Two-Stage DEA: An Application to Major League Baseball
01 Apr 2003-Journal of Productivity Analysis (Kluwer Academic Publishers)-Vol. 19, Iss: 2, pp 227-249
TL;DR: In this article, the authors use DEA to model DMUs that produce in two stages, with output from the first stage becoming input to the second stage, and apply the model to Major League Baseball, demonstrating its advantages over a standard DEA model.
Abstract: We show how to use DEA to model DMUs that produce in two stages, with output from the first stage becoming input to the second stage. Our model allows for any orientation or scale assumption. We apply the model to Major League Baseball, demonstrating its advantages over a standard DEA model. Our model detects inefficiencies that standard DEA models miss, and it can allow for resource consumption that the standard DEA model counts towards inefficiency. Additionally, our model distinguishes inefficiency in the first stage from that in the second stage, allowing managers to target inefficient stages of the production process.
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01 Feb 2021
TL;DR: A fuzzy two-stage parallel-series system to determine the lower and upper bound fuzzy efficiencies of the decision-making units with the help of $$\alpha -$$ α - cut and rank the DMUs using the ranking index approach is developed.
Abstract: We consider a two-stage parallel-series system having three sub-systems. The independent two sub-systems of the first stage are linked in parallel and then linked to the third sub-system of the second stage in series. The deterministic two-stage parallel-series system approach is extended to uncertain/imprecise environment where the data are represented as fuzzy numbers. Using the Zadeh extension principle, we develop a fuzzy two-stage parallel-series system to determine the lower and upper bound fuzzy efficiencies of the decision-making units with the help of $$\alpha -$$
cut and rank the DMUs using the ranking index approach. The proposed methodology is illustrated using the case of Taiwan’s non-life insurance companies.
7 citations
TL;DR: In this article, the authors investigated the efficiency of public historical archives in Italy over the period 2011-2012 and estimated the efficiency frontier using Data Envelopment Analysis (DEA) implementing several procedure that allows to better investigate the performance.
Abstract: In the economic literature increasing attention is paid to the efficiency evaluation in the cultural sector. However, so far, the performance of archives is rarely investigated, notwithstanding their cultural and historical relevance. Indeed, the analysis of archives raises interesting theoretical issues because of the economic features of their outputs, ranging from public goods to divisible services. Moreover, similar services are usually provided in a decentralized way and, therefore, there is room for interesting benchmarking analysis and for policy implications. In this paper we investigate the efficiency of public historical archives in Italy over the period 2011-2012. The efficiency frontier is estimated using Data Envelopment Analysis (DEA) implementing several procedure that allows us to better investigate the performance. The efficiency analysis provides insights for policy implication.
6 citations
Journal Article•
TL;DR: The overall efficiency and each of the different stages of BSC are obtained, and two techniques including goal programming and weighted average method are used to solve such problems.
Abstract: Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity and separate use of DEA and BSC is not effective and leads to miscalculation of performance, integrated DEA-BSC model is applied. Regarding to multi-objective nature of the proposed model, two techniques including goal programming and weighted average method are used to solve such problems. At the end of the study, based on data relating to indexes of quad areas of BSC model, the results of the mentioned methods are compared. Besides assessing validation of the proposed model, the overall efficiency and each of the different stages of BSC are obtained. So that, finding a model for decision making units in various stages of BSC is the innovation of this research study.
6 citations
Cites methods from "Two-Stage DEA: An Application to Ma..."
...[5] Sexton, T.R. and Lewis, H.F. 2003....
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...The network DEA (NDEA) model was proposed by Lewis and Sexton [5] to overcome the weakness of the traditional DEA model....
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TL;DR: In this paper, the authors used the two-stage data envelopment analysis (DEA) and divided life insurance activities into two stages according to the production characteristics of 11 life insurance companies in Taiwan.
Abstract: In this research we use the two-stage data envelopment analysis (DEA) and divide life insurance activities into two stages according to the production characteristics of 11 life insurance companies in Taiwan. The first stage is the operational efficiency, and the second stage is the profitability efficiency. Analysis of the input and output data during the 2005–2006 period was made for 11 life insurance companies in Taiwan. The aim of this analysis was to investigate the relative efficiency of each life insurance company at various stages of production activities. The efficiency of decision processes that can be divided into single stages has been measured for the whole process as well as for each stage separately by using the conventional DEA methodology in order to identify the causes of inefficiency.
