Generative artificial intelligence (GenAI) and entrepreneurial performance: implications for entrepreneurs

Ailing Liu () and Shaofeng Wang ()
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Ailing Liu: Ningbo University of Technology
Shaofeng Wang: Fuzhou University of International Studies and Trade

The Journal of Technology Transfer, 2024, vol. 49, issue 6, No 15, 2389-2412

Abstract: Abstract This study examines the impact of Generative Artificial Intelligence (GenAI) resources on entrepreneurial performance in China, focusing on internal integration and external collaboration mediating roles. Drawing upon Resource-Based Theory (RBT), this study proposes a theoretical model that outlines how tangible, intangible, and human resources related to GenAI affect entrepreneurial performance. GenAI internal integration and external collaboration serve as mediators. A purposive sampling technique was employed to collect data from Chinese university students who have initiated startups utilizing GenAI technologies. The Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was applied to analyze data from 491 respondents. Findings reveal that GenAI’s tangible, intangible, and human resources significantly foster both internal integration and external collaboration, which, in turn, positively influence entrepreneurial performance. This study contributes to the entrepreneurship and management literature by elucidating the mechanism through which GenAI resources enhance entrepreneurial outcomes, and offers practical insights for entrepreneurs on leveraging GenAI resources to bolster internal and external collaborative efforts for improved performance.

Keywords: Generative artificial intelligence; Entrepreneurial performance; Resource-based theory; Internal integration; External collaboration; Chinese university student entrepreneurs (search for similar items in EconPapers)
JEL-codes: L26 M13 M15 O32 O33 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10961-024-10132-3

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