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Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic

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  • Nick Drydakis

    (Anglia Ruskin University
    Pembroke College, University of Cambridge
    University of Cambridge
    Global Labor Organization)

Abstract

The study utilises the International Labor Organization’s SMEs COVID-19 pandemic business risks scale to determine whether Artificial Intelligence (AI) applications are associated with reduced business risks for SMEs. A new 10-item scale was developed to capture the use of AI applications in core services such as marketing and sales, pricing and cash flow. Data were collected from 317 SMEs between April and June 2020, with follow-up data gathered between October and December 2020 in London, England. AI applications to target consumers online, offer cash flow forecasting and facilitate HR activities are associated with reduced business risks caused by the COVID-19 pandemic for both small and medium enterprises. The study indicates that AI enables SMEs to boost their dynamic capabilities by leveraging technology to meet new types of demand, move at speed to pivot business operations, boost efficiency and thus, reduce their business risks.

Suggested Citation

  • Nick Drydakis, 2022. "Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 24(4), pages 1223-1247, August.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:4:d:10.1007_s10796-022-10249-6
    DOI: 10.1007/s10796-022-10249-6
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    Cited by:

    1. Meub, Lukas & Proeger, Till, 2022. "Künstliche Intelligenz in Handwerk und Mittelstand: Ein Forschungsüberblick," ifh Forschungsberichte 1, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    2. Nick Drydakis, 2022. "Improving Entrepreneurs’ Digital Skills and Firms’ Digital Competencies through Business Apps Training: A Study of Small Firms," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    3. Xin Zhang & Felix Nutakor & Michael Kaku Minlah & Jinke Li, 2023. "Can Digital Transformation Drive Green Transformation in Manufacturing Companies?—Based on Socio-Technical Systems Theory Perspective," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    4. Nisreen Ameen & Jyoti Choudrie & Paul Jones & Amitabh Anand, 2022. "Innovative Technologies and Small-Medium Sized Enterprises in Times of Crisis," Information Systems Frontiers, Springer, vol. 24(4), pages 1055-1060, August.
    5. Ana NASTASE & Lauren?iu COROBAN & Nicolae VRANA, 2023. "Challenges for Change Management in SMEs," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 24(5), pages 826-832, December.

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    More about this item

    Keywords

    SMEs; Business Risks; COVID-19 pandemic; Artificial Intelligence; Dynamic Capabilities;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship

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