customer Valuation in Incentive Regulation—Evidence from the Case of Norway," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 71-91, Springer.
    4. Seyed Rakhshan & Ali Kamyad & Sohrab Effati, 2015. "Ranking decision-making units by using combination of analytical hierarchical process method and Tchebycheff model in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 505-525, March.
    5. Cathal O'Donoghue & Thia Hennessy, 2015. "Policy and Economic Change in the Agri-Food Sector in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 46(2), pages 315-337.
    6. Christophe Lemiére & Gaute Torsvik & Ottar Mæstad & Christopher H. Herbst & Kenneth L. Leonard, 2013. "Evaluating the Impact of Results-Based Financing on Health Worker Performance: Theory, Tools and Variables to Inform an Impact Evaluation," Health, Nutrition and Population (HNP) Discussion Paper Series 98269, The World Bank.
    7. Aurélie Corne & Olga Goncalves & Nicolas Peypoch, 2020. "Evaluating the performance drivers of French ski resorts: A hierarchical approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 389-405, April.
    8. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    9. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.
    10. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    11. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    12. Valentinas Navickas & Adriana Grenčíková & Karol Krajčo, 2021. "DEA model and efficiency of universities - case study in Slovak Republic," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(1), pages 348-362, September.
    13. Gardijan Kedžo, Margareta & Lukač, Zrinka, 2021. "The financial efficiency of small food and drink producers across selected European Union countries using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 291(2), pages 586-600.
    14. Vassilios Babalos & Michael Doumpos & Nikolaos Philippas & Constantin Zopounidis, 2015. "Towards a Holistic Approach for Mutual Fund Performance Appraisal," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 35-53, June.
    15. Adel Hatami-Marbini & Madjid Tavana & Kobra Gholami & Zahra Ghelej Beigi, 2015. "A Bounded Data Envelopment Analysis Model in a Fuzzy Environment with an Application to Safety in the Semiconductor Industry," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 679-701, February.
    16. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    17. Peter Nijkamp & Soushi Suzuki, 2009. "A Generalized Goals-achievement Model in Data Envelopment Analysis: an Application to Efficiency Improvement in Local Government Finance in Japan," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(3), pages 249-274.
    18. Karima Kourtit & Peter Nijkamp & Soushi Suzuki, 2023. "Quantitative performance assessment of Asian stellar cities by a DEA cascade system: a capability interpretation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 70(1), pages 259-286, February.
    19. W D Cook & J Zhu, 2011. "Output-specific input-assurance regions in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1881-1887, October.
    20. Geng, ZhiQiang & Dong, JunGen & Han, YongMing & Zhu, QunXiong, 2017. "Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes," Applied Energy, Elsevier, vol. 205(C), pages 465-476.

    More about this item

    Keywords

    Livestock Production/Industries; Production Economics; Productivity Analysis;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ags:ubgc50:161805. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aoubgyu.html .

    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.