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Data Envelopment Analysis and Performance Measurement: Recent Developments
Abstract
Emrouznejad, A. and E. Thanassoulis (2018), Data Envelopment Analysis and Performance Measurement: Recent Developments: Proceedings of the DEA40: International Conference of Data Envelopment Analysis, April 2018, Aston Business School, Birmingham, UK, ISBN: 978 1 85449 438 2.
... where B is the number of bootstrap iterations, and λ b k are the bootstrap efficiencies. As a result, the initial efficiency is an overestimate of the true efficiency and, in a few cases, reaches the upper bound on the confidence interval, which is 100% or higher [29]. ...
Risk management is a key activity in every organization. The identification and evaluation of all risks in higher education institutions lead to the continuous monitoring of investments in people, high technology, and innovation. This paper evaluates the relative efficiency of study programs in Romanian higher education using the DEA method. This study is based on 38 study programs from a public university in Romania, using a traditional DEA approach: CRS-DEA and VRS-DEA models, with an output orientation for three academic years (2016–2019). To avoid distortions in the efficiency scores, we decided to implement the bootstrap method to correct DEA efficiencies. The results show that only four study programs were efficient during this period under the CRS-DEA approach, and eight study programs were efficient under the VRS-DEA model. According to scale efficiency and the bootstrap method, the results also showed that four study programs were efficient during the period analyzed. Finally, we observed that the inefficiency of study programs is relatively persistent (89%), compared with efficient DMUs (11%). Based on these findings, higher education institutions should consider the possibility of increasing the quality of study programs correlated with the degree of attractiveness of various programs in the current socio-economic environment.
... In the last two decades a great deal of effort has been put into constructing composite indicators for the purpose of performance analysis. In many studies, data envelopment analysis (DEA) has been used as a suitable methodological tool (e.g., Emrouznejad and Yang 2018;Emrouznejad and Thanassoulis 2018;Peykani et al. 2019). The DEA is a nonparametric mathematical optimization method developed by Charnes et al. (1978) and extended by Banker et al. (1984). ...
Objectives:
Composite road safety performance indicators (RSPIs) are useful tools in regional road safety planning. Among the indicators and data calculated by the World Health Organization (WHO), information on the effectiveness of law enforcement on various risk factors for road casualties were provided, which can be considered as qualitative indicators. The purpose of this study is to analyze the performance indicators related to the percentage of helmet and seat-belt use versus the qualitative enforcement scores attributed by WHO.
Methods:
This analysis was performed for 30 member states of WHO and will show how and with what degree of efficiency the qualitative output of the enforcement score acts versus the input percentage of seat-belt and helmet use. The qualitative nature of the output index has led us to depart the traditional analysis of crisp numerical indicators related to road safety performance and to consider data as imprecise or fuzzy indices. In this study we used two methods including imprecise DEA-based CIs and fuzzy DEA-based CIs, respectively.
Results:
Results show that the clear score achieved by the Imprecise DEA-based CI model is easy to interpret and use. Whereas, in the Fuzzy DEA-based CI model, the fuzzy indicator scores obtained based on the level of several probabilities are strong in capturing the uncertainties related to human behavior.
Conclusions:
Both RSPIs are applicable with slight differences that were in the order of countries and the ease of reading the results. We also found that each method has different strengths and that the FDEA-based CIs method is more accurate and more in line with the inputs than the IDEA-based CIs method.
Failure to wear a helmet and seat belt is one of the most important risk factors for road traffic injuries. According to data from most countries in the world, only one-third of countries classify their enforcement level as "good" for each of the risk factors. This requires the development and ensuring of law enforcement in countries to increase the share and efficiency of helmet and seat belt use. The purpose of this study is to determine the level of efficiency in enforcing helmet and seat belt use laws to reduce road fatality rates at the country level. This level of efficiency is measured based on the enforcement score assigned by the World Health Organization to each of these two factors then the necessary targets are set for each inefficient country to improve the level of traffic safety in it. In this study, in addition to the values of indicators related to the use of helmets and seatbelts, the data of the related fatality rate and the degree of law enforcement were used simultaneously. The data for this model include three levels, which are the percentage of helmet and seat belt use (intervention outputs), the enforcement scores (intermediate outcomes) and the road fatality rates (final outcomes). The intermediate outcomes are qualitative data and the model in this study was based on fuzzy data envelopment analysis (DEA). For this purpose, a multi-objective fuzzy DEA model was used which encompasses two basic submodels: (1) evaluation of final outcomes affected by the intermediate outcome indicators; and (2) evaluation of intermediate outcomes affected by intervention output data. The results show that only Finland and Spain have absolute efficiency. As an underperforming country, Iran ranks 19th in terms of inefficiency score. In order to become an efficient country based on the data of its benchmark countries, it must increase its helmet enforcement by 55.4 percent, and at the same time maintain its seat-belt enforcement law without the need to change. In the case of helmets, this rate should increase to 77.6 percent for motorcycle riders and 382.5 percent for passengers. Seat belts should also be increased by 4.3 percent for front seat occupants and 470 percent for rear seat occupants in vehicles.
The main objective of this research is to measure the relative efficiency of the campuses of Farhangian University, which trains schoolteachers in Iran. As with many organizations, Farhangian University’s campuses have hierarchical structures and need to provide appropriate models for evaluating their performance. Data envelopment analysis (DEA) is now widely used for evaluating the performance and efficiency of many systems. The present research aims at introducing suitable models for calculating the efficiency of hierarchical structures using DEA and applying these models for comparing the efficiencies of Farhangian University’s campuses. The results reveal that some campuses have high efficiency, while others do not have satisfactory performance, suggesting that these campuses do not optimally utilize their inputs and outputs. The results of the proposed models can be of great assistance for managers to identify inefficient departments, develop strategies to improve their performance and enhance the overall efficiency of the campuses.
