Science and Technology Parks (STPs) are clusters of companies managed by specialized teams, aiming to foster innovation and regional development. As a public policy tool, they have been implemented in both developed and emerging countries to stimulate economic activity through ecosystems grounded in knowledge and technology. Despite their widespread adoption, the effectiveness of STPs has been questioned, sparking an ongoing and active debate.
The academic literature on STPs has predominantly focused on their impact on companies located within their boundaries. Two main evaluation approaches have been used:
Homogeneous, which assumes that all STPs have a uniform average effect on businesses and that all companies benefit equally.
Heterogeneous, which recognizes that certain STP characteristics and specific company traits may influence the magnitude of the benefits achieved.
Most existing studies have evaluated the quantity of innovation, often measured by the number of patents. However, this approach overlooks the fact that not all patents carry the same value or significance, which limits the reliability of this metric. This gap highlights the importance of assessing patent quality to provide a more comprehensive understanding of innovation outcomes.
This doctoral thesis aims to contribute to the STP literature by introducing patent quality as an evaluation metric, which has not been previously explored in this field. The study also incorporates both homogeneous and heterogeneous approaches to analyze the interaction between the characteristics of STPs and the firms within them. Furthermore, it adopts a regional perspective and applies advanced econometric techniques, such as the difference-in-difference staggered approach, which offers a more robust and detailed analysis of STP impacts.
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