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AI-Enhanced TOE Framework for Sustainable Industrial Performance in Fragile and Transforming Economies: Evidence from Yemen and Saudi Arabia

Author

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  • Shaima Farhana
  • Dong Yua
  • Amirhossein Karamoozianc
  • Ali Al-shawafid
  • Amar N. Alsheavif

Abstract

Using an integrated framework rooted in the TOE model enhanced with AI, this study looks at ways to improve industrial performance and environmental sustainability in fragile and rapidly transforming contexts such as those found in Yemen and Saudi Arabia. Data for the research are field-based and were obtained from a total of 600 SMEs operating in both countries. Based on the questionnaires' responses by 294 managers, results from the partial least squares structural equation modeling (PLS-SEM) have indicated significant positive effects of AI-TOE on environmental performance (beta = 0.487) and manufacturing performance (beta = 0.759). Results indicate that AI acts as a transformative force, though its impact differs based on the maturity of infrastructure and organizational readiness. The Saudi SMEs gain from their institutional support and advanced technologies, while those in Yemen are dependent on the low-cost adoption of AI and organizational flexibility to accept structural challenges. PLS-SEM analysis of the study showed that integrating AI into the TOE dimensions accelerates operational efficiency in order to support environmental performance. Industrial performance was found to be a very important mediator in this relationship. This study responds to the call for digital transformation literature by providing an actionable framework of AI adoption in resource-constrained environments. These findings offer insights that might guide policymakers and organizations toward more resilient and sustainable operational strategies. These findings provide valuable guidance for engineering managers within the context of negotiating digital transformation and sustainability trade-offs in fragile and resource-constrained contexts.

Suggested Citation

  • Shaima Farhana & Dong Yua & Amirhossein Karamoozianc & Ali Al-shawafid & Amar N. Alsheavif, 2025. "AI-Enhanced TOE Framework for Sustainable Industrial Performance in Fragile and Transforming Economies: Evidence from Yemen and Saudi Arabia," Papers 2512.10333, arXiv.org.
  • Handle: RePEc:arx:papers:2512.10333
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    References listed on IDEAS

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    1. Abou-Foul, Mohamad & Ruiz-Alba, Jose L. & López-Tenorio, Pablo J., 2023. "The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 157(C).
    2. Nouira, Imen & Hammami, Ramzi & Fernandez Arias, Alina & Gondran, Natacha & Frein, Yannick, 2022. "Olive oil supply chain design with organic and conventional market segments and consumers’ preference to local products," International Journal of Production Economics, Elsevier, vol. 247(C).
    3. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.
    4. Rohit Agrawal & Abhijit Majumdar & Anil Kumar & Sunil Luthra, 2023. "Integration of artificial intelligence in sustainable manufacturing: current status and future opportunities," Operations Management Research, Springer, vol. 16(4), pages 1720-1741, December.
    5. Akram, Rabia & Li, Qiyuan & Srivastava, Mohit & Zheng, Yulu & Irfan, Muhammad, 2024. "Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    6. Violetta Giada Cannas & Maria Pia Ciano & Mattia Saltalamacchia & Raffaele Secchi, 2024. "Artificial intelligence in supply chain and operations management: a multiple case study research," International Journal of Production Research, Taylor & Francis Journals, vol. 62(9), pages 3333-3360, May.
    7. Liu, Xiaoqian & Cifuentes-Faura, Javier & Zhao, Shikuan & Wang, Long, 2023. "Government environmental attention and carbon emissions governance: Firm-level evidence from China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 121-142.
    8. Muhammad, Syed Sardar & Dey, Bidit Lal & Kamal, Muhammad Mustafa & Samuel, Lalnunpuia & Alzeiby, Ebtesam Abdullah, 2025. "Digital transformation or digital divide? Smes' use of AI during global crisis," Technological Forecasting and Social Change, Elsevier, vol. 217(C).
    9. Rohit Sharma & Anjali Shishodia & Angappa Gunasekaran & Hokey Min & Ziaul Haque Munim, 2022. "The role of artificial intelligence in supply chain management: mapping the territory," International Journal of Production Research, Taylor & Francis Journals, vol. 60(24), pages 7527-7550, December.
    10. Shashi, & Centobelli, Piera & Cerchione, Roberto & Singh, Rajwinder, 2019. "The impact of leanness and innovativeness on environmental and financial performance: Insights from Indian SMEs," International Journal of Production Economics, Elsevier, vol. 212(C), pages 111-124.
    11. Rabia Akram & Qiyuan Li & Mohit Srivastava & Yulu Zheng & Muhammad Irfan, 2024. "Nexus between Green Technology Innovation and Climate Policy Uncertainty: Unleashing the Role of Artificial Intelligence in an Emerging Economy," Post-Print hal-04846845, HAL.
    12. Yang, Haochang & Li, Lianshui & Liu, Yaobin, 2022. "The effect of manufacturing intelligence on green innovation performance in China," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    13. Chapman, Alexis & Dilmperi, Athina, 2022. "Luxury brand value co-creation with online brand communities in the service encounter," Journal of Business Research, Elsevier, vol. 144(C), pages 902-921.
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