Journal of the Operations Research Society of Japan

[title in Japanese]

Article type: Cover
2009 Volume 52 Issue 2 Pages Cover4-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.Cover4

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[title in Japanese]

Article type: Appendix
2009 Volume 52 Issue 2 Pages App3-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.App3

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EDITORIAL INTRODUCTION : A SPECIAL ISSUE ON "OPERATIONS RESEARCH FOR PERFORMANCE EVALUATION"(<Special Issue>Operations Research for Performance Evaluation)

Hiroshi Morita, Kazuyuki Sekitani, Hiroshi Yabe, Tohru Ueda, Hirofumi ...

Article type: Article
2009 Volume 52 Issue 2 Pages 75-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.75

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TUNING REGRESSION RESULTS FOR USE IN MULTI-STAGE DATA ADJUSTMENT APPROACH OF DEA(<Special Issue>Operations Research for Performance Evaluation)

Kaoru Tone, Miki Tsutsui

Article type: Article
2009 Volume 52 Issue 2 Pages 76-85
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.76

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Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and several studies have followed it, such as Fried et al. [5], Avkiran and Rowlands [1], and so forth. Firstly, we point out shortcomings of the traditional adjustment scheme for combining regression results for use in DEA in the multi-stage approach, and then we propose a new scheme for data adjustment. We demonstrate the effect of this adjustment formula using an electric utility dataset.

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OUTPUT SLACKS-ADJUSTED COST EFFICIENCY AND VALUE-BASED TECHNICAL EFFICIENCY IN DEA MODELS(<Special Issue>Operations Research for Performance Evaluation)

Hirofumi Fukuyama, William L. Weber

Article type: Article
2009 Volume 52 Issue 2 Pages 86-104
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.86

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This paper addresses two potential problems that arise when measuring Farrell cost efficiency using linear programming methods. First, when an optimal solution to the cost function allows slack in the output constraints that define the technology it is possible to increase at least one output without increasing costs. Therefore, two firms might be deemed equally cost efficient even though one firm produces more of at least one output. Second, previous research has shown that when input prices vary across firms, it is possible for firms with higher costs to be deemed more cost efficient than firms who have lower costs. We present a new measure of cost efficiency that accounts for both of these potential problems. We illustrate our method using data on Japanese securities firms operating in the 2004 to 2006.

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PREFERENCE VOTING AND RANKING USING DEA GAME CROSS EFFICIENCY MODEL(<Special Issue>Operations Research for Performance Evaluation)

Jie Wu, Liang Liang, Yingchun Zha

Article type: Article
2009 Volume 52 Issue 2 Pages 105-111
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.105

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Data envelopment analysis (DEA), a useful assessment tool, has been used to solve the problem of preference voting and aggregation which require the determination of the weights associated with different ranking places. Instead of applying the same externally imposed weighting scheme to all candidates, DEA models allow each candidate to choose his/her own weights in order to maximize his/her own overall ratings subject to certain conditions. It is evident that competition exists among the candidates in a preferential election, while there is no literature considering the factor of competition. This paper proposes an approach to rank candidates based on DEA game cross efficiency model, in which each candidate is viewed as a player who seeks to maximize its own efficiency, under the condition that the cross efficiencies of each of other DMU's does not deteriorate. The game cross efficiency score is obtained when the DMU's own maximized efficiencies are averaged. The obtained game cross efficiency scores constitute a Nash Equilibrium point. Therefore, the results and orders based upon game cross efficiency analysis are more reliable and will benefit the decision-maker.

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A STUDY ON LINEAR INEQUALITY REPRESENTATION OF SOCIAL WELFARE FUNCTIONS(<Special Issue>Operations Research for Performance Evaluation)

Keisuke Sato, Yoshitsugu Yamamoto

Article type: Article
2009 Volume 52 Issue 2 Pages 112-130
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.112

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This paper presents a study on the recently proposed linear inequality representation of Arrovian Social Welfare Functions (ASWFs). We correct and show several sufficient conditions on preference domains for the linear inequalities of the representation to form integral polytopes. We also show that a given probabilistic ASWF induces a real vector satisfying the inequalities.

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FAIR ALLOCATION BASED ON TWO CRITERIA : A DEA GAME VIEW OF "ADD THEM UP AND DIVIDE BY TWO"(<Special Issue>Operations Research for Performance Evaluation)

Ken Nakabayashi, Biresh K. Sahoo, Kaoru Tone

Article type: Article
2009 Volume 52 Issue 2 Pages 131-146
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.131

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The phrase "add them up and divide by two (Tashite Ni De Waru, in Japanese)" is an established maxim in Japanese society, and has its historical roots in Japanese culture. This means adopting a middle course between two competing proposals in order to avoid a conflict. In the spirit of Max Weber (1949), this paper establishes a systematically correct scientific proof of "add them up and divide by two" (Add-Div), by using conceptions of the two OR methodologies, data envelopment analysis (DEA) and cooperative game theory. More specifically, in the DEA game scheme of Nakabayashi and Tone (2006), we study an allocation problem with two criteria, in which game-theoretic solutions such as the Shapley value and the nucleolus prove coincident with the result of the Add-Div method. While today some brilliant minds may propose that people should abandon the Add-Div mentality, this paper enables one to re-consider the concept of Add-Div not only as a matter of mentality but also as an application of OR methods. We also illustrate the use of the Add-Div concept where the "assurance region" (AR) method of DEA is incorporated.

