The Social Psychology of Organizations.

New Patterns of Management.

Leadership styles and outcome patterns for the nursing workforce and work environment: A systematic review

In recent years there has been an exponential growth in the number of publications related to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and Rhodes (1978) introduced DEA as a tool for measuring efficiency and productivity of decision making units. DEA has immediately been recognized as a modern tool for performance measurement. Since then, a large and considerable amount of articles has been appeared, including significant breakthroughs in theory and a great portion of works on DEA applications, both public and private sectors, to assess the efficiency and productivity of their activities. Although there have been several bibliographic collections reported, a comprehensive analysis and listing of DEA-related articles covering its first four decades of history is still missing. This paper, thus, aims to report an extensive listing of DEA-related articles including theory and methodology developments and "real" applications in diversified scenarios from 1978 to end of 2016. Some summary statistics of the publications' growth, the most utilized academic journals, authorship analysis, as well as keywords analysis are also provided.

A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016

The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.

A survey of DEA applications

Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available. This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007. A listing of the most utilized/relevant journals, a keyword analysis, and selected statistics are presented.

Evaluation of research in efficiency and productivity:a survey and analysis of the first 30 years of scholarly literature in DEA

This is the post-print version of the final paper published in Socio-Economic Planning Sciences. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.

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The competitiveness of nations and implications for human development

In aggregation for data envelopment analysis (DEA), a jointly determined aggregate measure of output and input efficiency is desired that is consistent with the individual decision making unit measures. An impasse has been reached in the current state of the literature, however, where only separate measures of input and output efficiency have resulted from attempts to aggregate technical efficiency with the radial measure models commonly employed in DEA. The latter measures are “incomplete” in that they omit the non-zero input and output slacks, and thus fail to account for all inefficiencies that the model can identify. The Russell measure eliminates the latter deficiency but is difficult to solve in standard formulations. A new approach has become available, however, which utilizes a ratio measure in place of the standard formulations. Referred to as an enhanced Russell graph measure (ERM), the resulting model is in the form of a fractional program. Hence, it can be transformed into an ordinary linear programming structure that can generate an optimal solution for the corresponding ERM model. As shown in this paper, an aggregate ERM can then be formed with all the properties considered to be desirable in an aggregate measure—including jointly determined input and output efficiency measures that represent separate estimates of input and output efficiency. Much of this paper is concerned with technical efficiency in both individual and system-wide efficiency measures. Weighting systems are introduced that extend to efficiency-based measures of cost, revenue, and profit, as well as derivatives such as rates of return over cost. The penultimate section shows how the solution to one model also generates optimal solutions to models with other objectives that include rates of return over cost and total profit. This is accomplished in the form of efficiency-adjusted versions of these commonly used measures of performance.

Efficiency aggregation with enhanced Russell measures in data envelopment analysis

Emergency service systems provide mobile units (crews and/or equipment) to respond to requests for assistance and/or service in emergency situations that occur at any time and any place throughout a specified region such as a metropolitan district or a rural area. This paper presents a simulation model that serves as a tool for resource allocation and management of an emergency service system. The model was tested to study, evaluate, and optimize the allocation of police patrol vehicles to non-homogeneous zones with different demand patterns in the City of Richmond, Virginia. © 1997 Elsevier Science Ltd

A Simulation Model for the Analysis and Management of An Emergency Service System

In data envelopment analysis (DEA), there are two principal methods for identifying and measuring congestion: Those of Fare et al. [Fare R, Grosskopf S. When can slacks be used to identify congestion. An answer to W. W. Cooper, L. Seiford, J. Zhu. Socio-Economic Planning Sciences 2001;35:1–10] and Cooper et al. [Cooper WW, Deng H, Huang ZM, Li SX. A one-model approach to congestion in data envelopment analysis. Socio-Economic Planning Sciences 2002;36:231–8]. In the present paper, we focus on the latter work in proposing a new method that requires considerably less computation. Then, by proving a selected theorem, we show that our proposed methodology is indeed equivalent to that of Cooper et al.

Barnett R. Parker

Papers

Evaluation of research in efficiency and productivity:a survey and analysis of the first 30 years of scholarly literature in DEA

The competitiveness of nations and implications for human development

Efficiency aggregation with enhanced Russell measures in data envelopment analysis

A Simulation Model for the Analysis and Management of An Emergency Service System

A new method for measuring congestion in data envelopment analysis