{"title":"Variable range measure: A new range measure for super-efficiency model based on DDF in presence of nonpositive data","authors":"Hsuan-Shih Lee","doi":"10.1016/j.omega.2025.103295","DOIUrl":null,"url":null,"abstract":"<div><div>In order to handle the nonpositive data and increase the discrimination power, we propose a new DDF super-efficiency model called variable range measure (VRM). VRM is translation-invariant and unit-invariant. VRM is feasible when data set contains zero or negative data. The super-efficiency obtained by VRM is less than or equal to two. Range adjusted measure (RAM) makes input contraction and output expansion along the direction vector in a balanced way, but it is target-invariant. The range directional model (RDM) for super-efficiency might be infeasible, but it is target-variant. We combine the advantages of RAM and RDM into VRM so that VRM is target-variant and feasible under super-efficiency. Output vector of the direction vector proposed by Lin and Liu (2019) (LL model) might be zero for some DMUs. VRM overcomes the shortcomings of the LL model. We show that the VRM direction vector is a good proxy of the RAM direction vector by examples.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"134 ","pages":"Article 103295"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Omega-international Journal of Management Science","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305048325000210","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
In order to handle the nonpositive data and increase the discrimination power, we propose a new DDF super-efficiency model called variable range measure (VRM). VRM is translation-invariant and unit-invariant. VRM is feasible when data set contains zero or negative data. The super-efficiency obtained by VRM is less than or equal to two. Range adjusted measure (RAM) makes input contraction and output expansion along the direction vector in a balanced way, but it is target-invariant. The range directional model (RDM) for super-efficiency might be infeasible, but it is target-variant. We combine the advantages of RAM and RDM into VRM so that VRM is target-variant and feasible under super-efficiency. Output vector of the direction vector proposed by Lin and Liu (2019) (LL model) might be zero for some DMUs. VRM overcomes the shortcomings of the LL model. We show that the VRM direction vector is a good proxy of the RAM direction vector by examples.
期刊介绍：
Omega reports on developments in management, including the latest research results and applications. Original contributions and review articles describe the state of the art in specific fields or functions of management, while there are shorter critical assessments of particular management techniques. Other features of the journal are the "Memoranda" section for short communications and "Feedback", a correspondence column. Omega is both stimulating reading and an important source for practising managers, specialists in management services, operational research workers and management scientists, management consultants, academics, students and research personnel throughout the world. The material published is of high quality and relevance, written in a manner which makes it accessible to all of this wide-ranging readership. Preference will be given to papers with implications to the practice of management. Submissions of purely theoretical papers are discouraged. The review of material for publication in the journal reflects this aim.
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