The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs

The most popular weight restrictions are assurance regions (ARs), which impose ratios between weights to be within certain ranges. ARs can be categorized into two types: ARs type I (ARI) and ARs type II (ARII). ARI specify bounds on ratios between input weights or between output weights, whilst ARII specify bounds on ratios that link input to output weights. DEA models with ARI successfully maximize relative efficiency, but in the presence of ARII the DEA models may under-estimate relative efficiency or may become infeasible. In this paper we discuss the problems that can occur in the presence of ARII and propose a new nonlinear model that overcomes the limitations discussed. Also, the dual model is described, which enables the assessment of relative efficiency when trade-offs between inputs and outputs are specified. The application of the model developed is illustrated in the efficiency assessment of Portuguese secondary schools.info:eu-repo/semantics/publishedVersio

Upgraded data envelopment analysis model application for total productivity comparison in major airports of the European Union

In order to compare the productivity of airports different scientific approaches are used by various authors. Previous research has shown wide application of the data envelopment analysis (D.E.A.) model for productivity comparison. The D.E.A. model may be used to compare both partial and total factor productivity. However, aggregation of the separate partial factors into a single D.E.A. model is still not sufficiently investigated. The purpose of this paper is to suggest the integration of two methods – DEA and Delphi Expert Panel – to solve this problem. A model was developed and experimentally tested with 15 major European Union airports. The results show that the suggested model could be efficiently used to compare the airports’ productivity, which is expressed by a large set of attributes. The main conclusion is that model can be successfully used to compare airports by different criteria through integrating the DEA and Delphi Expert Panel techniques. The model can be used for any set of airports to compare productivity. The research could be useful to airport managers and investors, as well as to researchers in the area of D.E.A. application

The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale (CRS or VRS) models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run. A different example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

World state of quality: a frontier approach to benchmark the performance of countries worldwide

Purpose - The World State of Quality (WSQ) Project aims to evaluate, analyse, rank and categorise countries according to their performance in quality as a multidimensional concept. The Project involves the computation of an overall score for each country, obtained as a weighted average of ranking positions of 16 metrics, with weights determined by a panel of experts. Methodology-This work proposes an alternative strategy for that procedure, using a Benefit-of-the-Doubt (BoD) Composite Indicator approach under the framework of Data Envelopment Analysis (DEA). This strategy avoids the need of using subjective weights and normalising data by rank positions, using a more objective procedure to obtain the countries’ ranking. A new overall score of the World State of Quality is proposed, which allows the categorisation of countries’ performance. The novel insights resulting from the use of this methodology are discussed, including the identification of strengths and weaknesses of the various countries, and the peers that can be used for facilitating continuous improvements policies. Findings - The results show that the BoD approach and the original method used by the WSQ Project present comparable results. Countries’ strengths and weaknesses and their suitable peers and targets for benchmarking are presented with illustrative examples. Originality/value – A novel frontier approach for countries’ benchmarking regarding their performance in quality is proposed, incorporating new insights into the current method.FCT - Fundação para a Ciência e a Tecnologia(2021.05244)The authors acknowledge the financial support provided by FCT- Fundação para a Ciência e a Tecnologia (Portuguese National Funding Agency for Science, Research and Technology) through PhD research grants and SFRH/BD/131285/2017. This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Integration von Gewichtsrestriktionen in das DEA-Modell nach Charnes, Cooper und Rhodes: exemplarische Optionen und Auswirkungen

Ziel des Beitrags ist es, die Integration von Gewichtsrestriktionen in das DEA-Basismodell nach Charnes, Cooper und Rhodes (CCR-Modell) zu untersuchen. Für ein fiktives Beispiel werden die Ergebnisse der um verschiedene Gewichtsrestriktionen erweiterten DEA-Modelle präsentiert und diskutiert. In einfachen Sensitivitätsanalysen wird der Einfluss ausgewählter Gewichtsrestriktionen auf die Effizienzwerte näher beleuchtet

