Accounting for slacks to measure and decompose revenue efficiency in the Spanish Designation of Origin wines with DEA

In this paper, we show how Data Envelopment Analysis (DEA) may be used to measure and decompose revenue inefficiency, taking into account all sources of technical waste in the context of an application to assess the Spanish quality wine sector, in particular Designation of Origin (DO) wines. We try to go beyond the standard approaches, which use Shephard distance functions or directional distance functions, to provide decomposition that incorporates slacks as a source of technical inefficiency. To accomplish this, we will base our analysis on a recent approach introduced in Cooper et al. (2011a). In particular, we show how an output-oriented version of the Weighted Additive model can be used to properly identify revenue, technical, and allocative inefficiencies in Spanish DOs. In the application, we conclude that the main source of revenue inefficiency in this sector is technical waste, and that Cava can be highlighted as the DO that performs as a benchmark for more numbers of units.     

On the relative efficiency of alternative modes of producing a public sector output: The case of the developmentally disabled

This paper examines the relative efficiency of alternative methods of producing care for the developmentally disabled. A linear programming framework is used to construct a production frontier which allows measurement of relative efficiency among institutions in the sample. Tests are performed to detect influential observations in the data which might result from measurement error which could distort the efficiency measures. Different types of institutions are compared in terms of average efficiency. Policy implications of the analysis are discussed in the concluding section.     

On comparing the performance of primary care providers

In the past few years primary health care has been characterised as central to the development of the National Health Service in the United Kingdom. Furthermore, performance assessment is seen as a way of achieving care of high standards. Performance indicators and targets are being developed to assess primary care providers, and to develop financial incentives. However, the number of studies that have compared the performance of primary care providers is limited and the existing approaches to evaluation are open to improvement.     

Efficiency and equity in private and public education: A nonparametric comparison

We present a nonparametric approach for (1) efficiency and (2) equity evaluation in education. Firstly, we use a nonparametric (Data Envelopment Analysis) model that is specially tailored to assess educational efficiency at the pupil level. The model accounts for the fact that typically minimal prior structure is available for the behavior (objectives and feasibility set) under evaluation. It allows for uncertainty in the data, while it corrects for exogenous ‘environmental’ characteristics that are specific to each pupil. Secondly, we propose two multidimensional stochastic dominance criteria as naturally complementary aggregation criteria for comparing the performance of different school types (private and public schools). While the first criterion only accounts for efficiency, the second criterion also takes equity into consideration. The model is applied for comparing private (but publicly funded) and public primary schools in Flanders. Our application finds that no school type robustly dominates another type when controlling for the school environment and taking equity into account. More generally, it demonstrates the usefulness of our nonparametric approach, which includes environmental and equity considerations, for obtaining ‘fair’ performance comparisons in the public sector context.     

Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools

Public sector output provision is influenced not only by discretionary inputs but also by exogenous environmental factors. In this paper, we extended the literature by developing a conditional DEA estimator of allocative efficiency that allows a decomposition of overall cost efficiency into allocative and technical components while simultaneously controlling for the environment. We apply the model to analyze technical and allocative efficiency of Dutch secondary schools. The results reveal that allocative efficiency represents a significant 37 percent of overall cost efficiency on average, although technical inefficiency is still the dominant part. Furthermore, the results show that the impact of environment largely differs between schools and that having a more unfavorable environment is very expensive to schools. These results highlight the importance of including environmental variables in both technical and allocative efficiency analysis.     

Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA

This study surveys the increasing research field of performance measurement by making use of a bibliometric literature analysis. We concentrate on two approaches, namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) as the most important methods to evaluate the efficiency of individual and organizational performance. It is the first literature survey that analyses DEA and SFA publications jointly, covering contributions published in journals, indexed by the Web of Science database from 1978 to 2012. Our aim is to identify seminal papers, playing a major role in DEA and SFA development and to determine areas of adoption. We recognized a constant growth of publications during the years identifying DEA as a standard technique in Operations Research, whereas SFA is mainly adopted in Economic research fields. Making use of document co-citation analysis we identify Airports and Supplier Selection (DEA) as well as Banking and Agriculture (SFA) as most influential application areas. Furthermore, Sensitivity and Fuzzy Set Theory (DEA) as well as Bayesian Analysis and Heterogeneity (SFA) are found to be most influential research areas and seem to be methodological trends. By developing an adoption rate of knowledge we identify that research, in terms of citations, is more focusing on relatively old and recent research at the expenses of middle-aged contributions, which is a typical phenomenon of a fast developing discipline.     

