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As we have addressed in an earlier article, quantitative evaluation of R&D policies often approaches the outcomes of initiatives without effectively considering differential impacts on economic agents. Our goal is to confirm the existence of “segments” of firms according to their outcomes arising from participation in a given R&D program. Data is gathered from Eureka Program’s Final Reports (2000-2005 and 2006-2008) from Spanish, Italian, French, British, and German firms. Classification focus is directed towards variables related to innovation projects’ outcomes. Log-likelihood clustering method was used. Tests for differences between clusters in terms of some variables of interest were performed. Results are consistent with the hypothesis of marked heterogeneity in firms’ outcomes. This methodology offers a valuable instrument for RTD policymakers in terms of monitoring and ex post intervention

Firm Segmentation as a Tool for R&D Policy Evaluation: Revisiting the Taxonomy of Firms Engaged in International R&D Networks