A Dynamic MAUT Decision Model for R&D Project Selection

R&D is an economical activity plenty of decision problems involving risk and uncertainty, and how to select the optimal candidate project that can make optimal use of the limited available resources is a difficulty question. However, the commonly used methods usually ignore risk propensity of decision-makers and can´t reflect the sensitivity of ranking results. In order to solve this problem, a dynamic MAUT decision model is proposed for R&D project selection. From the perspective of risk and profit, choose technological risk, market risk and economic benefits as the decision attributes and construct utility functions for each attribute; and then, through a dynamic weight evaluation method to simulate the change of attributes´ weights; and finally select the best alternative according to the simulation statistics. For illustration, a real R&D investment example is utilized to show the feasibility and effectiveness of this model. Empirical results show that it not only can take decision-makers´ risk propensity and risk tolerance into account, but also can provide indications for a robustness control and reflect the sensitivity of the ranking results. The dynamic MAUT decision model helps decision-makers analyzing comprehensively and dynamically so that an organization can use to improve quality of its project selection.