DEA, incepted in 80s, has emerged as a popular decision-making technique, for determining the efficiency of similar units. Due to its simplicity and applicability, DEA has gained the attention of scientists and researchers working in diverse areas, which has contributed towards a rich literature both in terms of theoretical development as well as different applications. This paper tries to bring together the near 40 years of existence of DEA in a concise format by discussing the popular DEA models, their advantages and shortcomings, and different applications of DEA. It also provides a brief bibliometric analysis to highlight the development of DEA over the years in terms of publication trends, highly cited papers, journal citation, etc. 

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A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends

Professional football clubs have a special characteristic not shared by other types of companies: their sport performance (on the field) is important, in addition to their financial performance (of

https://journals.sagepub.com/doi/pdf/10.1177/2158244021989257

Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football:

Data envelopment analysis (DEA) model was introduced nearly half a century ago for evaluation of relative efficiency of entities having homogeneous set of input and outputs. Classical DEA has been applied to wide and diverse fields of research since its inception, due to its applicability to universal problems without any prior knowledge of functions of entities understudy or the interrelation between the inputs and outputs. However, it has certain shortcomings and several extensions of the basic DEA model have been introduced in the literature. This paper discusses the basic concept of the classical DEA models, its advantage and disadvantages vis-a-vis more recent extensions of this model.

Non-parametric Frontier Analysis Models for Relative Performance Evaluation

espanolEl analisis envolvente de datos (DEA) es una tecnica de programacion matematica determinista que evalua el rendimiento y la evaluacion comparativa de las unidades de toma de decisiones (DMU) con varias entradas y salidas. El DEA, ademas de en los sectores publico y privado, encuentra aplicacion en el ambito deportivo. Como resultado, se ha publicado un numero significativo de articulos que determinan la eficiencia atletica, economica y gerencial usando DEA en varios deportes. En este articulo presentamos un extenso estudio sobre la aplicacion de varios modelos de DEA en los siguientes deportes: Beisbol, baloncesto, cricket, ciclismo, futbol, golf, balonmano, Las olimpiadas y el tenis. Se ha encontrado que el DEA identifica las fuentes de ineficiencia en diferentes deportes individuales y de equipo por medio de analisis comparativos y proporciona posibles lineas de mejora. EnglishData envelopment analysis (DEA) is a deterministic mathematical programming technique, evaluates the performance and benchmarking of decision making units (DMUs) with several inputs and outputs. DEA, in addition to public and private sectors, finds application in the sports setting. As a result, a significant number of papers have been published that determine the athletic/economic/managerial efficiency by DEA in various sports. In this paper we present an extensive study on the application of various models of DEA in the following sports: Baseball, Basketball, Cricket, Cycling, Football, Golf, Handball, Olympics, and Tennis. It is found that DEA identified the sources of inefficiency in different team and individual games by means of benchmarking analysis and provided possible directions for improvement

A comprehensive review of data envelopment analysis (dea) in sports

Original scientific paper Using the nonparametric variable output-oriented DEA (Data Envelopment Analysis) model, this paper analyses technical efficiency of the observed national football team in the qualifications for 2010 FIFA World Cup. If DEA model has a two stage structure, the first stage uses inputs to generate outputs that then became the inputs to the second stage. The indexes of efficiency, previously generated for attack and defence, will be implemented as parameters in the second-stage DEA analysis in accordance with the initial aim of this paper, to present new results as the outcome of the comprehensive approach to both inseparable aspects of the football. This theoretical approach is structured as follows: the football teams are defined as DMU (DecisionMaking Units), then, the methodology is established, specifically, the stages of range and objectives, analysis of procedure and variables, and the description of the theoretical analysis used.

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Dijana Petrović Djordjević

Papers

Mjerenje učinkovitosti nogometnih timova primjenom višestupanjskog DEA modela