Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes

[2504.02553] Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Software Engineering arXiv:2504.02553 (cs) [Submitted on 3 Apr 2025 ( v1 ), last revised 14 Apr 2026 (this version, v2)] Title: Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes Authors: Stefano Lambiase , Gemma Catolino , Fabio Palomba , Filomena Ferrucci , Daniel Russo View a PDF of the paper titled Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes, by Stefano Lambiase and 4 other authors View PDF HTML (experimental) Abstract: Context: The advent of Large Language Models (LLMs) is transforming software development, significantly enhancing software engineering (SE) processes. Research has explored their role within development teams, focusing on the specific purposes for which LLMs are used within SE tasks, such as artifact generation, decision-making support, and information retrieval. Despite the growing body of work on LLMs in SE, most studies have centered on broad adoption trends, neglecting the nuanced relationship between individual cognitive and behavioral factors and their impact on purpose-specific adoption. While factors such as perceived effort and performance expectancy have been explored at a general level, their influence on distinct SE purposes remains underexamined. This gap hinders the development of tailored LLM-based systems (e.g., Generative AI Agents) that align with engineers' specific needs and limits the ability of team leaders to devise effective strategies for fostering LLM adoption in targeted workflows. Objectives: For the reasons mentioned above, this study aims to study the individual factors that drive the choice to use LLMs for distinct SE purposes. Methods: To achieve the above-mentioned objective, we surveyed 188 software engineers to test the relationship between individual attributes related to technology adoption and LLM adoption across five key purposes, using structural equation modeling (SEM). The Unified Theory of Acceptance and Use of Technology (UTAUT2) was applied to characterize individual adoption behaviors. Results: The findings reveal that purpose-specific adoption is influenced by distinct factors, some of which negatively impact adoption when considered in isolation, underscoring the complexity of LLM integration in SE. Subjects: Software Engineering (cs.SE) Cite as: arXiv:2504.02553 [cs.SE] (or arXiv:2504.02553v2 [cs.SE] for this version) https://doi.org/10.48550/arXiv.2504.02553 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1016/j.infsof.2026.108295 Focus to learn more DOI(s) linking to related resources Submission history From: Stefano Lambiase Prof [ view email ] [v1] Thu, 3 Apr 2025 13:07:04 UTC (170 KB) [v2] Tue, 14 Apr 2026 04:43:24 UTC (132 KB) Full-text links: Access Paper: View a PDF of the paper titled Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes, by Stefano Lambiase and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.SE < prev | next > new | recent | 2025-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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