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Using the Large Language Model ChatGPT to Support Decisions in Sustainable Transport

Author

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  • Paweł Ziemba

    (Institute of Management, University of Szczecin, 70-453 Szczecin, Poland)

  • Filip Majewski

    (Faculty of Computer Science and Telecommunications, Maritime University of Szczecin, 70-500 Szczecin, Poland)

Abstract

Recently, the popularity of large language models (LLMs) used as artificial intelligence tools supporting humans has been growing. LLMs are applied in many fields, including increasingly for various sustainability-related issues. One of the most popular tools of this type is ChatGPT, which, after being supplied with appropriate knowledge, can act as a domain expert, including in the area of sustainable transport. The article uses this functionality of ChatGPT, feeding it with knowledge about electric vehicles (EVs) available on the Polish market. The aim of the research was to develop a solution based on an LLM, which will act as an advisor when buying an EV. After appropriate modelling of knowledge and feeding it into ChatGPT, an expert system was obtained, which, based on the defined needs of the user, recommends the most suitable EV for them. When answering the system’s questions, the user provides only a description of the decision-making situation at the LLM input (e.g., the locations to which they are travelling, information on the number of family members, etc.). In turn, the appropriately fine-tuned ChatGPT provides a recommendation of vehicles that meet the user’s defined needs. This is a very user-friendly solution because it does not require the user to precisely define the vehicle evaluation criteria or a set of alternatives. This approach also does not require the user to have detailed domain knowledge.

Suggested Citation

  • Paweł Ziemba & Filip Majewski, 2025. "Using the Large Language Model ChatGPT to Support Decisions in Sustainable Transport," Sustainability, MDPI, vol. 17(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7520-:d:1728554
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    References listed on IDEAS

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    1. Alberto Menéndez Medina & José Antonio Heredia Álvaro, 2024. "Using Generative Pre-Trained Transformers (GPT) for Electricity Price Trend Forecasting in the Spanish Market," Energies, MDPI, vol. 17(10), pages 1-15, May.
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    5. Paweł Ziemba & Marek Kannchen & Mariusz Borawski, 2024. "Selection of the Family Electric Car Based on Objective and Subjective Criteria—Analysis of a Case Study of Polish Consumers," Energies, MDPI, vol. 17(6), pages 1-27, March.
    6. Jay N. Meegoda & Daniel Watts & Udaysinh Patil, 2025. "Regulations and Policies on the Management of the End of the Life of Lithium-Ion Batteries in Electrical Vehicles," Energies, MDPI, vol. 18(3), pages 1-39, January.
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