Hunting Hotspots - A framework to assess the effectiveness of using environmentally extended input-output models as a method to identify CO2-eq hotspots in the upstream supply chain of a company

Abstract: Industry’s indirect upstream greenhouse gas (GHG) emissions contribute significantly to climate change. To identify and reduce them, some companies conduct a hotspot analysis using an environmentally extended input-output (EEIO) model (often utilizing EXIOBASE database). Despite the widespread use of EEIO models to identify hotspots in industry, their effectiveness in estimating GHG emissions has not yet been investigated. Therefore, this thesis explores what effectiveness constitutes in this context and compares the strengths and weaknesses of EEIO (and EXIOBASE) with alternative methods, such as using supplier-specific, average-data and hybrid methods (and other common EEIO databases: Eora, GTAP, WIOD). Using a mixed methods model of literature research, systematized literature review, and expert interviews, the results lead to an effectiveness framework with three dimensions and a precondition to determine its applicability. Finally, practical implications provide guidance for companies on how to apply it to positively contribute to carbon management and combating climate change.