Oct 2026· The International Journal of Management Education· 74 references
Entrepreneurship Studies and Influences
Abstract
Generative artificial intelligence (GAI) is rapidly evolving and creating new possibilities for supporting students' entrepreneurial development. However, limited research has examined how GAI usage is associated with entrepreneurial intention (EI) through specific psychological pathways. Drawing on self-efficacy theory, this study examines the relationship between GAI usage and EI, focusing on the mediating roles of task and social self-efficacy. Using survey data from 521 Chinese university students, this study empirically tests the proposed model. The results show that GAI usage is positively associated with students' task and social self-efficacy. However, task self-efficacy (TSE) is not directly associated with EI. In contrast, social self-efficacy (SSE) accounts for a significant indirect association between GAI usage and EI. Moreover, a significant sequential indirect association is observed, linking GAI usage with EI through TSE and SSE. By disentangling the distinct roles of TSE and SSE, this study shows that the association between GAI usage and EI is consistent with pathways that differ in their functions and proximity to entrepreneurial action. The findings also provide practical insights for entrepreneurship education and AI-supported learning environments.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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