Equivalent standard DEA models to provide super-efficiency scores

DEA super-efficiency models were introduced originally with the objective of providing a tie-breaking procedure for ranking units rated as efficient in conventional DEA models. This objective has been expanded to include sensitivity analysis, outlier identification and inter-temporal analysis. However, not all units rated as efficient in conventional DEA models have feasible solutions in DEA super-efficiency models. We propose a new super-efficiency model that (a) generates the same super-efficiency scores as conventional super-efficiency models for all units having a feasible solution under the latter, and (b) generates a feasible solution for all units not having a feasible solution under the latter. Empirical examples are provided to compare the two super-efficiency models

Agricultural Economics Education in Ukrainian Agricultural Universities: An Efficiency Analysis Using Data Envelopment Analysis

Ukraine's transition from a centrally-planned to a market economy has had a profound effect upon its agricultural sector and agricultural universities. A substantial reduction in state financing has forced universities to adopt a range of survival strategies, with varying degrees of success. In this paper we use data envelopment analysis to examine the technical efficiency of 44 agricultural economics programs from 19 Ukrainian universities during the 2002/03 academic year. Our empirical results indicate wide disparities in performance, ranging from 36% to 100% technical efficiency. A second-stage analysis suggests that factors such as student demand, commercial activities and staff quality help explain a portion of this variation.higher education, Ukraine, efficiency, data envelopment analysis, Teaching/Communication/Extension/Profession, I21, C14, Q16,

Calculating Super Efficiency of DMUs for Ranking Units in Data Envelopment Analysis Based on SBM Model

There are a number of methods for ranking decision making units (DMUs), among which calculating super efficiency and then ranking the units based on the obtained amount of super efficiency are both valid and efficient. Since most of the proposed models do not provide the projection of Pareto efficiency, a model is developed and presented through this paper based on which in the projection of Pareto-efficient is obtained, in addition to calculating the amount of super efficiency. Moreover, the model is unit invariant, and is always feasible and makes the amount of inefficiency effective in ranking

Inferring the Latent Incidence of Inefficiency from DEA Estimates and Bayesian Priors

Data envelopment analysis (DEA) is among the most popular empirical tools for measuring cost and productive efficiency. Because DEA is a linear programming technique, establishing formal statistical properties for outcomes is difficult. We show that the incidence of inefficiency within a population of Decision Making Units (DMUs) is a latent variable, with DEA outcomes providing only noisy sample-based categorizations of inefficiency. We then use a Bayesian approach to infer an appropriate posterior distribution for the incidence of inefficient DMUs based on a random sample of DEA outcomes and a prior distribution on the incidence of inefficiency. The methodology applies to both finite and infinite populations, and to sampling DMUs with and without replacement, and accounts for the noise in the DEA characterization of inefficiency within a coherent Bayesian approach to the problem. The result is an appropriately up-scaled, noise-adjusted inference regarding the incidence of inefficiency in a population of DMUs.Data Envelopment Analysis, latent inefficiency, Bayesian inference,Beta priors, posterior incidence of inefficiency

Analysis of efficiency and profitability of franchise services

The present study analyses the relative efficiency of franchise services and characterises the best companies, confirming the relationship between efficiency and profit. These companies are from the trade and other services sector , the main group of service-providing companies in the Spanish economy. The methodology calls for first comparing the relative efficiency of franchisers and ownership enterprises. Second, the focus turns to the most efficient franchise services, using a super-efficiency model to rank them. The paper then goes on to cover the analysis of the main characteristics of the best franchise enterprises, the number of own establishments in a franchise business and the profitability of the company. This paper presents arguments as to why companies from the trade and other services sector are included. The main conclusion is that, whilst the number of establishments is irrelevant in achieving greater efficiency, many of the most efficient enterprises have high returns.García Martin, CJ.; Medal Bartual, A.; Peris-Ortiz, M. (2014). Analysis of efficiency and profitability of franchise services. Service Industries Journal. 34(9):796-810. doi:10.1080/02642069.2014.905921S79681034

Social and Financial Efficiency of Microfinance Institutions in Pakistan

Financial efficiency and profitability of „for profit‟ institutions have been traditionally measured with the help of financial ratios [Hassan and Sanchez (2009)]. However, financial ratios are inappropriate to investigate the sources of inefficiency, estimate financial or social efficiency with multiple inputs and outputs, and to decompose the sources of efficiency or inefficiency into technical, technological and scale efficiencies or inefficiencies respectively [Hassan and Sanchez (2009)]. Microfinance Institutions (MFIs) are special institutions, which simultaneously consider their social role to uplift the marginalised community members along with their commercial objective to secure self-sustainability. In standard literature this phenomenon is coined MFIs as being „double bottom line” institutions. [Gutierrez-Nieto, Serrano-Cinca, and Mar Molinero (2007); Gutiérrez-Nieto, Serrano-Cinca, and Molinero (2007)]. This simultaneity differentiates MFIs from conventional financial institutions. The achievement of socioeconomic efficiency is indispensable for MFIs to operate independently and on a wider scale. Thus investigation of socioeconomic efficiency of MFIs is important for monitoring and optimal policy implications

A Modified Super-Efficiency in the Range Directional Model

The range directional model (RDM) relaxes the assumption of non-negativity of inputs and outputs in the conventional data envelopment analysis (DEA) with the aim of evaluating the efficiency of a decision-making unit (DMU) when some data are negative. Although the concept of super-efficiency in the RDM contributes to enhancing discriminatory power, the formulated model may lead to the infeasibility problem for some efficient DMUs. In this paper, we modify the super-efficiency RDM (SRDM) model to overcome the infeasibility problem occurring in such cases. Our method leads to a complete ranking of the DMUs with negative data for yielding valuable insights that aid decision makers to better understand the findings from a performance evaluation process. The contribution of this paper is fivefold: (1) we detect the source of infeasibility problems of SRDM in the presence of negative data, (2) the proposed model in this study yields the SRDM measures regardless of feasibility or infeasibility of the model, (3) when feasibility occurs, the modified SRDM model results in the scores that are the same as the original model, (4) we differentiate the efficient units to improve discriminatory power in SRDM, and (5) we provide two numerical examples to elucidate the details of the proposed method

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measuring the effectiveness of various industries when used in conjunction with non-parametric methods such as multiple regression, analytical hierarchy process (AHP), multidimensional scaling (MDS), and other multiple criteria decision making (MCDM) approaches. In this study, ten petrochemical companies in the Kingdom of Saudi Arabia are evaluated using Banker, Charnes and Cooper (BCC)/Charnes, Cooper, and Rhodes (CCR) models of DEA to compute the technical and super-efficiencies for ranking according to their relative performances. Data were collected from the Saudi Stock Exchange on key financial performance measures, five of which were chosen as inputs and five as outputs. Five DEA models were developed using different input–output combinations. The efficiency plots obtained from DEA were compared with the Euclidean distance scatter plot obtained from MDS. The dimensionality of MDS plots was derived from the DEA output. It was found that the two-dimensional positioning of the companies was congruent in both plots, thus validating the DEA results

Multi-Factor Policy Evaluation and Selection in the One-Sample Situation

Firms nowadays need to make decisions with fast information obsolesce. In this paper I deal with one class of decision problems in this situation, called the “one-sample” problems: we have finite options and one sample of the multiple criteria with which we use to evaluate those options. I develop evaluation procedures based on bootstrapping DEA (Data Envelopment Envelopment) and the related decision-making methods. This paper improves the bootstrap procedure proposed by Simar and Wilson (1998) and shows how to exploit information from bootstrap outputs for decision-making