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Article
Publication date: 14 March 2008

Štefan Bojnec and Laure Latruffe

The aim of this paper is to investigate technical, scale, allocative and economic efficiencies by data envelopment analysis (DEA) and stochastic frontier methods to provide a…

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Abstract

Purpose

The aim of this paper is to investigate technical, scale, allocative and economic efficiencies by data envelopment analysis (DEA) and stochastic frontier methods to provide a decision‐making tool and managerial implications in the measurement of farm business performance and efficiency.

Design/methodology/approach

Technical, scale, allocative and economic efficiencies are analyzed with the Farm Accountancy Data Network (FADN) sample for 13 farm business branches in Slovenia in the period 1994‐2003. DEA models are used with an output‐orientation, three outputs and four inputs. The non‐parametric DEA estimations are compared with a parametric stochastic frontier approach. The cluster analysis is used to identify three different farm business groups according to their performance.

Findings

The average technical, scale, allocative and economic efficiencies for the whole FADN sample over the analyzed period are relatively high (around or over 0.90), suggesting that, although the FADN sample contains very different farms, the latter have similar management practices, and are similarly able to make the best use of the existing technology. Five farm branches (crop, dairy, livestock using own feed, fruit, and forestry) are fully efficient with respect to all four analyzed efficiency measures, suggesting that these specializations have the best chance to compete on the European and world markets.

Originality/value

Studies of technical, scale, allocative and economic efficiencies are rare for transitional farm businesses, especially in Slovenia. The research contributes to the crucial issue of whether small family farm businesses might be able to compete on international markets, as Slovenian agriculture is characterized by such structures.

Details

Industrial Management & Data Systems, vol. 108 no. 2
Type: Research Article
ISSN: 0263-5577

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Book part
Publication date: 23 November 2020

Free Access. Free Access

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Details

Change at Home, in the Labor Market, and On the Job
Type: Book
ISBN: 978-1-83909-933-5

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