Pursuing Impactful Entrepreneurship Research Using Artificial Intelligence

被引：56

作者：

Levesque, Moren ^{[1
]}

Obschonka, Martin ^{[2
]}

Nambisan, Satish ^{[3
]}

机构：

[1] York Univ, Schulich Sch Business, 4700 Keele St, Toronto, ON M3J 1P3, Canada

[2] Queensland Univ Technol, QUT Business Sch, Brisbane, Qld, Australia

[3] Case Western Reserve Univ, Weatherhead Sch Management, Cleveland, OH 44106 USA

来源：

ENTREPRENEURSHIP THEORY AND PRACTICE | 2022年 / 46卷 / 04期

关键词：

entrepreneurship research; theory building; theory testing; research relevance; artificial intelligence; BIG DATA; PRACTICAL RELEVANCE; GRAND CHALLENGES; MANAGEMENT; NEUROSCIENCE; REPLICATION; SIMULATION; BIOLOGY; SYSTEMS; FUTURE;

D O I：

10.1177/1042258720927369

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

It is time for the entrepreneurship field to come to terms with leading-edge artificial intelligence (AI). AI holds great promise to transform entrepreneurship into a more relevant and impactful field, but it must overcome conflicts between the AI-driven research approach and that of the traditional, theory-based research process. We explore these opportunities and challenges and suggest concrete approaches that entrepreneurship researchers can use to harness the power of AI with rigor and enhance research relevance. We conclude that incorporating the power of AI in entrepreneurship research and managing the associated risks offer a new and "grand challenge" for the field.

引用

页码：803 / 832

页数：30

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