6 citations
01 Jan 2004
TL;DR: In this article, the reverse inputs and outputs are incorporated into a DEA model by returning to the basic principles that lead to the DEA model formulation, and the authors compare their method to reverse scoring, the most commonly used approach, and demonstrate the relative advantages of their proposed technique.
Abstract: Data envelopment analysis (DEA) assumes that inputs and outputs are measured on scales in which larger numerical values correspond to greater consumption of inputs and greater production of outputs. We present a class of DEA problems in which one or more of the inputs or outputs are naturally measured on scales in which higher numerical values represent lower input consumption or lower output production. We refer to such quantities as reverse inputs and reverse outputs. We propose to incorporate reverse inputs and outputs into a DEA model by returning to the basic principles that lead to the DEA model formulation. We compare our method to reverse scoring, the most commonly used approach, and demonstrate the relative advantages of our proposed technique. We use this concept to analyze all 30 Major League Baseball (MLB) organizations during the 1999 regular season to determine their on-field and front office relative efficiencies. Our on-field DEA model employs one output and two symmetrically defined inputs, one to measure offense and one to measure defense. The defensive measure is such that larger values correspond to worse defensive performance, rather than better, and hence is a reverse input. The front office model uses one input. Its outputs, one of which is a reverse output, are the inputs to the on-field model. We discuss the organizational implications of our results.
6 citations
References
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TL;DR: In this paper, a non-parametric productivity measure that explicitly incorporates intermediate products is proposed, which is based on the Productivity Index (PII) and employs a nonparametric approach to measure productivity.
462 citations
TL;DR: A nonparametric, linear programming, frontier procedure for obtaining a measure of managerial efficiency that controls for exogenous features of the operating environment is introduced.
Abstract: The ability of a production unit to transform inputs into outputs is influenced by its technical efficiency and external operating environment. This paper introduces a nonparametric, linear programming, frontier procedure for obtaining a measure of managerial efficiency that controls for exogenous features of the operating environment. The approach also provides statistical tests of the effects of external conditions on the efficient use of each individual input (for an input oriented model) or for each individual output (for an output oriented model). The procedure is illustrated for a sample of nursing homes.
441 citations
"Two-Stage DEA: An Application to Ma..." refers methods in this paper
...Sexton and Silkman (2000) and Fried et al. (1999) present similar but distinct approaches to dealing with site characteristics in standard DEA models....
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Posted Content•
TL;DR: In this article, the authors introduce a frontier model for productivity measurement that explicitly recognizes that some inputs are produced and consumed within the production technology, where intermediate inputs may also be final output.
Abstract: The purpose of this paper is to introduce a frontier model for productivity measurement that explicitly recognizes that some inputs are produced and consumed within the production technology. Here we differ from Koopmans (1951) by assuming that the intermediate inputs may also be final output. This assumption is in line with current international trade theory, where intermediate inputs are tradable. Our model consists of two production units that are interconnected in a network to form a production technology. The productivity measure employed here is the so-called Malmquist productivity index. This index consists of ratios of distance functions. Here these distance functions are defined on the network technology and they are computed using linear programming techniques.
439 citations
TL;DR: It is found that the decomposition of production into subproduction processes reduces the dimensions of problem specification, with the effect that a larger number of variables may be usefully included in the model.
Abstract: Agricultural production is often characterised by multiple inputs and multiple outputs to multiple production processes. Where an output from one process is used as an input to another, this output is called an intermediate product. This is a common situation when a farm produces both crops and livestock. The analysis of production efficiency is important for the evaluation of agricultural policy, but until recently, no methods have explicitly included intermediate products. This study applies a non-parametric technique of efficiency measurement which includes intermediate products. The data set is a sample of dairy farms drawn using a complex survey design. The use of non-parametric efficiency measurement and the subsequent application of bootstrapping and kernel density estimation to the results allow inferences to be drawn concerning the whole population from which the sample was drawn. We find that the decomposition of production into subproduction processes reduces the dimensions of problem specification, with the effect that a larger number of variables may be usefully included in the model.
145 citations