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Hasta la vista, baby - will machine learning terminate human literature reviews in entrepreneurship?

journal contribution
posted on 08.07.2021, 08:42 by Sebastian Robledo, Andrés Mauricio Grisales Aguirre, Mathew HughesMathew Hughes, Fabian Eggers
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.

History

School

  • Business and Economics

Department

  • Business

Published in

Journal of Small Business Management

Publisher

Taylor & Francis

Version

AM (Accepted Manuscript)

Rights holder

© 2021 International Council for Small Business

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Small Business Management on 19 Aug 2021, available online: https://doi.org/10.1080/00472778.2021.1955125

Acceptance date

07/07/2021

Publication date

2021-08-19

ISSN

0047-2778

eISSN

1540-627X

Language

en

Depositor

Prof Mat Hughes. Deposit date: 8 July 2021