Abstract
Enterprise modeling is concerned with the systematic development of a comprehensive and holistic representation of an enterprise (an enterprise model) to support organisational initiatives. Domain experts have an essential role in enterprise modeling projects (EM), as they provide the required domain knowledge or specifics of the organisation under consideration. The paper investigates if neural text generators (large language models) can reduce the dependency on domain experts for certain tasks in enterprise modeling. The main contributions of this paper are (1) a systematic literature analysis on neural text generator use in EM, (2) the identification of potential for applying large language models in EM, and (3) findings from quasi-experiments comparing output of ChatGPT and domain experts for the same EM task.
Paper Type
Full Paper
DOI
10.62036/ISD.2023.44
Neural Text Generators in Enterprise Modeling: Can Chatgpt be Used as Proxy Domain Expert?
Enterprise modeling is concerned with the systematic development of a comprehensive and holistic representation of an enterprise (an enterprise model) to support organisational initiatives. Domain experts have an essential role in enterprise modeling projects (EM), as they provide the required domain knowledge or specifics of the organisation under consideration. The paper investigates if neural text generators (large language models) can reduce the dependency on domain experts for certain tasks in enterprise modeling. The main contributions of this paper are (1) a systematic literature analysis on neural text generator use in EM, (2) the identification of potential for applying large language models in EM, and (3) findings from quasi-experiments comparing output of ChatGPT and domain experts for the same EM task.
Recommended Citation
Sandkuhl, K., S. Barn, B., & Barat, S. (2023). Neural Text Generators in Enterprise Modeling: Can Chatgpt be Used as Proxy Domain Expert?. In A. R. da Silva, M. M. da Silva, J. Estima, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development, Organizational Aspects and Societal Trends (ISD2023 Proceedings). Lisbon, Portugal: Instituto Superior Técnico. ISBN: 978-989-33-5509-1. https://doi.org/10.62036/ISD.2023.44