A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem


OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, vol.73, pp.79-92, 2017 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 73
  • Publication Date: 2017
  • Doi Number: 10.1016/j.omega.2016.12.006
  • Journal Indexes: Science Citation Index Expanded, Social Sciences Citation Index, Scopus
  • Page Numbers: pp.79-92
  • Keywords: Multiple criteria sorting, Data envelopment analysis, Interval analytic hierarchy process, UTADIS, R&D project selection, ANALYTIC HIERARCHY PROCESS, DEA-DISCRIMINANT ANALYSIS, GOAL PROGRAMMING METHOD, EFFICIENCY, RANKING, WEIGHTS, PERFORMANCE, MODEL, MCDM, MULTIPLE


In this paper, multiple criteria sorting methods based on data envelopment analysis (DEA) are developed to evaluate research and development (R&D) projects. The weight intervals of the criteria are obtained from Interval Analytic Hierarchy Process and employed as the assurance region constraints of models. Based on data envelopment analysis, two threshold estimation models, and five assignment models are developed for sorting. In addition to sorting, these models also provide ranking of the projects. The developed approach and the well-known sorting method UTADIS are applied to a real case study to analyze the R&D projects proposed to a grant program executed by a government funding agency in 2009. A five level R&D project selection criteria hierarchy and an assisting point allocation guide are defined to measure and quantify the performance of the projects. In the case study, the developed methods are observed to be more stable than UTADIS. (C) 2016 Elsevier Ltd. All rights reserved.