The aim of this paper is to empirically examine the influence of different types of credibility on the legitimacy to grant individual actors within consortia an innovation subsidy. Theorizing from the resource dependence view and the sociology of expectations, we hypothesize that four types of credibility are related to legitimacy: scientific credibility, market credibility, expectation track record, and social capital. Further, we operate on two levels of analysis, the actor and the consortium level. Empirically, we quantitatively analyze the Dutch electric vehicle subsidy program as a case study. We develop a model that accurately forecasts which consortia are most likely to receive subsidies. We demonstrate that social capital and market credibility positively influence the likelihood of receiving innovation subsidies, while scientific credibility sources and expectation track record have a negative influence. Based on these findings we provide policy recommendations and avenues for further research.Jelcodes:O38,- Credibility and legitimacy in policy driven innovation networks: Resource dependencies and expectations in Dutch electric vehicle subsidies AbstractThe aim of this paper is to empirically examine the influence of different types of credibility on the legitimacy to grant individual actors within consortia an innovation subsidy. Theorizing from the resource dependence view and the sociology of expectations, we hypothesize that four types of credibility are related to legitimacy: scientific credibility, market credibility, expectation track record, and social capital. Further, we operate on two levels of analysis, the actor and the consortium level.Empirically, we quantitatively analyze the Dutch electric vehicle subsidy program as a case study. We develop a model that accurately forecasts which consortia are most likely to receive subsidies. We demonstrate that social capital and market credibility positively influence the likelihood of receiving innovation subsidies, while scientific credibility sources and expectation track record have a negative influence. Based on these findings we provide policy recommendations and avenues for further research.