The application of Geometric Brownian motion to forecast share prices is reviewed. Formula of Geometric Brownian motion is analyzed and examined to meet the fluctuation of share prices. Uncertainty and unpredictability share prices makes it difficult for investors to forecast future prices. Thus, this reviewed paper aims to state the importance of application of Geometric Brownian Motion into share prices and helps the investors to forecast future prices for the short-term investment. This paper will elaborate geometric Brownian motion involving the randomness, volatility and drift that can help investors in making their investment decision wisely.
This paper constructs an innovative approach to measure school district organizational effectiveness. We use the fully nonparametric Benefit-of-the-Doubt approach to construct a composite indicator which reduces subjectivity in choosing weights attached to different functions of school districts. The model is extended to reduce the influence of outliers (robust) and to account for the exogenous environment (conditional). We apply the suggested technique to unique and self-collected data from surveys and interviews taken from school board members and principals. We illustrate why accounting for respondent characteristics is crucial when evaluating school districts. Next, we analyze the obtained aggregate measures to identify which organizational structures, board characteristics and management styles are of importance for the organizational effectiveness of school districts.
Purpose: Performance evaluation is a general problem both in production and service systems. Generally, operation performance is determined based on input resource utilization and on outputs related data. Performance evaluation is especially complicated when both financial and nonfinancial indicators must be considered in the evaluation of the efficiency of healthcare system. The purpose of this paper is to apply data envelopment analysis (DEA) in order to measure the efficiency of rehabilitation departments curing musculoskeletal diseases.
Methodology/Approach: The evaluation of the efficiency of rehabilitation departments includes several parameters. Performance evaluation becomes complicated when several evaluation criteria must be taken into consideration at the same time. In these cases, scoring methods are generally used, which transform performance data into a common scale and an aggregate score is calculated with subjective weights. Using DEA the subjective element of evaluation is eliminated when the weights of inputs and outputs are determined.
Findings: The applied DEA model evaluates the performance of rehabilitation departments. The presented analysis highlights the differences between the efficiency of the studied departments, and explores inefficiencies related to economies of scale. The slack values directly show the operational shortcomings in specific areas, and indicate the exact amount of the required changes.
Research Limitation/implication: The applied DEA model evaluates the performance of rehabilitation departments. The presented analysis highlights the differences between the efficiency of the studied departments, and explores inefficiencies related to economies of scale. The slack values directly show the operational shortcomings in specific areas, and indicate the exact amount of the required changes.
Originality/Value of paper: The originality of the paper lies on the identification of inputs and outputs for the applied DEA model as only nonfinancial indicators were taken into consideration. The analysis involves all rehabilitation departments of the Hungarian healthcare system; consequently, conclusions related to the general state of this area can be drawn.
Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References, And DEA-Solver Software, 2nd Edition is designed to provide a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. Emphasis is placed on the use as well as an understanding of DEA and the topics in this book have been selected and treated accordingly. The first nine chapters cover the basic principles of DEA and the final seven chapters are more advanced treatment of DEA. These final chapters were completely revised into new chapters, reflecting recent developments that greatly extend the power and scope of DEA and lead to new directions for research and DEA uses. Together with the first ten chapters of the basic principles, they will provide students and researchers with a solid understanding of the methodology, its uses and its potential.
Network Data Envelopment Analysis (network DEA) is an extension of the conventional Data Envelopment Analysis (DEA) developed to take into account the internal structure of the Decision Making Units (DMUs). In network DEA, the DMU is considered as a network of interconnected sub-processes, where the connections indicate the flow of the intermediate measures. In this paper, we reformulate some of the basic network DEA methodologies in a common modelling framework. We show that the leader-follower approach, the multiplicative and the additive decomposition methods as well as the recently introduced min-max method and the “weak-link” approach, can all be modelled in a multi-objective programming framework, differentiating only in the definition of the overall system efficiency and the solution procedure adopted. Such a common modelling framework makes the direct comparison of the different methodologies possible and enables us to spot and underline their similarities and dissimilarities effectively. We illustrate graphically how the aforementioned methodologies locate their optimal efficiency scores on the Pareto front in the objective functions space, with an example taken from the literature.
This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook's chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work.
The second edition includes updated versions of selected first edition chapters. New chapters have been added on:
· Different approaches with no need for a priori choices of weights (called “multipliers) that reflect meaningful trade-offs.
· Construction of static and dynamic DEA technologies.
· Slacks-based model and its extensions
· DEA models for DMUs that have internal structures network DEA that can be used for measuring supply chain operations.
· Selection of DEA applications in the service sector with a focus on building a conceptual framework, research design and interpreting results.
Using Transparency International’s Corruption Perceptions Index (CPI), this paper establishes a statistically significant link between CPI and foreign direct investment (FDI) flows to 54 developing and developed countries. In addition to each country’s CPI, several location and economic characteristics are also postulated to influence FDI. For a group of 22 developing countries, the paper then simulates the impact of an improvement in the CPI score on FDI. This simulation shows that a one point improvement in CPI would generate on average additional FDI of 0.5% of GDP. For instance, the gain in annual FDI would be 18 billion for China. The paper further simulates the effects of larger FDI on the generation of taxable income and tax revenues in each country using country-specific rates of return on US investment and the highest marginal corporate tax rate in each country. This simulation shows that a three point improvement in CPI would more than double the corporate tax take on average with the biggest beneficiaries such as India, Turkey, Egypt, South Korea, the Philippines and Thailand.