Correspondence: julio.raffo@wipo.int

Summary of the Session’s Theme and Objectives

How can policymakers prioritize technologies or industries when designing innovation and industrial policies that build on their local innovation ecosystem? Economies and regions can benefit greatly from any guidance on where to focus their limited resources to clear the innovation roadblocks between science, innovation and industries. National governments are increasingly making critical decisions in the fields of science, technology, and innovation (STI) policy, which affect resource allocation decisions by various public and private actors within different innovation ecosystems.
As a result, many policymakers and entrepreneurs turn to innovation as a potential solution for increasing the innovativeness of companies, industries, regions and countries to build economic resilience when facing current and future crises.  How can governments make STI policy decisions that are informed by local capabilities? Innovation capabilities are essential drivers of competitive outcomes in science, technology, and production. “Big Data” plays a crucial role in identifying these local capabilities and understanding how they are interconnected. Through the analysis of large volumes of data, experts can uncover patterns, correlations, and trends that inform policymakers, enabling them to identify opportunities that align with the unique potential of each country or region.
This context invites a rethinking of how STI policies are prioritized, designed, and evaluated. There is growing consensus that decisions should not be made in isolation and through centralized (“top-down”) approaches, but rather by considering the local capabilities and needs of innovation ecosystems. Approaches like “smart specialization” emphasize the need for policies grounded in local diagnostics and knowledge, leveraging each region’s existing skills and, above all, addressing its specific challenges. However, surveying local capabilities in a “bottom-up” manner across all innovation ecosystems may be unfeasible for a national government.

List of Topics to Be Presented in the Special Session

• The use of innovation and IP related big data to inform industrial and innovation policymaking
• Mapping regions and countries innovation dynamism with innovation and IP data
• Measuring innovation relatedness and complexity with innovation and IP data for policy design
• Empirical analysis of Smart specialization and regional innovation policies and IP rights
• Connecting insights from scientific, technological, production and other innovation related data
• Knowledge similarity and complementarity across STI domains 

Key References

Balland, P.-A., Broekel, T., Diodato, D., Giuliani, E., Hausmann, R., O’Clery, N., & Rigby, D. (2022). The new paradigm of economic complexity. Research Policy, 51(3), 104450. 
Balland, P. A., Boschma, R., Crespo, J., & Rigby, D. L. (2019). Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification. Regional studies, 53(9), 1252-1268.
Boschma, R., Balland, P. A., & Kogler, D. F. (2015). Relatedness and technological change in cities: the rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010. Industrial and corporate change, 24(1), 223-250.
Deegan, J., Broekel, T., & Fitjar, R. D. (2021). Searching through the Haystack: The relatedness and complexity of priorities in smart specialization strategies. Economic Geography, 97(5), 497-520.
Diodato, D., Napolitano, L., Pugliese, E., Tacchella, A., & European Commission (Eds.). (2024). Handbook of economic complexity for policy. Publications Office. 
Foray, D., David, P.A. and Hall, B. (2009), “Smart specialisation: the concept”, Knowledge for Growth: Prospects for Science, Technology and Innovation, EUR 24047 EN, European Commission.
Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the national academy of sciences, 106(26), 10570-10575. 
Moscatelli, F., Raffo, J., Chacua, C., Hartog, M., Yildirim, M. A., Hausmann, R., & Gadgin Matha, S. (2024). Can we map innovation capabilities? (No. 81). World Intellectual Property Organization. 
Pugliese, E., Cimini, G., Patelli, A., Zaccaria, A., Pietronero, L., & Gabrielli, A. (2019). Unfolding the innovation system for the development of countries: Coevolution of Science, Technology and Production. Scientific Reports, 9(1), Article 1. https://doi.org/10.1038/s41598-019-52767-5
Stojkoski, V., Koch, P., & Hidalgo, C. A. (2023). Multidimensional economic complexity and inclusive green growth. Communications Earth & Environment, 4(1), 1–12. https://doi.org/10.1038/s43247-023-00770-0
WIPO (2024) World IP Report, Making Innovation Policy Work for Development, Geneva, Switzerland