A pathway to bypassing market entry barriers from data network effects: A case study of a start-up’s use of machine learning

Darek M. Haftor, Ricardo Costa-Climent and Samuel Ribeiro Navarrete

Journal of Business Research, 2023, vol. 168, issue C

Abstract: Highly valued firms exploit machine learning to activate data network effects. Data is gathered and analyzed to generate predictions and recommendations. This loop locks in existing service users and locks out potential competitors, thus creating a sizeable entry barrier, particularly for small and medium-sized (SME) enterprises. The literature does not describe the possible pathways to enter markets protected by incumbents’ data network effects. This study examines an SME that successfully entered such a market. A key finding is that, for successful market entry, an SME can focus on different stakeholders from those that are targeted by incumbents, provided such stakeholders can legitimize the SME’s use of user data generated by incumbents.

Keywords: Artificial intelligence; Machine learning; Market entry; Legitimacy; SMEs; Stakeholders (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:168:y:2023:i:c:s0148296323006033

DOI: 10.1016/j.jbusres.2023.114244

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