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DYNAMIC NETWORK DEA : AN ILLUSTRATION(<Special Issue>Operations Research for Performance Evaluation)

Peter Bogetoft, Rolf Fare, Shawna Grosskopf, Kathy Hayes, Lori Taylor

Article type: Article
2009 Volume 52 Issue 2 Pages 147-162
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.147

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Network DEA provides a flexible way to customize DEA problems to specific applications. It provides 'links' across DMU's, or alternatively allows us to look inside a complex DMU with multiple nodes. In this short paper, we provide an illustration of a dynamic network DEA model. It is a network in the sense that it links the behavior of DMU's across time. Our particular illustration is to an 'old' issue: the impact of public capital on technology and productivity (TFP) at the state level in the U.S. We use a dynamic network production model developed by Fare and Grosskopf [8,9] to measure dynamic efficiency. As a byproduct of the model, we solve for optimal public and private investment paths, which we then can compare to realized investment. We apply this to U.S. manufacturing data over the 1978-1999 period using state level data.

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SELECTING INPUTS AND OUTPUTS IN DATA ENVELOPMENT ANALYSIS BY DESIGNING STATISTICAL EXPERIMENTS(<Special Issue>Operations Research for Performance Evaluation)

Hiroshi Morita, Necmi K. Avkiran

Article type: Article
2009 Volume 52 Issue 2 Pages 163-173
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.163

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Data envelopment analysis (DEA) is a data oriented, non-parametric method to evaluate relative efficiency based on pre-selected inputs and outputs. In some cases, the performance model is not well defined, so it is critical to select the appropriate inputs and outputs by other means. When we have many potential variables for evaluation, it is difficult to select inputs and outputs from a large number of possible combinations. We propose an input output selection method that uses diagonal layout experiments, which is a statistical approach to find an optimal combination. We demonstrate the proposed method using financial statement data from NIKKEI 500 index.

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THE NUMBER OF CIRCULAR TRIADS IN A PAIRWISE COMPARISON MATRIX AND A CONSISTENCY TEST IN THE AHP(<Special Issue>Operations Research for Performance Evaluation)

Youichi Iida

Article type: Article
2009 Volume 52 Issue 2 Pages 174-185
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.174

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A pairwise comparison matrix in the Analytic Hierarchy Process (AHP), which was proposed by Saaty in 1970s, consists of elements expressed on a numerical scale. The purpose of this paper is to propose a consistency test for ordinality of items in the pairwise comparison matrix. The original of this test is in a sensory test. In a sensory test we use a pick-the-winner ordinal scale to obtain the table of preferences for objects. In 1940 Kendall and Babington Smith proposed a consistency test for the preference table, using the number of circular triads in it. In this paper we show how to apply their test to a pairwise comparison matrix in the binary AHP and to one without a tie for up to nine items in the AHP. This is to test, using a pairwise comparison matrix, whether or not we can accept that items which are factors or alternatives are sufficiently ranked linearly before calculating weights of these items.

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CONGESTION IN THE NEW BRITISH UNIVERSITIES : A FURTHER ANALYSIS(<Special Issue>Operations Research for Performance Evaluation)

Anthony T. Flegg, David O. Allen

Article type: Article
2009 Volume 52 Issue 2 Pages 186-203
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.186

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The focus of this paper is on the problem of congestion, which refers to a situation where the use of a certain input has increased by so much that output has actually fallen. This problem is explored using the methodological framework proposed by Fare et al. Annual data are examined for a sample of 41 new British universities in the period 1995/6 to 2003/4. These former polytechnics were granted university status in 1992. A widespread problem of congestion is identified. The results reveal that the order in which technical efficiency is decomposed into scale efficiency, congestion efficiency and pure technical efficiency makes a noticeable difference to the amount of congestion identified. The results also clearly indicate that an excessive number of undergraduate students is the largest single cause of congestion in these new universities. The paper concludes by considering the results from the alternative approach to the measurement of congestion formulated by Cooper et al.

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AN EVALUATION OF FACTORY PERFORMANCE UTILIZED KPI/KAI WITH DATA ENVELOPMENT ANALYSIS(<Special Issue>Operations Research for Performance Evaluation)

Koichi Murata, Hiroshi Katayama

Article type: Article
2009 Volume 52 Issue 2 Pages 204-220
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.204

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In this paper, based on Key Performance Indicator (KPI) and Key Activity Indicator (KAI) as the fundamental data for calculating defined factory performance function, evaluation system of factory performance is discussed by following four phases. 1) Designing framework for evaluation system of factory performance, 2) Constructing structure of KPI/KAI database, 3) Formulating evaluation of factory performance with proposed model utilized Data Envelopment Analysis (DEA) and 4) Classifying analyzed factories based on established factory performance values.

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[title in Japanese]

Article type: Appendix
2009 Volume 52 Issue 2 Pages App4-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.App4

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[title in Japanese]

Article type: Cover
2009 Volume 52 Issue 2 Pages Cover5-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.Cover5

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[title in Japanese]

Article type: Cover
2009 Volume 52 Issue 2 Pages Cover6-
Published: 2009
Released on J-STAGE: June 27, 2017

DOIhttps://doi.org/10.15807/jorsj.52.Cover6

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