The measurement of returns to scale under a simultaneous occurrence of multiple solutions in a reference set and a supporting hyperplane

This research theoretically explores the measurement of RTS (Returns to Scale) under a possible occurrence of multiple solutions in DEA (Data Envelopment Analysis). In this study, the occurrence of multiple solutions is classified into Type I and Type II. Type I is an occurrence of multiple solutions in a reference set. Type II is an occurrence of multiple solutions on a supporting hyperplane passing on the reference set. Both Types I and II are very well known among DEA researchers, but previous research has not sufficiently explored a simultaneous occurrence of Type I and Type II in the RTS measurement. The two types of multiple solutions influence a degree of RTS in the DEA measurement. Such a quantitative issue on RTS is examined from the perspective of the Type I and Type II problems. To deal with such difficulties, a new linear programming approach is proposed to identify all efficient DMUs (Decision Making Units) that consist of a reference set, even if multiple solutions occur on the reference set. Based upon the research result, we can identify when multiple solutions of Type I and/or Type II occur on the RTS measurement and how to deal with such difficulties. Our research result makes it possible to measure a degree of scale economies (RTS) under the simultaneous occurrence of Type I and Type II.     

Pricing public health care services using DEA: Methodology versus politics

The New Zealand public health sector has used DEA since 1997 to identify efficient expenditure levels to set prices for hospital services at the DRG level. Given the size of the expenditure (NZ$ 2.6 billion), considerable robustness was required for the results and sophistication of the models/process. While the model development and application appeared to be successful, politics overturned the results in the short run. In the longer term, the results have been shown to be reasonably robust and have become a base-line reference for future developments. As such, this paper reports a relatively successful transfer of theory into practice.     

Semi-radial technical efficiency measurement

Semi-radial efficiency measurement combines technical efficiency, as captured by the classical Farrell measure, with an economically meaningful mix efficiency component. The semi-radial evaluation we propose proceeds in two steps. First, we build on the price interpretation of the generally accepted Koopmans efficiency notion to characterize appropriate benchmarks. Next, we present both a quantity-based distance measure and its dual (price-based) equivalent to evaluate the mix efficiency factor. The type of measures we propose may, e.g., be used to provide a price rationale for the Zieschang technical efficiency evaluation procedure.     

Integrating the regulatory and utility firm perspectives,when measuring the efficiency of electricity distribution

Several DEA applications for benchmarking in utility regulation use classical models, which reveal inconsistencies due to Pareto inefficient targets. The natural course of action would be to incorporate weight restrictions, reflecting value judgments and requiring interaction between analyst and decision maker. We show that weight restricted DEA models still present some inconsistencies, since it is not possible to ensure that the target both dominates the observed DMU and lies on the empirical production frontier.     

Robustness of the efficient DMUs in data envelopment analysis

By means of modified versions of CCR model based on evaluation of a decision making unit (DMU) relative to a reference set grouped by all other DMUs, sensitivity analysis of the CCR model in data envelopment analysis (DEA) is studied in this paper. The methods for sensitivity analysis are linear programming problems whose optimal values yield particular regions of stability. Sufficient and necessary conditions for upward variations of inputs and for downward variations of outputs of an (extremely) efficient DMU which remains efficient are provided. The approach does not require calculation of the basic solutions and of the inverse of the corresponding optimal basis matrix. The approach is illustrated by two numerical examples.     

只有输出(入)的DEA改进模型及其应用

研究了只有输出(入)的DEA分析方法,针对只有输出(入)DEA模型的不足,重新定义了只有输出(入)的DEA评价方法的有效性,并改进了模型。相对已有的只有输出(入)的DEA模型,该模型充分利用了决策单元的诸输出(入),提高了DEA评价的效果。作为应用,运用新模型对武警防暴队形优选问题进行了有效性分析。     

Improving envelopment in Data Envelopment Analysis under variable returns to scale

In a Data Envelopment Analysis model, some of the weights used to compute the efficiency of a unit can have zero or negligible value despite of the importance of the corresponding input or output. This paper offers an approach to preventing inputs and outputs from being ignored in the DEA assessment under the multiple input and output VRS environment, building on an approach introduced in Allen and Thanassoulis (2004) for single input multiple output CRS cases. The proposed method is based on the idea of introducing unobserved DMUs created by adjusting input and output levels of certain observed relatively efficient DMUs, in a manner which reflects a combination of technical information and the decision maker’s value judgements. In contrast to many alternative techniques used to constrain weights and/or improve envelopment in DEA, this approach allows one to impose local information on production trade-offs, which are in line with the general VRS technology. The suggested procedure is illustrated using real data.     

