Artificial Intelligence and Entrepreneurial Decision‐Making in Micro‐Entrepreneurship: A Systematic Literature Review
Jialin Song & Yipeng Sha
Abstract
Artificial intelligence (AI) has emerged as a transformative force in contemporary entrepreneurship, redefining how micro‐enterprises sense opportunities, allocate scarce resources, and navigate uncertainty. Despite the growing intersection of AI and entrepreneurship, a systematic review focusing specifically on micro‐entrepreneurial decision‐making remains conspicuously absent. This review addresses this critical gap through a multi‐dimensional analysis. First, it employs bibliometric techniques to map the field's intellectual structure, visualizing collaboration landscapes, core literature, and evolutionary trajectories. Second, it systematically synthesizes findings across seven key dimensions of the decision‐making process: opportunity assessment, entrepreneurial entry, opportunity exploitation, entrepreneurial exit, cognitive heuristics and biases, decision‐maker characteristics, and the environmental decision context. Finally, the study delineates a forward‐looking research agenda bridging theoretical insights with practical applications for AI‐enabled micro‐ventures.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.