Innovation Policy Evaluation – Challenges and Roads Ahead

Prior Work A vital development of innovation policies as well as innovation theories over the past couple of decades is the increased focus upon collaboration and networking between actors. It is, however, difficult to evaluate such activities with traditional evaluation metrics. The literature on innovation policy evaluations has established that outcomes of innovation policy programs should be regarded much broader than was the case less than two decades ago (e.g. Georghiou, 2007). Objectives The broader view on policy effects in evaluation studies implies incorporating more types of additionality including what has been denoted ‘behavioural additionality’. There is now a growing recognition that policy schemes also impact the behaviour and strategies of actors in a long term perspective. The literature has, though, been relatively silent in specifying what are really these broader effects. What are they, how can they be measured, and what are their effects? Approach The study is based upon interviews as well as observation studies. Reporting methods on how the network evolved and was evaluated are confronted with the theoretical and methodological discussion. The results from the paper are that the criteria for evaluating effects should be extended beyond the immediate, observable impact. Results It is found that using traditional evaluation metrics render an underestimation of indirect, hard to measure effects such as transfer of tacit knowledge, reputation effects, long-term benefits from networking, training effects in increased abilities to select and manage collaboration projects, and the general increase in connectivity of the innovation system. Value This study contributes to our understanding of how innovation network policies are evaluated. The paper firstly propose what should be included in comprehensive innovation network policy evaluation generally; then specify such considerations to a specific type of network; evaluates a specific case, and point out new avenues for innovation policy evaluation. Specifically, the paper discusses the possible rationale for governments to support business angel networks (BAN) and how this corresponds (or not) to how governments evaluate a specific BAN. Implications The implications are that awareness among governments on these potential positive side-effects is important to a comprehensive assessment of policy initiatives and generally to policy learning