On the performance and strategy of innovation systems: A multicriteria group decision analysis approach

Mainstream approaches to analyzing innovation systems are based on statistical methods, use standard sets of indicators, and are typically deployed to measure and classify innovation performance. As they are not based on decision-theoretic approaches that involve the multiple agents that are usually embedded in innovation systems, conventional approaches are rather inadequate to generate the strategy and describe the dynamics of innovation systems. Taking a rather different approach that has been motivated by the need to generate the strategy of innovation systems, we set out a methodology that lies at the intersection of strategy, innovation and decision theory. The methodology construes the strategy of an innovation system as a process that emerges from the evaluations of agents and the aggregation logics used to arrive at a group decision. The methodology draws upon the TOPSIS multicriteria decision analysis method, uses the Mahalanobis metric of distance and applies the Borda count to aggregate the preferences of multiple agents who participate as strategists in the process of allocating resources based on a set of agreed-upon indicators. The resulting methodology can be used in concert with different innovation frameworks using sets of indicators that may show varying degrees of correlation in order to drive the strategy of innovation systems as a dynamic group decision-theoretic process. •We set out a novel methodology for modeling the strategy of innovation systems.•The methodology addresses shortcomings of mainstream empirical approaches.•The methodology extends MCDA methods for multicriteria group decision-making.•The methodology can be used to model the dynamics of innovation systems.•The methodology can be used for policy engineering using agent-based modeling.