R&D Project Performance Evaluation With Multiple and Interdependent Criteria

In this study, we develop an approach based on analytic network process (ANP) and data envelopment analysis (DEA) to evaluate the performance of Research and Development projects. We identify a set of criteria and subcriteria having interdependencies among themselves. Interdependency is treated usin...

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Bibliographic Details
Published in:IEEE transactions on engineering management Vol. 57; no. 4; pp. 620 - 633
Main Authors: Tohumcu, Zeynep, Karasakal, Esra
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
AHP-Verfahren
Analytic network process (ANP)
Criteria
Data envelopment analysis
data envelopment analysis (DEA)
Data-Envelopment-Analyse
Decision making
group decision making
Gruppenentscheidung
Industrieforschung
Interdependence
Intervals
Mathematical analysis
Matrices
Matrix methods
Monitoring
Multikriterielle Entscheidungsanalyse
multiple criteria decision making
Networks
Performance evaluation
Personnel
Projektbewertung
Projektmanagement
R&D
R&D project performance evaluation
Research & development
Research and development
Studies
ISSN:0018-9391, 1558-0040
Online Access:Get full text
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Summary:In this study, we develop an approach based on analytic network process (ANP) and data envelopment analysis (DEA) to evaluate the performance of Research and Development projects. We identify a set of criteria and subcriteria having interdependencies among themselves. Interdependency is treated using a hybrid ANP model consisting of both hierarchy and network. The interval pairwise comparison matrices are constructed in a group decision-making process. ANP is extended to obtain interval weights from the interval pairwise comparison matrices. Interval weights are formulated as assurance region constraints in a super-efficiency DEA model, through which the project ranking is obtained. The super-efficiency DEA model is also modified to handle missing data. The approach is applied to a real case study on performance evaluation of the ongoing projects in a Defense Research and Development Institute.
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ISSN:0018-9391
1558-0040
DOI:10.1109/TEM.2009.2036159