IDEAS home Printed from https://ideas.repec.org/a/caa/jnlage/v70y2024i11id190-2024-agricecon.html
   My bibliography  Save this article

Micro-data efficiency evaluation of agricultural companies: The case of Germany and neighbouring countries

Author

Listed:
  • Kevin Nowag

    (Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Brno, the Czech Republic)

  • Jitka Janová

    (Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Brno, the Czech Republic)

Abstract

This study uses micro-financial data to examine the efficiency of agricultural enterprises in Germany and its neighbouring countries. The aim of the study is to introduce a model for the agricultural sector and conduct an efficiency analysis using these data, interpreting the results with specific knowledge in the management of an agriculture company. Both technical and allocative efficiencies were determined, and the companies were ranked. Possible correlations between company size, measured by turnover, and the determined efficiency were analysed. At present, there is a lack of studies in the agricultural sector with high aggregated financial data, which are the basis and necessity for well-founded decision support to increase efficiency. The data envelopment analysis method was used, as a non-parametric procedure from operations research and economics field. Both the constant returns to scale (CCR) and variable returns to scale (BCC) models were used to calculate the efficiency values. The results showed that large and very large companies achieved the highest levels of efficiency. Interestingly, very large companies lost efficiency compared to large companies, suggesting that the optimal efficiency level lies with the latter. Furthermore, the Netherlands was the absolute efficiency leader, while the other countries achieved similar lower efficiencies. This study contributes to the literature by providing a comprehensive efficiency analysis in the agricultural sector based on financial data, thus offering a basis for future studies and political decisions.

Suggested Citation

  • Kevin Nowag & Jitka Janová, 2024. "Micro-data efficiency evaluation of agricultural companies: The case of Germany and neighbouring countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(11), pages 565-576.
    • Handle: RePEc:caa:jnlage:v:70:y:2024:i:11:id:190-2024-agricecon
    DOI: 10.17221/190/2024-AGRICECON
    as

    Download full text from publisher

    File URL: http://agricecon.agriculturejournals.cz/doi/10.17221/190/2024-AGRICECON.html
    Download Restriction: free of charge
    File URL: http://agricecon.agriculturejournals.cz/doi/10.17221/190/2024-AGRICECON.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.17221/190/2024-AGRICECON?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nicolae Bobitan & Diana Dumitrescu & Valentin Burca, 2023. "Agriculture’s Efficiency in the Context of Sustainable Agriculture—A Benchmarking Analysis of Financial Performance with Data Envelopment Analysis and Malmquist Index," Sustainability, MDPI, vol. 15(16), pages 1-27, August.
    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. Leonidas Sotirios Kyrgiakos & Georgios Kleftodimos & George Vlontzos & Panos M. Pardalos, 2023. "A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability," Operational Research, Springer, vol. 23(1), pages 1-38, March.
    4. Alexander Gocht & Kelvin Balcombe, 2006. "Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data," Agricultural Economics, International Association of Agricultural Economists, vol. 35(2), pages 223-229, September.
    5. Anna NOWAK & Tomasz KIJEK & Katarzyna DOMAŃSKA, 2015. "Technical efficiency and its determinants in the European Union," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(6), pages 275-283.
    6. Isabelle Piot-Lepetit & Dominique Vermersch & Robert Weaver, 1997. "Agriculture's environmental externalities: DEA evidence for French agriculture," Applied Economics, Taylor & Francis Journals, vol. 29(3), pages 331-338.
    7. Jitka JANOVÁ, 2014. "Crop plan optimization under risk on a farm level in the Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(3), pages 123-132.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    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. Isidoro GUZMÁN & Narciso ARCAS, 2008. "The Usefulness Of Accounting Information In The Measurement Of Technical Efficiency In Agricultural Cooperatives," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 79(1), pages 107-131, March.
    2. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.
    3. Nodjitigje DJIMASRA, 2010. "Mesure de l'efficacité technique des pays africains producteurs du coton : une application de la méthode Data Envelopment Analysis (DEA)," LEO Working Papers / DR LEO 1207, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    4. Lilienfeld, Amy & Asmild, Mette, 2007. "Estimation of excess water use in irrigated agriculture: A Data Envelopment Analysis approach," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 73-82, December.
    5. Reig-Martinez, Ernest & Picazo-Tadeo, Andres J., 2004. "Analysing farming systems with Data Envelopment Analysis: citrus farming in Spain," Agricultural Systems, Elsevier, vol. 82(1), pages 17-30, October.
    6. Joseph Sarkis & Srinivas Talluri, 2013. "Using data envelopment analysis for ecoefficiency evaluation," Chapters, in: M. A. Quaddus & M. A.B. Siddique (ed.), Handbook of Sustainable Development Planning, chapter 7, pages 141-158, Edward Elgar Publishing.
    7. Fousekis, Panos & Spathis, Pavlos & Tsimboukas, Konstantinos, 2001. "Assessing the Efficiency of Sheep Farming in Mountainous Areas of Greece. A Non Parametric Approach," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 2(2), pages 1-11, August.
    8. Weaver, Robert D. & Kim, Taeho, 1999. "Targeting Environmental Protection In Agriculture: Ipm And Bmps As Environmental Performance Indicators," 1999 Annual meeting, August 8-11, Nashville, TN 21576, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Fraser, I. & Cordina, D., 1999. "An application of data envelopment analysis to irrigated dairy farms in Northern Victoria, Australia," Agricultural Systems, Elsevier, vol. 59(3), pages 267-282, March.
    10. von Hobe, Cord-Friedrich & Michels, Marius & Musshoff, Oliver, 2021. "Technical efficiency and productivity change in German large-scale arable farming," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 70(01), January.
    11. Watkins, K. Bradley & Henry, Chris G. & Hardke, Jarrod T. & Mane, Ranjitsinh U. & Mazzanti, Ralph & Baker, Ron, 2021. "Non-radial technical efficiency measurement of irrigation water relative to other inputs used in Arkansas rice production," Agricultural Water Management, Elsevier, vol. 244(C).
    12. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, January.
    13. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    14. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    15. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    16. Ruiqing Yuan & Xiangyang Xu & Yanli Wang & Jiayi Lu & Ying Long, 2024. "Evaluating Carbon-Emission Efficiency in China’s Construction Industry: An SBM-Model Analysis of Interprovincial Building Heating," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    17. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    18. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    19. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    20. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.

    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:caa:jnlage:v:70:y:2024:i:11:id:190-2024-agricecon. 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: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    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.