R&D Investment Game Strategies Revisited by Decision-Tree with R&D Incentives

Abstract

The primary objective of this research is to provide the best scenarios for firms and decision makers to take advantage of competitive situations where they take strategic actions to obtain the greatest benefit in various game situations. To make the R&D game model practically, we consider a strategic decision making process for competing firms in R&D investment markets where one is with a relatively higher brand image or cost functions and the other with low investment cost through non-infringing imitation. The scenarios take into account the effect of the presence and absence of patent protection on the firms’ strategic decisions that cause change in the competition, uncertain patent acquisition and the two firms’ cooperation & licensing options. Through the decision-making tree analysis, this research analyzes factors influencing decisions on R&D investment of two competing companies, draws expected profits and R&D incentives along decision-making paths. Especially, through DT analysis using not only payoff but strategic and non-strategic R&D incentives, we structure various variables included in the asymmetric R&D investment game model, and compare decision-making process based on expected values of decision-making nodes and changes of R&D incentives. Our findings are as follows: (1) The best strategy in an asymmetric competition situation analyzed through Decision-Tree using payoffs and R&D incentives for both companies is to compete through R&D investment and technology licensing decision. (2) The second-best strategy is to choose no-R&D decision for the superior Firm 1, and R&D cooperation for inferior Firm 2. (3) DT using R&D incentive enables us to analyze the best and the second-best strategies of firms with half times as many as the number of DT needed in using payoff, enhancing computational efficiency.