Artificial Intelligence Adoption by SMEs to Achieve Sustainable Business Performance: Application of Technology–Organization–Environment Framework
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The primary purpose of this study was to investigate and present a theoretical model that identifies the most influential factors affecting the adoption of artificial intelligence (AI) by SMEs to achieve sustainable business performance in Saudi Arabia by integrating the Technology–Organization–Environment (TOE) framework. The authors utilized a quantitative method, using a survey instrument for this research. Data for this research were collected from managers working in six different sectors. Subsequently, based on company size, firms were divided into two groups, allowing multi-group analysis of small and medium-sized businesses to explore group differences. Hence, firm size played a moderating role in the conceptualized model. Data analysis was performed on SmartPLS 3, and the results suggest that dimensions of the TOE framework, such as relative advantage, compatibility, sustainable human capital, market and customer demand, and government support, play a significant role in the adoption of AI. Moreover, this study found a significant influence of AI on SMEs’ operational and economic performance. The multi-group analysis (MGA) results reveal significant group differences, with a medium-sized firm strengthening the relationship between relative advantage and AI adoption compared to small-size firms. The findings lead to practical implications for companies on how to increase the adoption of AI to help SMEs embrace their technological challenges in KSA and obtain sustainable business performance to contribute to the economy.
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Integrating RBV, DC, and TOE frameworks provides a comprehensive understanding of AI adoption and value creation potential in SMEs across developing economies.
“The adoption and value creation potential of AI in SMEs across developing economies can be comprehensively understood by integrating three complementary theoretical frameworks: the RBV, DC, and TOE (Almashawreh et al., 2024; Badghish & Soomro, 2024; Shahadat et al., 2023).”
From Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies (2026) · cites this paper as Badghish & Soomro, 2024
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- Authors
- Badghish, S., & Soomro, Y. A.
- Affiliations
- King Abdulaziz University (SA)
- Corresponding author
- Soomro, Yasir Ali
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2024-02-24
- Volume
- 16
- Issue
- 5
- Pages
- 1864
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4392164072
- Cited by
- 261
- References
- 130
- Citations by year
- 2026: 140 · 2025: 92 · 2024: 29
- FWCI
- 97.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Ministry of Education and Deanship of Scientific Research (DSR), King Abdulaziz University (IFPDP-242-22)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Keywords
- artificial intelligence adoption, small and medium-sized enterprises, sustainable business performance, technology-organization-environment framework, relative advantage, compatibility, government support, firm size, moderating effect of firm size, Saudi Arabia
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