Chapter 11 Simulation studies of efficiency,returns to scale and misspecification with nonlinear functions in DEA

Using statistically designed experiments, 12,500 observations are generated from a 4-pieced Cobb-Douglas function exhibiting increasing and decreasing returns to scale in its different pieces. Performances of DEA and frontier regressions represented by COLS (Corrected Ordinary Least Squares) are compared at sample sizes ofn=50, 100, 150 and 200. Statistical consistency is exhibited, with performances improving as sample sizes increase. Both DEA and COLS generally give good results at all sample sizes. In evaluating efficiency, DEA generally shows superior performance, with BCC models being best (except at corner points), followed by the CCR model and then by COLS, with log-linear regressions performing better than their translog counterparts at almost all sample sizes. Because of the need to consider locally varying behavior, only the CCR and translog models are used for returns to scale, with CCR being the better performer. An additional set of 7,500 observations were generated under conditions that made it possible to compare efficiency evaluations in the presence of collinearity and with model misspecification in the form of added and omitted variables. Results were similar to the larger experiment: the BCC model is the best performer. However, COLS exhibited surprisingly good performances — which suggests that COLS may have previously unidentified robustness properties — while the CCR model is the poorest performer when one of the variables used to generate the observations is omitted.     

论“打开黑箱评价”的网络DEA模型

讨论了两阶段网络DEA模型KH,复合网络DEA模型WYP,以及两个模型之间的关系.并指出了上述两个模型能够打开"黑箱".     

Optimizing the rank position of the DMU as secondary goal in DEA cross-evaluation

Cross-efficiency evaluation is an extension of Data Envelopment Analysis (DEA) that permits not only the determination of a ranking of Decision Making Units (DMUs) but also the elimination of unrealistic weighting schemes, thereby rescinding the necessity for the inclusion of individual judgements in the models. The main deficiency of the procedure is the non-uniqueness of the optimal weights, which results in the peer evaluations dependences, for instance, on the software used to determine DMU’s efficiencies. This shortfall justifies the inclusion of secondary goals in order to determine cross-efficiency values. In this paper a new proposal of a secondary goal is studied. The idea is related with that proposed in Wu et al. (2009), in which the objective is the optimization of the rank position of the DMU under evaluation. In the procedure proposed here, an incentive to break level-pegging ties between alternatives is introduced by considering that efficiency scores induce a weak order of alternatives. The model is illustrated with a preference-aggregation application.     

Scaling units via the canonical correlation analysis in the DEA context

This paper deals with the evaluation of decision making units which have multiple inputs and outputs. A new method (CCA/DEA) is developed where the Canonical Correlation Analysis (CCA) is utilized to provide a full rank scaling for all the units rather than a categorical classification (for efficient and inefficient units) as done by the Data Envelopment Analysis (DEA). The CCA/DEA approach is an attempt to bridge the gap between the frontier approach of DEA and the average tendencies of statistics (econometrics). Nonparametric statistical tests are employed to validate the consistency between the classification from the DEA and the postclassification that was generated by the CCA/DEA.     

Review of Methods for Increasing Discrimination in Data Envelopment Analysis

We present a review of methods for increasing discrimination between efficient DMUs in Data Envelopment Analysis. These methods were classified into two groups: those that incorporate a priori information and those that do not use or minimize the use of such a priori information. We also compare these methodologies regarding their specific characteristics.     

Improvements by analyzing the efficient frontier in DEA

In this paper, we suggest four types of improvements for making inefficient DMUs efficient in the CCR model with the minimal change of input and output values. Moreover, we propose an algorithm for calculating such improvements by applying quadratic programming techniques. Furthermore, since all equations constructing the efficient frontiers of the CCR and BCC models are necessary to execute the algorithm, we present a procedure for calculating them.     

Measuring the efficiency of highway maintenance contracting strategies: A bootstrapped non-parametric meta-frontier approach

Highly deteriorated US road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving performance of highway maintenance practices. Privatizing some portions of road maintenance operations by state Departments of Transportation (DOTs) under the auspices of performance-based contracts has been one of the innovative initiatives in response to such a need. This paper adapts the non-parametric meta-frontier framework to the two-stage bootstrapping technique to develop an analytical approach for evaluating the relative efficiency of two highway maintenance contracting strategies. The first strategy pertains to the 180 miles of Virginia’s Interstate highways maintained by Virginia DOT using traditional maintenance practices. The second strategy pertains to the 250 miles of Virginia’s Interstate highways maintained via a Public Private Partnership using a performance-based maintenance approach. The meta-frontier approach accounts for the heterogeneity that exists among different types of highway maintenance contracts due to different limitations and regulations. The two-stage bootstrapping technique accounts for the large set of uncontrollable factors that affect the highway deterioration processes. The preliminary findings, based on the historical data for the state of Virginia, suggest that road authorities (counties) that have used traditional contracting for transforming the maintenance expenditures into the improvement of the road conditions seem to be more efficient than road authorities that have used the performance-based contracting. This paper recommends that road authorities use hybrid contracting approaches that include best practices of both traditional and performance-based highway maintenance contracting.