Looking for Best Performers: a Pilot Study towards the Evaluation of Science Parks

Science Parks are complex institutions that aim at promoting innovation and entrepreneurship at local level. Their activities entertain a large set of stakeholders going from internal and external researchers to entrepreneurs, local level public administration and universities. As a consequence, their performances extends on a large set of dimensions affecting each other. This feature makes Science Parks particularly difficult to be properly compared. However, evaluating their performances in a comparable way may be important for at least three reasons: (1) to identify best practices in each activity and allow a faster diffusion of these practices, (2) to inform potential entrepreneurs about institutions better supporting start-ups birth and first stages and (3) to guide public policies in the distribution of funds and incentives. The multidimensional nature of Science Parks raises the problem of aggregating performances in simple indexes that can be accessed by stakeholders willing to compare different structures on the basis of their own preferences. This paper exploits a new dataset on Italian Science Parks to provide a pilot study towards this direction. In particular, we apply Choquet integral based Multi-Attribute Value Theory to elicit stakeholders’ preferences on different dimensions of Science Parks’ performances and construct a robust index allowing to rank them. This tool can be used to support the decision making process of multiple stakeholders looking for best (or worst) performers and allows to account both for subjective nature of the evaluation process and the interactions among decision attributes. Despite the present study employs only a limited number of respondents and performance measures, the procedure we present can be straightforwardly adapted to much richer environments.