Performance assessment in production systems without explicit inputs: an application to basketball players

Masoumzadeh, Atefeh; Toloo, Mehdi; Amirteimoori, Alireza

doi:10.1093/imaman/dpu011

Cited by 10 publications

(3 citation statements)

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“…, ) ≥ 0. Masoumzadeh et al [14] have used the weak disposability assumption of Shephard [15] to propose the following linear production technology to handle undesirable outputs in production system without explicit inputs:…”

Section: Marginal Rates In the Presence Of Bad Outputsmentioning

confidence: 99%

Alternative Trade-Offs in Data Envelopment Analysis: An Application to Hydropower Plants

Mirzaei¹,

Kordrostami²,

Amirteimoori³

et al. 2016

Mathematical Problems in Engineering

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In multidimensional input/output space, the behavior of the firms can be analyzed by using efficient frontier or supporting surfaces of production technology. To this end, mathematicians are interested to use marginal rates of substitutions. The piecewise linear frontier of data envelopment analysis (DEA) technology is not differentiable at the extreme points and marginal rates calculation is valid only for small changes in one or more variables. The existing trade-off analysis methods calculate the maximum changes in a specific throughput when another throughput is changed. We will show that binding efficient supporting surfaces of an efficient point may be used to define different marginal rates of substitutions and in this sense, we get different marginal rates to each frontier point.

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Section: Marginal Rates In the Presence Of Bad Outputsmentioning

confidence: 99%

Alternative Trade-Offs in Data Envelopment Analysis: An Application to Hydropower Plants

Mirzaei¹,

Kordrostami²,

Amirteimoori³

et al. 2016

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

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“…Since 1978 that CCR model was proposed by Charnes et al (1978), DEA has had a significant role in evaluating the relative efficiency of DMUs (e.g. Farzipoor Saen and Zohrehbandian, 2008;Dibachi et al, 2014Dibachi et al, , 2015Masoumzadeh et al, 2014). Simsek and T€ uys€ uz (2018) developed an integrated network DEA method with fuzzy data to measure and analyze the performance of sub-process and overall system of a cargo company.…”

Section: Introductionmentioning

confidence: 99%

How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran

Izadikhah

Saen

Ahmadi

et al. 2020

JEIM

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PurposeThe aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering.Design/methodology/approachFirst, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers.FindingsThis paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters.Originality/valueThe main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.

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“…For example, assists, rebounds, points are used to measure the contribution of each player to the final match result. Masoumzadeh et al (2016) model the outputs of a production system and present an application to basketball players. Sport's literature focuses mainly on individual efficiency measures.…”

Section: Introductionmentioning

confidence: 99%

An extended regularized adjusted plus-minus analysis for lineup management in basketball using play-by-play data

Grassetti

Bellio

Gaspero

et al. 2020

IMA Journal of Management Mathematics

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In this work we analyse basketball play-by-play data in order to evaluate the efficiency of different five-man lineups employed by teams. Starting from the adjusted plus-minus framework, we present a model-based strategy for the analysis of the result of partial match outcomes, extending the current literature in two main directions. The first extension replaces the classical response variable (scored points) with a comprehensive score that combines a set of box score statistics. This allows various aspects of the game to be separated. The second extension focuses on entire lineups rather than individual players, using a suitable extended model specification. The model fitting procedure is Bayesian and provides the necessary regularization. An advantage of this approach is the use of posterior distributions to rank players and lineups, providing an effective tool for team managers. For the empirical analysis, we use the 2018/2019 regular season of the Turkish Airlines Euroleague Championship, with play-by-play and box scores for 240 matches, which are made available by the league website. The results of the model fitting can be used for several investigations as, for instance, the comparative analysis of the effects of single players and the estimation of total and synergic effects of lineups monitoring. Moreover, the behaviour of players and lineups during the season, updating the estimation results after each gameday, can represent a rather useful tool.

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Performance assessment in production systems without explicit inputs: an application to basketball players

Cited by 10 publications

References 0 publications

Alternative Trade-Offs in Data Envelopment Analysis: An Application to Hydropower Plants

Alternative Trade-Offs in Data Envelopment Analysis: An Application to Hydropower Plants

How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran

An extended regularized adjusted plus-minus analysis for lineup management in basketball using play-by-play data

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