Marta F. Arroyabe , Carlos F.A. Arranz , Ignacio Fernandez De Arroyabe , Juan Carlos Fernandez de Arroyabe
{"title":"Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment","authors":"Marta F. Arroyabe , Carlos F.A. Arranz , Ignacio Fernandez De Arroyabe , Juan Carlos Fernandez de Arroyabe","doi":"10.1016/j.techsoc.2024.102733","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102733"},"PeriodicalIF":10.1000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Society","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160791X24002811","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL ISSUES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Technology in Society is a global journal dedicated to fostering discourse at the crossroads of technological change and the social, economic, business, and philosophical transformation of our world. The journal aims to provide scholarly contributions that empower decision-makers to thoughtfully and intentionally navigate the decisions shaping this dynamic landscape. A common thread across these fields is the role of technology in society, influencing economic, political, and cultural dynamics. Scholarly work in Technology in Society delves into the social forces shaping technological decisions and the societal choices regarding technology use. This encompasses scholarly and theoretical approaches (history and philosophy of science and technology, technology forecasting, economic growth, and policy, ethics), applied approaches (business innovation, technology management, legal and engineering), and developmental perspectives (technology transfer, technology assessment, and economic development). Detailed information about the journal's aims and scope on specific topics can be found in Technology in Society Briefings, accessible via our Special Issues and Article Collections.