Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment

This study investigates the effects of digital capabilities, innovation capabilities, and business environmental support on the adoption of Artificial Intelligence (AI) in Small and Medium-sized Enterprises (SMEs). Utilizing dynamic capabilities and resource dependency theories, we provide a comprehensive and integral analysis of the drivers that facilitate AI adoption in SMEs. We conducted an empirical study encompassing 12,108 SMEs, based on survey data of the Flash Eurobarometer database from the European Union. Our analysis employed a combination of classical regression methods and advanced machine learning techniques, including artificial neural networks and tree regression. Our findings highlight the importance of digital capabilities in driving AI adoption, where complementing innovation capabilities exhibit synergistic effects. Contrary to prevailing literature, business environmental support alone demonstrates limited impact, emphasizing its contingent effectiveness within a well-elaborated institutional framework. Furthermore, the synergy between business environmental support and digital and innovation capabilities has a significant impact on AI adoption in SMEs. However, internal capabilities exert a greater influence on AI adoption in SMEs compared to business environmental support. This study contributes to dynamic capabilities theory by elucidating the interplay of digital and innovation capabilities, offering a nuanced understanding of their combined influence on AI adoption. It also enriches resource dependency theory by highlighting the dynamic nature of business environmental support. For practitioners, our results underscore the need for a balanced investment in digital and innovation capabilities. Policymakers should consider these insights when designing support structures for SMEs, emphasizing a comprehensive approach to foster internal capabilities alongside creating an enabling external environment. • This study investigates the effects of digital and innovation capabilities, and business environmental support on SMEs AI. • Drawing from dynamic capabilities and resource dependency theory, we conducted a comprehensive analysis. • We conducted an empirical study encompassing 12,108 SMEs from European Union. • Our findings highlight the importance of digital and innovation capabilities in driving AI adoption. • Business environmental support demonstrates limited impact.

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Publication Details

Journal
Technology in Society
Published
2024-10-28
DOI
https://doi.org/10.1016/j.techsoc.2024.102733
Citations
74
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
36.29
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article

Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment

Carlos F.A. Arranz, Ignacio Fernandez De Arroyabe, Marta F. Arroyabe, Juan Carlos Fernández de Arróyabe
74 citations
Technology in Society
Impact of AI and Big Data on Business and Society
36.29
article

Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment

Carlos F.A. Arranz, Ignacio Fernandez De Arroyabe, Marta F. Arroyabe, Juan Carlos Fernández de Arróyabe
article en
74 citations

Abstract

This study investigates the effects of digital capabilities, innovation capabilities, and business environmental support on the adoption of Artificial Intelligence (AI) in Small and Medium-sized Enterprises (SMEs). Utilizing dynamic capabilities and resource dependency theories, we provide a comprehensive and integral analysis of the drivers that facilitate AI adoption in SMEs. We conducted an empirical study encompassing 12,108 SMEs, based on survey data of the Flash Eurobarometer database from the European Union. Our analysis employed a combination of classical regression methods and advanced machine learning techniques, including artificial neural networks and tree regression. Our findings highlight the importance of digital capabilities in driving AI adoption, where complementing innovation capabilities exhibit synergistic effects. Contrary to prevailing literature, business environmental support alone demonstrates limited impact, emphasizing its contingent effectiveness within a well-elaborated institutional framework. Furthermore, the synergy between business environmental support and digital and innovation capabilities has a significant impact on AI adoption in SMEs. However, internal capabilities exert a greater influence on AI adoption in SMEs compared to business environmental support. This study contributes to dynamic capabilities theory by elucidating the interplay of digital and innovation capabilities, offering a nuanced understanding of their combined influence on AI adoption. It also enriches resource dependency theory by highlighting the dynamic nature of business environmental support. For practitioners, our results underscore the need for a balanced investment in digital and innovation capabilities. Policymakers should consider these insights when designing support structures for SMEs, emphasizing a comprehensive approach to foster internal capabilities alongside creating an enabling external environment. • This study investigates the effects of digital and innovation capabilities, and business environmental support on SMEs AI. • Drawing from dynamic capabilities and resource dependency theory, we conducted a comprehensive analysis. • We conducted an empirical study encompassing 12,108 SMEs from European Union. • Our findings highlight the importance of digital and innovation capabilities in driving AI adoption. • Business environmental support demonstrates limited impact.

Technology in SocietyVol. 79
University of Essex (GB), Loughborough University (GB), Lloyds Banking Group (United Kingdom) (GB), University of Greenwich (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Impact of AI and Big Data on Business and Society
36.29
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