Join Clara Krämer and Malte Toetzke from the Technical University of Munich
for a thought-provoking discussion on how global innovation networks are driving climate technologies and shaping collaboration and policy worldwide.
Abstract:
Innovation networks are essential for advancing climate technologies, yet their structure and dynamics remain poorly understood. Using large language models to analyze 26 million LinkedIn posts, we map a global network of 166,459 organizations and 3 million partnerships across 189 countries. Our dataset spans 27 climate technologies and 17 collaboration types, including demonstration projects, product launches, adoption, and equity investments. We use this data to analyze how innovation networks and actor roles evolve over time and how public policy can foster network formation and spillovers.
About the speakers:
Clara Krämer is a PhD student and researcher at the Public Policy for the Green Transition research group at TUM. In her research, she analyses the effects of public policies for decarbonizing firms and households. Prior to joining the PPGT, Clara worked as a policy advisor for fiscal policy in the German Parliament and as an analyst for labour market policy at the OECD. Clara holds a Master’s Degree in Public Policy from the Hertie School of Governance and a Bachelor's Degree in Philosophy and Economics from the University of Bayreuth, in both of which she focused on quantitative policy analysis.
Malte Toetzke is a PostDoc at the PPGT Group holding a TUM Global Postdoc Fellowship. He focuses on the global transition towards net-zero emissions, informing public policy with evidence generated via novel data science and machine learning approaches. His main research areas are climate-tech innovation, climate finance, and green industrial policy and his research has been published and presented in leading academic journals (Nature Sustainability, Nature Climate Change) and machine learning conferences (NeurIPS, ICLR). Malte is also a co-founder of a tech-startup based on natural language processing and computer vision technology.
