Fayed, HatemWohlgemuth, VolkerWohlgemuth, VolkerKranzlmüller, DieterHöb, Maximilian2023-12-152023-12-152023978-3-88579-736-4https://dl.gi.de/handle/20.500.12116/43337As worldwide agreements aiming to reduce the carbon footprint keep coming into effect, many companies aim to become more efficient in their production process. However, it is costly to hire environmental experts to help with the efficiency and carbon reduction process. This research aims to analyze the possibility of creating a Recommender System (RS) which suggests Carbon Reduction Measures (CRM) to the users based on their Life Cycle Assessment (LCA) reports. Based on the literature review into the latest RS techniques and the available databases, a study was conducted into creating a RS prototype. Analysis of the results demonstrates, that with the currently available databases, it is not possible to create an effective RS. The results indicate that in order to be able to create a functional and useful RS more detailed data needs to be extractable from the LCA tool. Further research is needed into the exports from other Environmental Management Information Systems (EMIS) and the identification of other factors that could strengthen the effectiveness of the RS.enArtificial Intelligence; Resource and Energy Efficiency; Recommender System; Material and Energy Balance; LCAText/Conference Paper10.18420/env2023-0171617-5468