The role of multiplier bounds in efficiency analysis with application to Kansas farming

Thompson, Russell G.; Langemeier, Larry N.; Lee, Chih-Tah; Lee, Euntaik; Thrall, Robert M.

doi:10.1016/0304-4076(90)90049-y

Cited by 601 publications

(236 citation statements)

References 17 publications

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“…The Assurance Region Type I (ARI) is one of the proposed weight restrictions approaches, as defined by Thompson et al (1990). In model (3) we show the generic formulation of the BCC model with output ARI restrictions imposed, where α i and β i are constants specified by the R. Bras.…”

Section: Methodsmentioning

confidence: 99%

Economic and socio-environmental performance assessment of beef cattle production systems: a data envelopment analysis (DEA) approach with weight restrictions

et al. 2015

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-This study evaluated the performance of 21 beef cattle modal production systems that conduct only the raising phase. These production systems were developed in 21 municipalities in seven Brazilian states. We used two different DEA BCC models, corresponding to different points of view. Firstly we used an economic model that measured the ability of a production system to generate revenue with the preservation of native forest, using labor, capital, and current spending as inputs. The socio-environmental approach, corresponding to the second BCC model, uses the production factor labor as an output. In that model our interest was to assess whether the capital costs generate economic, environmental, and social benefits. Weight restrictions were imposed on the output variables of each model to explain the proposed viewpoints and to avoid inconsistent results. The results pointed out sources of inefficiency in terms of labor with low qualification, and use of bulls of questionable quality, factors that are common in extensive systems. These are some of the major bottlenecks in animal production systems as a whole.

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Section: Methodsmentioning

confidence: 99%

Economic and socio-environmental performance assessment of beef cattle production systems: a data envelopment analysis (DEA) approach with weight restrictions

et al. 2015

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“…However, in realworld problems, some factors may be more important than others, and experts' subjective opinions on the importance of the factors should be incorporated into the methodology. One of the common methods to do so in DEA is the assurance regions (ARs) model, in which the upper bound and lower bound of a ratio of the weights of two inputs (outputs) are pre-determined [19,20] …”

Section: Weights Of Inputs/outputs In Deamentioning

confidence: 99%

An Integrated Decision-Making Model for the Location of a PV Solar Plant

et al. 2015

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Due to the increasing demand for electricity, the depletion of fossil fuels and the increase in environmental consciousness, generating power from renewable energy resources has become necessary. How to select the most appropriate site is a critical and foremost decision that must be made when setting up a renewable energy plant. This research proposes a two-stage framework for evaluating the suitability of renewable energy plant site alternatives. In the first stage, a fuzzy analytic hierarchy process (FAHP) is adopted to set the assurance region (AR) of the quantitative factors, and the AR is incorporated into data envelopment analysis (DEA) to assess the efficiencies of plant site candidates. A few sites are selected for further analysis. In the second stage, experts are invited to evaluate the qualitative characteristics of the selected sites, and FAHP is used to calculate the priorities of these sites. Solar energy is one of the most promising renewable energy sources, because of its abundance, inexhaustibility, safety and cleanliness. Based on the proposed integrated decision-making model, a case study for selecting the most appropriate photovoltaic (PV) solar plant site is examined. OPEN ACCESSSustainability 2015, 7 13523

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“…We prefer the former approach because it builds up on the already well-established concept of weight restrictions in the DEA literature. (Thompson et al 1990). Otherwise, the weight restriction is not linked and is termed Assurance Region I, or polyhedral cone ratio (Charnes et al 1989(Charnes et al , 1990).…”

Section: Production Trade-offsmentioning

confidence: 99%

DEA Models with Production Trade-offs and Weight Restrictions

Podinovski

2015

International Series in Operations Research &Amp; Management Science

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There is a large literature on the use of weight restrictions in multiplier DEA models. In this chapter we provide an alternative view of this subject from the perspective of dual envelopment DEA models in which weight restrictions can be interpreted as production trade-offs. The notion of production trade-offs allows us to state assumptions that certain simultaneous changes to the inputs and outputs are technologically possible in the production process. The incorporation of production trade-offs in the envelopment DEA model, or the corresponding weight restrictions in the multiplier model, leads to a meaningful expansion of the model of production technology. The efficiency measures in DEA models with production trade-offs retain their traditional meaning as the ultimate and technologically realistic improvement factors. This overcomes one of the known drawbacks of weight restrictions assessed using other methods. In this chapter we discuss the assessment of production trade-offs, provide the corresponding theoretical developments and suggest computational methods suitable for the solution of the resulting DEA models.

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The role of multiplier bounds in efficiency analysis with application to Kansas farming

Cited by 601 publications

References 17 publications

Economic and socio-environmental performance assessment of beef cattle production systems: a data envelopment analysis (DEA) approach with weight restrictions

Economic and socio-environmental performance assessment of beef cattle production systems: a data envelopment analysis (DEA) approach with weight restrictions

An Integrated Decision-Making Model for the Location of a PV Solar Plant

DEA Models with Production Trade-offs and Weight Restrictions

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