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Estimating the innovation benefits of first-mover and second-mover strategies when micro-businesses adopt artificial intelligence and machine learning

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  • Ully Y. Nafizah

    (The University of Warwick)

  • Stephen Roper

    (The University of Warwick)

  • Kevin Mole

    (The University of Warwick)

Abstract

Digital technologies have the potential to transform all aspects of firms’ operations. The emergence of advanced digital technologies such as Artificial Intelligence and Machine Learning raises questions about whether and when micro-businesses should adopt these technologies. In this paper we focus on how firms’ adoption decisions on Artificial Intelligence and Machine Learning influence their innovation capabilities. Using survey data for over 6,000 micro-businesses in the UK, we identify two groups of adopters based on the timing of their adoption of Artificial Intelligence and Machine Learning. ‘first movers’ – early adopters of the new technologies - and ‘second movers’- later adopters of the new technology. Probit models are used to investigate the innovation benefits of first and second mover adoption strategies. Our results suggest strong and positive impacts of adopting Artificial Intelligence and Machine Learning on micro-businesses’ innovation outcomes and innovation processes. We highlight the differential benefits of first mover and second mover strategies and highlight the role of technology characteristics as the differentiating factor. Our results emphasize both the innovation enabling role of digital technologies and the importance of an appropriate strategic approach to adopting advanced digital technologies.

Suggested Citation

  • Ully Y. Nafizah & Stephen Roper & Kevin Mole, 2024. "Estimating the innovation benefits of first-mover and second-mover strategies when micro-businesses adopt artificial intelligence and machine learning," Small Business Economics, Springer, vol. 62(1), pages 411-434, January.
    • Handle: RePEc:kap:sbusec:v:62:y:2024:i:1:d:10.1007_s11187-023-00779-x
    DOI: 10.1007/s11187-023-00779-x
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    Cited by:

    1. Raluca-Florentina Cretu & Daniela Tutui & Viorel-Costin Banta & Elena Claudia Serban & Laura - Eugenia - Lavinia Barna & Romeo-Catalin Cretu, 2024. "Effects of Artificial Intelligence-Based Technologies Implementation s on the Skills Needed in the Automotive Industry A Bibliometric Analysis," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 801-801, August.

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    More about this item

    Keywords

    Advanced digital technology; Artificial Intelligence; Digital adoption; Innovation; Machine Learning; Micro-Business; Timing Adoption;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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