A Linguistic Approach to Measuring the Attractiveness of New Products in Portfolio Selection

To gain a competitive edge, companies must continually invest in new product development (NPD), and must decide how to strategically allocate limited resources. The most critical NPD activity is the accurate assessment of the attractiveness of new products, simultaneously considering favorable factors (project value and strategic fit) and unfavorable factors (project risks), especially in robust companies in developing countries. In the NPD development process, the attractiveness of products is often evaluated using information that is imprecise or ambiguous. Fuzzy logic is well-suited to inform NPD decision-making. Thus, a comprehensive method considering both favorable and unfavorable factors, and using a fuzzy weighted average to devise a fuzzy possible-attractiveness rating (FPAR) of an NPD project for portfolio selection, is proposed in this paper. FPAR is a measurement of information, which is able to retain the multiplicity of that information. The proposed evaluation technique was demonstrated using a Taiwanese company as an example. The results indicated that this method provided an accurate assessment of overall product attractiveness, necessary for obtaining organizational buy-in, and can effectively aid managers to conduct sensitive analyses, balance the impact of changes in strategy, and receive quick feedback on the results of such changes.