Selecting R&D projects for technology-based innovation: Knowledge management in the face of embarras de choix

A vital question incorporated under the fundamental corporate strategy of technology-based innovation is that of ensuring that R&D would most effectively exploit technological change in the development of new or enhanced products and services. The literature contains a profusion of models, methods and techniques which guide R&D project selection. Three approaches are particularly important: one based on mathematical programming, one where project selection is understood as a process rationally embedded in the corporate behavioural, organisational, and informational structure, and one which requires projects to be strategically consistent-andintegrated. To assist the bounded-rational manager faced with this embarras de choix, the authors propose a heuristic framework which respects both the constraint imposed by decision costs and the principle that to optimise the use of knowledge as many as possible of the results from the literature should enter into the firm's decision-information shortlist. Exploiting this framework, the manager can readily compare the different approaches under the normative methodology of testing the empirical relevance of their assumptions against a core model description of the firm's 'real world' constructed according to the methodology of scientific realism. Once an approach which is methodologically best (most realistic) is found, the decision process can be refined upon further considerations of bounded rationality to determine a model, method, or technique under this approach which is simultaneously knowledge-optimal and operationally-satisficed.