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.     

Measurement of returns to scale using a non-radial DEA model: A range-adjusted measure approach

This research theoretically explores the measurement of returns to scale (RTS), using a non-radial DEA (data envelopment analysis) model. A range-adjusted measure (RAM) is used as a representative of such non-radial models. Historically, a type of RTS has been discussed within an analytical framework of radial models. The radial-based RTS measurement is replaced by the non-radial RAM/RTS measurement in this study. When discussing the non-radial RAM/RTS measurement, this study finds a problem of multiple projections that cannot be found in the radial measurement. In this research, a new linear programming approach is proposed to identify all efficient DMUs (decision making units) on a reference set. The important feature of the proposed approach is that it can deal with a simultaneous occurrence of (a) multiple reference sets, (b) multiple supporting hyperplanes and (c) multiple projections. All of the three difficulties are handled by the proposed RAM/RTS measurement. In particular, we discuss both when the three different types of multiple solutions occur on the RAM/RTS measurement and how to deal with such difficulties. Our research results make it possible to measure not only the type of RTS but also the magnitude of RTS in the RAM measurement.     

Determining new possible weight values in PROMETHEE: a procedure based on data envelopment analysis

Operational research (OR) offers efficient tools to support managers in strategic decision-making processes. Data envelopment analysis (DEA) and multiple criteria decision aid (MCDA) are two important research areas in OR. These two domains are both based on the evaluation of “objects” according to multiple “points of views”. Within the MCDA framework, choosing appropriate weights for the different criteria often arises as a problem itself for decision makers. As a consequence, researchers have developed original methodologies to help them during this elicitation phase. In this work, we aim to investigate how DEA can be used to propose weights in the context of the PROMETHEE II method. More precisely, we suggest an extension of the so-called “decision maker brain” used in the GAIA plane (also known as PROMETHEE VI) based on DEA. The underlying idea is based on the computation of weights in PROMETHEE (GAIA brain) which are compatible with the DEA analysis. We end this paper with a numerical example.     

On a basic definition of returns to scale

A concept that has sparked considerable interest in DEA is that of returns to scale (RTS). One of the basic and useful definitions of RTS in DEA models is based upon the PPS. In this work, a discussion about the PPS-based definition of RTS is given, leading to a modified definition of RTS which is suitable in the presence of multiple supporting hyperplanes passing through the unit under assessment. The definition provided is a simplification of a definition given by Tone.     

Validation and generalization of DEA and its uses

Summary Rapidly expanding uses of DEA have been accompanied by developments which have enhanced its power and enlarged its utility for additional applications. Developments covered in the present paper include simulation studies comparing DEA with competing forms of statistical regressions. Other studies covered show how these two approaches can be combined in complementary fashion. Another part of this paper deals with Chance Constrained Programming formulations which incorporate probabilistic elements into DEA. Included also are discussions of statistical characterizations with accompanying tests of statistical significance for DEA efficiency evaluations. This paper concludes with uses of DEA in “discovery processes”-processes that need strengthening (and encouragemnt) in contemporary social science and management science research. Suggestions are made for additional research on further developments which extend to uses of DEA to provide new approaches in economics (including econometrics), management and psychology and an Appendix introduces new or recently developed efficiency measures for use in DEA. Invited by J. T. Pastor     

Measurement of Returns to Scale and Damages to Scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs?

Environmental assessment is increasingly important in preventing various types of pollutions. Data Envelopment Analysis (DEA) has been long used as an operational performance measure, but we have insufficiently explored the use of DEA for environmental assessment. This study explores a new use of DEA for the environmental assessment in which outputs are classified into desirable (good) and undesirable (bad) outputs. Such an output separation is important in the DEA-based environmental assessment. This study extends the use of DEA to the measurement of both Returns to Scale (RTS) for desirable outputs and Damages to Scale (DTS) for undesirable outputs. A Range-Adjusted Measure (RAM) is used as a DEA model for this study because the non-radial model can easily combine the two types of outputs in a unified treatment. All the mathematical features regarding the RAM-based RTS/DTS measurement are first discussed from the operational and environmental performance in a separate treatment. Then, this study combines the two performance measures as a unified measure. The RAM-based RTS/DTS is mathematically explored from the unified measure for operational and environmental performance.     

Slack-adjusted DEA for time series analysis: Performance measurement of Japanese electric power generation industry in 1984–1993

Using a new slack-adjusted data envelopment analysis (SA-DEA) model which explicitly incorporates an influence of slacks into its efficiency measurement, this study discusses a use of various efficiencies and index measures for DEA dynamic analysis. An analytical formulation to determine the type of return to scale (RTS) is proposed for the new DEA model. This paper mathematically discusses when multiple solutions occur on RTS and how to deal with such a difficulty. As an important case study, this paper applies the proposed DEA approach to examine the performance of Japanese electric power generation companies from 1984 to 1993. Two policy implications are suggested for guiding the Japanese electric power industry.     