Consistent proportional trade-offs in data envelopment analysis

Proportional trade-offs – as an enhanced form of the conventional absolute trade-offs – have recently been proposed as a method which can be used to incorporate prior views or information regarding the assessment of decision making units (DMUs) into relative efficiency measurement systems by Data Envelopment Analysis (DEA). A proportional trade-off is defined as a percentage change of the level of inputs/outputs so that the corresponding restriction is adapted with respect to the volume of the inputs and outputs of the DMUs in the analysis. It is well-known that the incorporation of trade-offs either in an absolute form or proportional form may lead in certain cases to serious problems such as infinity or even negative efficiency scores in the results. This phenomenon is often interpreted as a result of defining the set of trade-offs carelessly by the analyst. In this paper we show that this may not always be the case. The existing framework by which the trade-offs are combined mathematically to build a corresponding production technology may cause a problem rather than the definition of the trade-offs. We therefore develop analytical criteria and formulate computational methods that allow us to identify the above-mentioned problematic situations and test if all proportional trade-offs are consistent so that they can be applied simultaneously. We then propose a novel framework for aggregating local sets of trade-offs, which can be combined mathematically. The respective computational procedure is shown to be effectively done by a suggested algorithm. We also illustrate how the efficiency can be measured against an overall technology, which is formed by the union of these local sets. An empirical illustration in the context of engineering schools will be presented to explain the properties and features of the suggested approach

The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-015-1854-0Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale (CRS or VRS) models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run. A different example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

Efficiency Evaluation in Two-stage Data Envelopment Analysis under a Fuzzy Environment: A Common-Weights Approach

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Data envelopment analysis (DEA) has been genuinely known as an impeccable technique for efficiency measurement. In practice, since many production systems such as broadcasting companies, banking and R&D activities include two processes connected in series, we have need of utilizing two-stage DEA models to identify the sources of inefficiency and explore in turn appropriate options for improving performance. The lack of the ability to generate the actual weights is not only an ongoing challenge in traditional DEA models, it can have serious repercussion for the contemporary DEA models (e.g., two-stage DEA). This paper presents a common-weights method for two-stage structures that allows us to consider equality of opportunity in a fuzzy environment when evaluating the system efficiency and the component process efficiencies. The proposed approach first seeks upper bounds on factor weights and then determines a set of common weights by a single linear programming problem. We illustrate the approach with a data set taken from the literature

The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs

The most popular weight restrictions are assurance regions (ARs), which impose ratios between weights to be within certain ranges. ARs can be categorized into two types: ARs type I (ARI) and ARs type II (ARII). ARI specify bounds on ratios between input weights or between output weights, whilst ARII specify bounds on ratios that link input to output weights. DEA models with ARI successfully maximize relative efficiency, but in the presence of ARII the DEA models may under-estimate relative efficiency or may become infeasible. In this paper we discuss the problems that can occur in the presence of ARII and propose a new nonlinear model that overcomes the limitations discussed. Also, the dual model is described, which enables the assessment of relative efficiency when trade-offs between inputs and outputs are specified. The application of the model developed is illustrated in the efficiency assessment of Portuguese secondary schools.Data envelopment analysis Weight restrictions Assurance regions type II

DEA models with production trade-offs and weight restrictions

There is a large literature on the use of weight restrictions in multiplier DEA models. In this chapter we provide an alternative view of this subject from the perspective of dual envelopment DEA models in which weight restrictions can be interpreted as production trade-offs. The notion of production trade-offs allows us to state assumptions that certain simultaneous changes to the inputs and outputs are technologically possible in the production process. The incorporation of production trade-offs in the envelopment DEA model, or the corresponding weight restrictions in the multiplier model, leads to a meaningful expansion of the model of production technology. The efficiency measures in DEA models with production trade-offs retain their traditional meaning as the ultimate and technologically realistic improvement factors. This overcomes one of the known drawbacks of weight restrictions assessed using other methods. In this chapter we discuss the assessment of production trade-offs, provide the corresponding theoretical developments and suggest computational methods suitable for the solution of the resulting DEA models