分析欧洲中小企业采用人工智能的情况：数字能力、创新和外部环境研究

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society Pub Date : 2024-10-28 DOI:10.1016/j.techsoc.2024.102733

Marta F. Arroyabe , Carlos F.A. Arranz , Ignacio Fernandez De Arroyabe , Juan Carlos Fernandez de Arroyabe

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引用次数: 0

摘要

本研究探讨了数字能力、创新能力和商业环境支持对中小企业采用人工智能（AI）的影响。利用动态能力和资源依赖理论，我们对促进中小企业采用人工智能的驱动因素进行了全面综合的分析。我们基于欧盟 Flash Eurobarometer 数据库的调查数据，对 12108 家中小企业进行了实证研究。我们的分析结合使用了经典回归方法和先进的机器学习技术，包括人工神经网络和树状回归。我们的研究结果凸显了数字能力在推动人工智能应用方面的重要性，其中互补的创新能力表现出协同效应。与现有文献相反，商业环境支持本身的影响有限，这强调了其在完善的制度框架内的或有效力。此外，商业环境支持与数字和创新能力之间的协同作用对中小企业采用人工智能有重大影响。然而，与商业环境支持相比，内部能力对中小企业采用人工智能的影响更大。本研究通过阐明数字化能力和创新能力的相互作用，为动态能力理论做出了贡献，并对它们对人工智能应用的综合影响提供了细致入微的理解。本研究还通过强调商业环境支持的动态性质，丰富了资源依赖理论。对于实践者来说，我们的研究结果强调了对数字和创新能力进行平衡投资的必要性。政策制定者在为中小企业设计支持结构时应考虑这些见解，强调在创造有利的外部环境的同时，采取综合方法培养内部能力。

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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.

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来源期刊

Technology in Society Multiple-

CiteScore

17.90

自引率

14.10%

发文量

316

审稿时长

60 days

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.