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Thomas R. Sexton

Bio: Thomas R. Sexton is an academic researcher from Stony Brook University. The author has contributed to research in topics: Data envelopment analysis & Inefficiency. The author has an hindex of 21, co-authored 57 publications receiving 2992 citations. Previous affiliations of Thomas R. Sexton include State University of New York System.


Papers
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TL;DR: This paper pointed out serious shortcomings in DEA's treatment of price efficiency, illustrates the dangers of misspecification errors in DEA, and suggests extentions of the basic DEA formulation that address these shortcomings.
Abstract: This chapter points out serious shortcomings in DEA's treatment of price efficiency, illustrates the dangers of misspecification errors in DEA, and suggests extentions of the basic DEA formulation that address these shortcomings.

1,173 citations

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TL;DR: The Network DEA Model allows individual DMU managers to focus efficiency-enhancing strategies on the individual stages of the production process, and can detect inefficiencies that the standard DEA Model misses.

372 citations

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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.

323 citations

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TL;DR: A heuristic routing and scheduling algorithm is shown to produce high quality solutions in reasonable computation time by testing on moderately sized real data bases from both Gaithers-burg, Maryland, and Baltimore, Maryland.
Abstract: A set of n customers is given. Each customer has a desired point of pickup, a desired point of delivery and a desired time of delivery. The problem is to determine the order of pickup and delivery and the times of pickup and delivery of these n customers by a single vehicle in order to minimize total customer inconvenience. Here, a mathematical programming formulating of this problem is subjected to Benders' decomposition procedure. The result is a heuristic routing and scheduling algorithm which is shown to produce high quality solutions in reasonable computation time by testing on moderately sized real data bases from both Gaithers-burg, Maryland, and Baltimore, Maryland. This study is divided into two parts, the first detailing the scheduling analysis and the second focusing on the routing component.

179 citations

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TL;DR: Data envelopment analysis is a linear programming–based method that has clear advantages over competing approaches, but its own limitations should not be overlooked.
Abstract: Data envelopment analysis is a linear programming–based method that has clear advantages over competing approaches. However, its own limitations should not be overlooked.

158 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints and finds that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.
Abstract: This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints. Given the intrinsic difficulty of this problem class, approximation methods seem to offer the most promise for practical size problems. After describing a variety of heuristics, we conduct an extensive computational study of their performance. The problem set includes routing and scheduling environments that differ in terms of the type of data used to generate the problems, the percentage of customers with time windows, their tightness and positioning, and the scheduling horizon. We found that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.

3,211 citations

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TL;DR: In this paper, a coherent data-generating process (DGP) is described for nonparametric estimates of productive efficiency on environmental variables in two-stage procedures to account for exogenous factors that might affect firms’ performance.

2,915 citations

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TL;DR: A sketch of some of the major research thrusts in data envelopment analysis (DEA) over the three decades since the appearance of the seminal work of Charnes et al. is provided.

1,390 citations

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TL;DR: The relational model developed in this paper is more reliable in measuring the efficiencies and consequently is capable of identifying the causes of inefficiency more accurately.

1,112 citations

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TL;DR: A slacks-based network DEA model is proposed, called Network SBM, that can deal with intermediate products formally and evaluate divisional efficiencies along with the overall efficiency of decision making units (DMUs).

954 citations