Enhancing Decision-Making in Purchasing to Reduce Carbon Emissions

This paper investigates the decision points of procurement professionals that have an impact on CO2 emissions. In order to support decision-makers in these decision processes to make emission reduced decisions, it is investigated how the integration of Knowledge Graph (KG) technology can be used and consequently reduce carbon emissions in supply chains.

Antonuccio, Deborah, 2023

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Laurenzi, Emanuele
Keywords
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The primary objective of the research is to find out how such a system can support procurement managers in making decisions to reduce CO2 emissions. The literature shows that KG-based knowledge bases are used in various industries to support decision-makers. In addition, the research addresses the challenges faced by supply chain managers, the prioritization of key information in a KG-based system and, its implementation.
The study focuses on the development of a KG-based decision support system through a literature review and a design science research methodology, including interviews with four experts working in the field of procurement in national and international companies.
The findings highlight the potential of KG in comparing materials based on CO2 emissions, contributing to emissions reduction within the supply chain. Challenges include the current lack of expertise in the procurement department in the area of sustainability and the methodology of calculating CO2 emissions within the supply chain. The study highlights the untapped potential of KG-based tools to guide procurement professionals to actively contribute to climate neutrality and net zero policy goals. Overall, the work argues that for the research purpose-defined problem, the integration of KG technology has the potential to bridge the gap between environmental goals and operational decisions in procurement.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Antonuccio, Deborah
Betreuende Dozierende
Laurenzi, Emanuele
Publikationsjahr
2023
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten