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Revealing the profile of economically efficient mussel farms: a restricted data envelopment analysis application

  • Alexandros TheodoridisEmail author
  • Athanasios Ragkos
  • Georgia Koutouzidou
Article
  • 27 Downloads

Abstract

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.

Keywords

Mussels Efficiency Benchmarking Economic performance 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with animals performed by any

of the authors.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Veterinary MedicineAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Agricultural Economics Research Institute, Hellenic Agricultural Organization “Demeter”AthensGreece
  3. 3.Department of Applied InformaticsUniversity of MacedoniaThessalonikiGreece

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