A dual simplex-based method for determination of the right and left returns to scale in DEA

This study reviews the concept of the “right” and the “left” returns to scale (RTS) in data envelopment analysis (DEA), and a dual simplex-based method, for determining these two notions in RTS, is proposed, which has computational advantages as compared to the customary method.     

Scale elasticity and returns to scale in the presence of alternative solutions

Scale elasticity (SE) and returns to scale (RTS) are important topics in performance analysis, which help managers to make decisions about the expansion or contraction of the operation of decision making units under assessment. In this paper, some new results about these topics in the presence of alternative solutions, regarding the concept of multifunction, are provided.At first, some properties of some multifunctions (functions), defined with respect to the optimal solutions of DEA models, are established which help us in what follows. In turn, the relationships between the considered multifunctions and the concept of RTS and SE are studied. Finally an approach for the estimation of the RTS classification of units is obtained, which leads to an important corollary as an interesting result which introduces a connection between two concepts, RTS and SE. This is important from an applied point of view. Also, from a technical point of view, the proofs of theorems which give this corollary use a main lemma of convex analysis literature and give a constructive proof about RTS.     

Methodological comparison between DEA (data envelopment analysis) and DEA–DA (discriminant analysis) from the perspective of bankruptcy assessment

This study compares DEA (data envelopment analysis) with DEA–DA (discriminant analysis) in terms of bankruptcy assessment. Recently, many DEA researchers propose a use of DEA as a quick-and-easy tool to assess corporate bankruptcy. Meanwhile, other DEA researchers discuss a use of DEA–DA for bankruptcy-based financial analysis. The two groups are very different from the conventional use of DEA because we have long applied DEA to the measurement of operational performance, or productivity analysis. The two research groups open up a new application area (bankruptcy-based financial assessment) for DEA. This study discusses methodological strengths and weaknesses of DEA and DEA–DA from the perspective of corporate failure. The proposed comparative analysis has the three main criteria: (a) how to handle negative data in financial variables, (b) how to handle data imbalance between default and non-default firms, and (c) how to identify a failure process over time. This study finds that DEA is a managerial tool for the initial assessment of corporate failure and DEA is useful for busy corporate leaders and financial managers. In contrast, DEA–DA is useful for researchers and individuals who are interested in the detailed assessment of bankruptcy and its failure process in a time horizon.     

Preference, Production and Performance in Data Envelopment Analysis

This paper attempts to provide a systematic approach to the DEA model building. To this end, we try to identify some essential aspects of DEA modelling. Three key building blocks in a DEA model are identified: they are preference order, production possibility set and performance measure. It is shown that the preferences and performance measurements used in the standard DEA models are only particular examples in this framework. It is also illustrated in this work that this methodology is useful in building new DEA models to handle nonstandard applications such as those involve non-Pareto preferences or undesirable inputs-outputs.     

E-DEA: Enhanced data envelopment analysis

Data envelopment analysis (DEA) has enjoyed a wide range of acceptance by researchers and practitioners alike as an instrument of performance analysis and management since its introduction in 1978. Many formulations and thousands of applications of DEA have been reported in a considerable variety of academic and professional journals all around the world. Almost all of the formulations and applications have basically centered at the concept of “relative self-evaluation”, whether they are single or multi-stage applications. This paper suggests a framework for enhancing the theory of DEA through employing the concept of “relative cross-evaluation” in a multi-stage application context. Managerial situations are described where such enhanced-DEA (E-DEA) formulations had actually been used and could also be potentially most meaningful and useful.     

Spreading the gospel of management science: operational research in Iron and Steel, 1950–1970

This paper builds on the author's earlier work on the history of operational research by presenting an analysis of the development of the discipline in Iron and Steel, an industry long regarded as one of the outstanding pioneers in the application of management science to decision-making processes. The contribution of Sir Charles Goodeve and BISRA to the diffusion and practice of operational research is well-documented. Less well known is the reaction to operational research within the managerial hierarchies of the private sector iron and steel companies. In the light of the development of dedicated operational research groups by the leading companies after 1950, it might be assumed that the industry was highly receptive to the discipline in terms of its perceived benefits. The present paper questions this assumption by highlighting the problems encountered by operational researchers in two of the largest Iron and Steel Companies which gave every appearance of being at the forefront of the practice of management science in British industry. Where appropriate, the paper draws contrasts and comparisons with the development of operational research within the nationalised Coal Industry.     

