interval-valued triangular fuzzy - gray relationship analysis

Research and development (R&D) department is an essential and critical section for all organizations, which are eager to actively participate in markets and strategies on R&D management. Today’s investment in this field has been approved and all organizations are aware of its role to increase competitive risk. Improving R&D departments and promoting the efficiency of companies can help a country to move toward knowledge-based economy and also assist to stop illogical exchange currency flow to foreign countries against import of technology transfer from them. A problem in a domestic market is the lack of the R&D strategy to produce new products and promote the customer’s satisfaction level in industrial companies. The objective of this research is to introduce a two-phase decision-making approach to assess R&D strategies in automotive battery industries stressing on the customer’s satisfaction parameter. In the first section, the practical strategies on R&D management and the effective indices of the customer’s satisfaction on R&D strategies are recognized. In the second section, weighting coefficients related to customer’s satisfaction indices are reached by utilizing the fuzzy best-worst method (FBWM) as an effective multi-criteria decision-making (MCDM) method. Moreover, the weight of any individual strategy and their final prioritization is calculated using the analytical method of the interval-valued triangular fuzzy - gray relation analysis (IVTFN-GRA). Based on the results gained from the proposed FBWM, three effective factors in evaluating R&D strategies in an automotive battery industry are recognized. Finally, among the existing strategies, the joint R&D strategy with 0.375 rate is selected