Requirements:
Basic economics and statistics
Learning Outcome:
By the end of the course, students will be able to: Explain and apply an ecosystem perspective to technological and social innovation across multiple scales (firm, territory, region, state, global networks). Diagnose socio-economic and institutional drivers/barriers and critically assess R&I policies and strategies, identifying governance arrangements, incentives, stakeholder configurations, objectives, instruments, trade-offs, and likely mechanisms of change. Design theory-based evaluation frameworks for innovation interventions under uncertainty, including theory of change, key assumptions, risks, learning dynamics, and potential unintended effects. Operationalize evidence and methods and communicate actionable findings, selecting appropriate quantitative/qualitative/mixed-method approaches, defining indicators and data strategies, interpreting results (including sustainability and social-impact implications), and translating them into recommendations for policymakers and stakeholders.
Content:
The course equips students with economic analysis and evaluation tools to examine innovation and entrepreneurship. Grounded in an ecosystem perspective, it trains students to assess how innovation is shaped by the interplay among firms, public institutions, universities, intermediaries, and other stakeholders, and by the rules, incentives, and resources that structure these relationships across multiple scales.
Students will work with real-world cases of public–private strategies, innovation programmes, and entrepreneurial initiatives. Using a complexity-sensitive evaluation approach, they will analyze how change unfolds through adaptation, learning, emergent dynamics, and unintended effects. The course also examines the socioeconomic and politico-institutional conditions that enable—or constrain—sustainability transitions, and the implications for competitiveness, inclusion, and territorial cohesion.
A core component develops students’ capacity to design and conduct theory-based evaluations of innovative and experimental interventions under uncertainty. By integrating quantitative and qualitative evidence (mixed methods), students will assess outcomes in terms of sustainability and societal impact and translate findings into actionable recommendations to strengthen innovation policies and improve the design of innovation-driven services, processes, programmes, and ventures.