DEA congestion and returns to scale under an occurrence of multiple optimal projections

Economic implications of congestion have been recently discussed in many DEA (data envelopment analysis) studies. In addition, several previous research efforts have explored a theoretical linkage between returns to scale (RTS) and the concept of congestion, because the two economic concepts are closely connected to each other. Tone and Sahoo [Tone, K., Sahoo, B.K., 2004. Degree of scale economies and congestion: A unified DEA approach. European Journal of Operational Research 158, 755–772] have published the theoretical linkage in this journal. All of the previous studies, including their research (2004), assume a unique optimal solution in the investigation on DEA-based congestion. When multiple solutions occur in DEA-based congestion measurement, the economic implications of congestion obtained from the previous research are all problematic from both theoretical and practical perspectives. To deal with the issue, this study explores how to deal with the occurrence of multiple solutions in the DEA-based congestion measurement. This study proposes a new approach for the congestion measurement and theoretically compares the proposed approach with Tone and Sahoo (2004).     

Justifying the methods of OR

Operational research practitioners use mathematical, statistical, scientific, and other methods to structure and analyse issues in order to advise and assist their clients. In doing so they apply values, follow rules and use methodologies. The paper examines the justification of these methods, values and methodologies. Starting with a conceptual model drawn from the philosophy of science, a justification framework is developed for operational research (OR). Making a distinction between OR academic research and OR practice helps to clarify the issues. OR research is similar to scientific, mathematical and social science research; OR practice, as technology, is closer to engineering. While OR academic researchers will seek justification in the academic discipline within which they choose to work, it is argued that the justification of OR practice lies in its usefulness. For academic OR, justification lies in the justification of mathematics, statistics, science and social science; for practice, it is practitioners who decide what usefulness means in their context.     

Optimal system design series-network DEA models

There is an urgent need in a wide range of fields such as logistics and supply chain management to develop effective approaches to measure and/or optimally design a network system comprised of a set of units. Data envelopment analysis (DEA) researchers have been developing network DEA models to measure decision making units’ (DMUs’) network systems. However, to our knowledge, there are no previous contributions on the DEA-type models that help DMUs optimally design their network systems. The need to design optimal systems is quite common and is sometimes necessary in practice. This research thus introduces a new type of DEA model termed the optimal system design (OSD) network DEA model to optimally design a DMUs (exogenous and endogenous) input and (endogenous and final) output portfolios in terms of profit maximization given the DMUs total available budget. The resulting optimal network design through the proposed OSD network DEA models is efficient, that is, it lies on the frontier of the corresponding production possibility set.     

Finding the efficiency score and RTS characteristic of DMUs by means of identifying the efficient frontier in DEA

Data envelopment analysis (DEA) is basically a linear programming based technique used for measuring the relative performance of organizational units, referred to as decision-making units (DMUs), where the presence of multiple inputs and outputs makes comparisons difficult. The ability of identifying frontier DMUs prior to the DEA calculation is of extreme importance to an effective and efficient DEA computation. In this paper, a method for identifying the efficient frontier is introduced. Then, the efficiency score and returns to scale (RTS) characteristic of DMUs will be produced by means of the equation of efficient frontier.     

Returns to scale in multiplicative models in data envelopment analysis

One class of models introduced in DEA is called multiplicative models, in which, as shown by Banker and Maindiratta (Manag. Sci. 32:126–135, 1986), the piecewise linear frontiers usually employed in DEA are replaced by a frontier that is piecewise Cobb-Douglas(=log  linear). Banker and Maindiratta (Manag. Sci. 32:126–135, 1986) introduced a model to identify the most productive scale size pattern, and Banker et al. (Eur. J. Oper. Res. 154:345–362, 2004) presented a two-stage method for the identification of returns to scale (RTS) in multiplicative models. In this paper it is shown that both the RTS situation and the MPSS pattern could be determined by a single model in one step. The new method is important in the computational point of view.     

Reconciling ratio analysis and DEA as performance assessment tools

The assessment of operational performance remains a fundamental challenge both in practice and in theory. Data envelopment analysis (DEA) is one method developed in production economic theory and applied by researchers to study groups of enterprises. In practice, individual enterprises almost universally rely on simple output–input ratios. Each approach has its strengths and weaknesses, but the theoretical connection between the two has not been fully articulated. This paper uses the framework of DEA to establish a mathematical relationship between DEA efficiency scores and corresponding ratio analysis. The relationship can be expressed as a product of seven components: technical efficiency, technical change, scale efficiency, input slack factor, input substitution factor, output slack factor and output substitution factor.     

带偏好DEA在“科学研究基金”管理中的应用研究

将带偏好锥DEA理论引入科学研究基金管理中,在包含"拥挤"迹象的生产可能集基础上建立了三个带偏好锥的平行网络结构DEA模型,对科研基金投入后产生的"成效"进行评价.这些模型分别从三个层面探讨了科研基金使用效率、分配合理性,以及最佳基金预算的确定方法.