Analysis of the use of Large-Scale Language Models (LLMs) in SMEs in the Guadalajara Metropolitan Area: Tools, Tasks, and Perceived Benefits

Luis Roberto Castro-Hernández (), Ricardo Arechavala-Vargas () and Marlon Israel Nuño-Rodríguez ()
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Luis Roberto Castro-Hernández: Universidad de Guadalajara, Mexico
Ricardo Arechavala-Vargas: Universidad de Guadalajara, Mexico
Marlon Israel Nuño-Rodríguez: Universidad de Guadalajara, Mexio

European Journal of Studies in Management and Business, 2025, vol. 35, 18-33

Abstract: This research examines how Small and Medium-sized Enterprises (SMEs) in Guadalajara’s Metropolitan Area are incorporating Large Language Models (LLMs) into their operations. Beyond simply mapping adoption, it explores the specific tools in use, the tasks they support, the organizational areas they influence, and the benefits companies perceive from their implementation. Adopting a quantitative design, the study will draw on data collected through a questionnaire administered to a representative sample of SMEs across diverse sectors. Key variables, namely frequency of use, user profiles, functional areas involved, types of tasks performed, perceived advantages, and decision-making factors, will be systematically analyzed. Statistical techniques, including descriptive, comparative, and correlational analyses, will be applied to reveal usage patterns and relationships among variables. The resulting evidence will provide a nuanced picture of how LLMs are transforming the local business landscape. These insights aim to inform public policy and guide technological adoption strategies, fostering broader and more effective integration of Artificial Intelligence tools within SMEs in Jalisco.

Keywords: Large Language Models; SMEs; Generative Artificial Intelligence; Productivity; Technological Adoption (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bco:mbrqaa::v:35:y:2025:p:18-33

DOI: 10.32038/mbrq.2025.35.02

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