A fuzzy ANP-based approach to R&D project selection: A case study

Abstract

Research and development (R&D) project selection is a complex decision-making process. It involves a search of the environment of opportunities, the generation of project options, and the evaluation by different stakeholders of multiple attributes, both qualitative and quantitative. Qualitative attributes are often accompanied by certain ambiguities and vagueness because of the dissimilar perceptions of organizational goals among pluralistic stakeholders, bureaucracy and the functional specialization of organizational members. Such differences in perceptions often hinder the attainment of consensus and coordination. Therefore, failures are frequent in R&D investment planning. To perceive the preferences of the various stakeholders and to map them into an analytical decision-making framework are challenging tasks. Further, risks and uncertainties are also associated with the investments and returns of R&D projects. This paper illustrates an application of fuzzy ANP (analytic network process) along with fuzzy cost analysis in selecting R&D projects. Fuzzy set theory is incorporated to overcome the vagueness in the preferences. The method adopted uses triangular fuzzy numbers for pair-wise comparison and applies extent analysis followed by defuzzification to determine the weights for various attributes.