Socio-Technical Antecedents of Social Entrepreneurial Intention: The Impact of Generational Differences, Artificial Intelligence Familiarity, and Social Proximity

This study examines the factors that influence individuals’ intentions to create socially oriented ventures, emphasizing the joint role of social and technical systems. Grounded in Socio-Technical Systems Theory, the research investigates how perceptions of social legitimacy and technological infras...

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Bibliographic Details
Published in:Systems
Main Authors: Rob Kim Marjerison, Jin Young Jun, Jong Min Kim
Format: Article
Language:English
Published: MDPI AG 2025-07-01
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Online Access:https://www.mdpi.com/2079-8954/13/7/616
Description
Summary:This study examines the factors that influence individuals’ intentions to create socially oriented ventures, emphasizing the joint role of social and technical systems. Grounded in Socio-Technical Systems Theory, the research investigates how perceptions of social legitimacy and technological infrastructure shape social entrepreneurial intention (SEI) and how these effects are conditioned by generational cohort, familiarity and intent to use artificial intelligence (AI), and social proximity to entrepreneurial peers. Based on survey data from 388 respondents in China who expressed interest in both entrepreneurship and social problem-solving, the study applies a conditional process structural equation model to capture the complex interplay between external systems and individual-level readiness. The results show that both social and technical systems significantly and positively influence SEI, particularly among younger generations (Millennials and Generation Z). Furthermore, AI familiarity and social proximity operate as moderated mediators, differentially transmitting and shaping systemic influences on SEI. These findings advance the theoretical understanding of socio-technical determinants of social entrepreneurship and offer practical insights for fostering inclusive, generationally responsive entrepreneurial ecosystems.
ISSN:2079-8954