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

• Published in: International journal of production research Vol. 43; no. 24; pp. 5199 - 5216
• Main Authors: Mohanty, R. P., Agarwal, R., Choudhury, A. K., Tiwari, M. K.
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis Group 15.12.2005; Washington, DC Taylor & Francis; Taylor & Francis LLC
• Subjects: Analytical network process (ANP); Applied sciences; Decision making; Decision theory. Utility theory; Exact sciences and technology; Fuzzy set; Fuzzy sets; Net present value (NPV); Operational research and scientific management; Operational research. Management science; Operations research; R&D; Research & development; Research and development(R&D); Stakeholders; Studies; Decision support system; Decision making; Research and development (R&D); Project selection; Fuzzy set; Fuzzy neural nets; Research and development; Fuzzy logic; Net present value (NPV); Multicomponent analysis; Analytical method; Fuzzy number; Analytical network process (ANP)
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207540500219031

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.