Theses and Dissertations

Date of Award

5-1-2026

Document Type

Thesis

Degree Name

Master of Business Administration (MBA)

Department

Information Systems

First Advisor

Xuan Wang

Second Advisor

Murad Moqbel

Third Advisor

Geng Sun

Abstract

AI adoption and its widespread use have sparked debates about the future of work, job displacement, and the evolving entrepreneurial landscape. While AI is often seen as a threat to traditional employment, research shows that this emerging technology is more likely to change task structures rather than eliminate entire occupations or industries. This shows that there are new entrepreneurial opportunities, particularly digital, that potential entrepreneurs can venture into. This thesis uses a meta-analytic approach to study the relationship between AI adoption and digital entrepreneurial intention, addressing inconsistencies in current research.

Following PRISMA guidelines, a comprehensive search was conducted across Web of Science, Scopus, and ScienceDirect, focusing on quantitative studies published from 2022 onward. After screening was completed, 26 studies were included in the final meta-analysis. Effect sizes were analyzed using R, with Fisher’s Z transformations applied to estimate pooled relationships and assess heterogeneity. The analysis examined the direct effect of AI adoption on digital entrepreneurial intention, the comparative relationship of perceptual AI adoption constructs on digital entrepreneurial self-efficacy and digital entrepreneurial intention, and the moderating roles of AI construct types, sample populations, and educational levels.

The results display a statistically significant and positive relationship between AI adoption and digital entrepreneurial intention, suggesting that working with AI-related tools and understanding how to use them drives people to be more motivated to pursue digital entrepreneurship.

Comments

Copyright 2026 Xandra P. Okori. All Rights Reserved. https://proquest.com/docview/3371164102

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