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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TL;DR: In this paper , the effect of time lag on a two-stage dynamic network data envelopment analysis (DEA) is investigated, where intermediate products produced in the first stage both contribute to concurrent production in the second stage and affect operations in subsequent periods.
Abstract: This study is focused on the effect of time lag on a two-stage dynamic network data envelopment analysis (DEA) where intermediate products produced in the first stage both contribute to concurrent production in the second stage and affect operations in subsequent periods. We concluded that existing treatments for estimating a uniform time lag parameter do not reflect various operational strategies deployed by individual decision making units (DMUs) over a period of time. As a remedy, we proposed a two-stage dynamic network DEA model that can consider variable time lag effects, namely multiple carryover schemes, optimized for each DMU in efficiency measurements. Empirical validation of the model is provided based on Korean research and development (R&D) institutes and a focused discussion on the technology licensing process. The comparative analysis shows that the dynamics of intellectual capital stock can be represented well by the proposed model, while the existing approaches carry a risk of understating efficiency measures owing to their restrictive nature. The proposed model is particularly robust to the concentration of inputs and/or outputs by recognizing virtual reallocations of resources over time, which can be used as a solution to the discrepancy between production lead time and interval of evaluation in dynamic systems.
1 citations
TL;DR: The “Dynamic-network” version of cost efficiency measurement in Data Envelopment Analysis (DEA) is proposed and is applicable in, improving the performance of the system.
Abstract: The “Dynamic-network” version of cost efficiency measurement in Data Envelopment Analysis (DEA) is proposed in this paper. The classical DEA models ignore operations of individual processes within a system; moreover, they compute efficiency at the same time. Therefore, we suggest a relational model to estimate cost efficiency in static network structures. Also, we incorporate the dynamic effect in network structures. The proposed models here evaluate the overall efficiency over the whole periods and indicate it as a weighted average of period efficiencies. The main advantage revealed in this study is recognition of: which divisions at what periods caused the inefficiency of the system, the internal activities of the system over time, considered; moreover, the results obtained here is applicable in, improving the performance of the system. A case study of Iranian banking industry is used to show the applicability of the approach.
1 citations
Cites background from "Two-Stage DEA: An Application to Ma..."
...Modeling network structures are critically debated by Fare and Grosskopf (1996, 2000), Lewis and Sexton (2004), Sexton and Lewis (2003), Golany et al. (2006), Prieto and Zofio (2007), Kao (2009, 2014), Tone and Tsutsui (2009), and Cook et al. (2010)....
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TL;DR: In this article, an output oriented methodology for calculating productivity growth by using Malmquist productivity index (MPI) and two different data envelopment analysis (DEA) views (optimistic and pessimistic) simultaneously, and apply it to five Iranian Commercial Banks over the four time period (2009-2013).
Abstract: The purpose of this paper is to develop an output oriented methodology for calculating productivity growth by using Malmquist productivity index (MPI) and two different data envelopment analysis (DEA) views (optimistic and pessimistic) simultaneously, and apply it to five Iranian Commercial Banks over the four time period (2009-2013). Consequently, we have proposed a new approach called the double frontiers two-stage DEA or DFTDEA for simultaneous measurement of the MPI from both different DEA views. Furthermore, this paper has used two-stage DEA with reference to the variable return to scale technology (VRS) and applied a new viewpoint to measure the overall efficiency of the process.
1 citations
01 Jan 2014
TL;DR: In this article, a two-stage DEA model is provided to measuring the efficiency of customer relationship management system (CRM) that have one input (service quality) and one intermediate measures (customer satisfaction) and gain only an overall efficiency score for the entire process.
Abstract: One of the best methods for measuring the efficiency of decision making units (DMUs) is Data envelopment analysis (DEA). Recently two-stage processes of DEA method has been populated in scholars researches. We use this model with this condition that all the outputs from the first stage that called intermediate measures are the inputs of the second stage. this two-stage DEA model is provided to measuring the efficiency of customer relationship management system (CRM) that have one input(service quality) and one intermediate measures(customer satisfaction) and one output(customer loyalty) and gain only an overall efficiency score for the entire process. Data was collected by the questionnaire and overall Crobach's Alpha is equal to 81.7. Case study includes of fourteen banks in Esfahan. The current study presents a new approach for determining the efficiency score of every decision making units (DMU) of CRM systems by designing a network structure. The results show the efficiency of every DMU and rank them in best way.
1 citations
Cites methods from "Two-Stage DEA: An Application to Ma..."
...Sexton and Lewis (2003) also use two-stage process of DEA for evaluating the performance of Major League Baseball....
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23 Mar 2022
TL;DR: In this paper , a non-oriented and non-radial slacks-based measure (SBM) of efficiency framework for the three-stage network production process is proposed for Indian banking efficiency.
Abstract: Data envelopment analysis (DEA) is a non-parametric technique for measuring and analyzing the relative efficiency of the Decision-Making Unit (DMU) having multiple homogeneous types of inputs and outputs. Traditional DEA treats DMU as black boxes and calculates their efficiencies by considering their initial inputs and final outputs. But the overall efficiency of DMU is directly depended upon the performances of intermediate processes of operations. In many situations, DMUs have a three-stage network structure. Against the aforesaid backdrop, this paper introduces a non-oriented and non-radial the slacks-based measure (SBM) of efficiency framework for the three-stage network production process. In the proposed model we have considered both series and parallel relationship between the inputs and outputs of different independent and dependent stages. Additionally, this research is aimed at measuring the Indian banking efficiency by using the three-stage network DEA model.
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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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