Measures of farm business efficiency.
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.
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ABSTRACT: Management performance measurement is a complex task since multiple inputs and multiple outputs are involved in the process. This study attempted to develop an integrated framework to encompass the basic concepts of balance scorecards (BSC) and data envelope analysis (DEA) for measuring management performance. BSC and DEA are complementary to each other. On the one hand, BSC can provide appropriate outputs of performance for DEA. On the other hand, DEA can set benchmarking for companies based on their inputs and outputs, as well as transform performance measures into managerial information. Accordingly, the synergy of BSC and DEA can translate the appropriate performance indices into managerial implications. This study selected auto and commercial bank industries as the targets for empirical investigation. The results indicated that the interrelationships among four perspectives of BSC were empirically valid. However, the most crucial indicators in each perspective were distinct in different industries. About 46% of auto companies and 57% of commercial banks are located at efficiency frontiers. Managerial implications and research limitations are addressed as well.Total Quality Management and Business Excellence 01/2009; 20(11):1153-1172. · 0.59 Impact Factor
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ABSTRACT: The wine Common Market Organisation has established two concepts for recognizing the quality of wines in the European Union (EU). The first corresponds to the so-called Protected Designation of Origin (PDO), and the second to the Protected Geographical Indication (PGI). The set of Spanish PDOs includes the subset of Spanish DOs (Designation of Origin), which have been recognized as quality wines by Spanish authorities since 1932. Spain accounts for 67 DOs but, due to a lack of data, only 34 of them are suitable for carrying out our analysis. We will analyze the efficiency of this subset for the 2008, 2009 and 2010 seasons resorting to Data Envelopment Analysis (DEA) and using a new additive based efficiency measure known as BAM (Bounded Adjusted Measure). Since we are using panel data, we will also evaluate the productivity associated with this data set resorting to Malmquist indexes. Our results show that the efficiency behavior of the subset of Spanish DOs is uniform over the time periods analyzed and that productivity experiments only minor and irrelevant changes. They also show that three DOs are in a very good competitive position while another three DOs are in a very bad position. We end up suggesting some economic reasons for explaining these resultsSPANISH JOURNAL OF AGRICULTURAL RESEARCH 04/2013; 11(2):294-304. · 0.66 Impact Factor
- 12/2011, Degree: PhD Thesis, Supervisor: Bo Öhlmer, Helena Hansson and Dragi Dimitrievski