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 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.