“Hasta la vista, baby” – will machine learning terminate human literature reviews in entrepreneurship?
探讨人工智能和机器学习能否用于研究学术文献，通过对比机器学习工具与人工文献综述，发现机器学习可增强人类研究结论的可复制性和稳健性，为创业学学者提供将机器学习融入学术研究的指南。
Can, and should, artificial intelligence (AI) and its machine learning (ML) variant be applied to study scholarly literature? With AI and ML rapidly disrupting industries, we investigate how scholars in entrepreneurship and small business management can capitalize on AI and ML to support their scholarship and comprehensively review, catalog, and analyze the literature. We examine various ML tools and deploy these tools against a published literature review to consider whether ML complements or substitutes scholars’ agency. We show that ML can reinforce human findings to support replicability and robustness, adding additional layers of transparency and validity to conclusions from human-derived systematic reviews. Our contributions provide scholars with valuable guidance and a blueprint for adopting ML into their scholarship and not replacing their scholarship.