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This study provides new empirical evidence regarding the relevance of evaluation criteria and firm characteristics for public R&D funding decisions. The database used contains both accepted and rejected R&D project proposals, project evaluation scores, and several firm characteristics. The probit estimations show that proposals with high scores on innovative content, spillover, and knowledge gain are significantly more likely to be approved and that most firm-level characteristics are not significant, except for firm size. For example, good or very good assessments of innovative content raise the acceptance probability by between 18 and 37 percentage points, respectively. Small firms are more likely to receive a grant.

The purpose of this study is to present a unique database on commercialized patents and to illustrate how it can be used to analyze the commercialization process of patents. The dataset is based on a survey of Swedish patents owned by inventors and small firms with a remarkably high response rate of 80 percent. It contains some key variables on commercialization not found anywhere else, including whether, when and how (acquisition, licensing, existing or new firm) patents were commercialized as well as whether this commercialization was profitable or not. Thus, this patent database measures technological innovation. The dataset is complemented with indicators of patent quality (patent renewal, forward citations, and patent family) from archive sources. Basic statistics for the key variables are described. Finally, the scientific output in terms of published articles in peer-reviewed journals shows how this database can be used to analyze the commercialization process of patents. The dataset has, for instance, been used to 1) evaluate government loan programs for inventors; 2) analyze the different roles of the inventor and the Schumpeterian entrepreneur during commercialization; 3) estimate the transfer of tacit knowledge when patents are sold or licensed; and 4) analyze the entry strategy among inventors in oligopolistic markets.