Revealing the profile of economically efficient mussel farms: a restricted data envelopment analysis application
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The level of technical efficiency (TE) of farms is a complex issue largely connected to the efficient use of available resources, which in turn determines their economic performance. Data envelopment analysis (DEA) is an established method to estimate TE; however, it is subject to drawbacks which sometimes reduce its ability to account differences in production scales. Indeed, the conventional DEA model allows total flexibility in the weights that a decision-making unit attaches to inputs and outputs, while in some cases, zero weights are attached to variables that are totally omitted in the efficiency analysis. Restricting efficiency weights in the DEA model, without of course eliminating the total weight flexibility assumption, guarantees zero weights, and prevents large differences in weights. In this study, an assurance region (AR) weight restricted model is applied on 66 mussel farms in order to calculate more comprehensive efficiency estimates and to obtain a meaningful and consistent picture of the efficient farm structure in economic terms, which could be potentially used for managerial suggestions, identification of best practices and innovations, and effective decision-making tool concerning mussel farm aquaculture. The cost share of the main production factors is used for imposing weight restrictions on the conventional DEA model, and a comparative descriptive technical and economic analysis of the efficient farms of the restricted and unrestricted DEA models is implemented. The results indicate that the structure of the efficient farm under the restricted DEA model is substantially diversified, formulating a new pattern of production system that achieves a higher economic performance.
KeywordsMussels Efficiency Benchmarking Economic performance
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with animals performed by any
of the authors.
- Angelidis P (2007) Shellfish culture in estuary zones and the sanitary restrictions. Sci Ann Danube Delta Instit 13:161–174 Google Scholar
- Coelli TJ, Prasada Rao DS, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis. Springer, New YorkGoogle Scholar
- Cooper WW, Seiford ML, Tone K (2000) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver software. Kluwer Academic Publishers, BostonGoogle Scholar
- Cooper WW, Seiford LM, Tone K (2007b) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software, 2nd edn. Springer, New YorkGoogle Scholar
- European Commission (2015) European maritime and fisheries fund, Greek Operational Programme 2014-2020, Ref. Ares (2015) 4433579 - 20/10/2015.Google Scholar
- FAO (2018) The State of world fisheries and aquaculture 2018 - meeting the sustainable development goals. Rome. Licence: CC BY-NC-SA 3.0 IGO.Google Scholar
- FAO (2019) GLOBEFISH – Information and analysis on world fist trade: the European market for mussels, http://www.fao.org/in-action/globefish/fishery-information/resource-detail/en/c/338588/. Accessed in 24 October 2019.
- Karanikolas P, Martinos N (2012) Greek agriculture facing crisis: problems and prospects (in Greek). Available online at: http://ardinrixi.gr/archives/3811
- Ministry of Rural Development and Food (2014) Multiannual national strategic plan for the development of aquaculture in the 2014 – 2020 period (in Greek).Directorate of General Fisheries, Athens.Google Scholar
- Nguyen THA (2012) Profitability and technical efficiency of black tiger shrimp (Penaeus Monodon) culture and white leg shrimp (Penaeus Vannamei) culture in Song Song Cau district, Phu Yen province, Vietnam. Master Thesis in Fisheries and Aquaculture Management and Economics, The Norwegian College of Fishery Science University of Tromso and Nha Trang University, Vietnam.Google Scholar
- Scientific, Technical and Economic Committee for Fisheries (STECF) (2016) Economic report of the EU aquaculture sector (EWG-16-12). Publications Office of the European Union, Luxembourg; EUR 28356 EN. https://doi.org/10.2788/677322
- Thanassoulis E, Portela MCAS, Allen R (2004) Incorporating value judgments in DEA. In: Cooper WW, Seiford LW, Zhu J (eds) Handbook on Data Envelopment Analysis. Kluwer Academic Publishers, Boston, pp 98–137Google Scholar
- Thanassoulis E, Portela M, Despic O (2008) Data envelopment analysis: the mathematical programming approach to efficiency analysis. In: Fried HO, Knox Lovell CA, Schmidt SS (eds) The Measurement of productive efficiency and productivity growth. Oxford University Press, New York, pp 251–420CrossRefGoogle Scholar
- Yilmaz B, Yurdusev MA (2011) Use of data envelopment analysis as a multicriteria decision tool – a case of irrigation management. Math Comput Appl 16:669–679Google Scholar
- Zhu J (2009) Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets. Springer, New YorkGoogle Scholar