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

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

arXiv 11 Dec 2025 · Econometrics

arXiv:2512.10333 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

34
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Al Koliby, I. S. and Al-Swidi, A. K. and Al-Hakimi, M. A. and Farhan… (2025) How green knowledge-oriented leadership drives green innovation in SMEs: the mediating role of environmental strategy and the mo…0.84333100%
2Cannas, V. G. and Ciano, M. P. and Saltalamacchia, M. and Secchi, R (2024) Artificial intelligence in supply chain and operations management: a multiple case study research0.51121100%
3De Giovanni, P (2021) Smart Supply Chains with vendor managed inventory, coordination, and environmental performance0.51121100%
4Fosso-Wamba, S. and Guthrie, C. and Queiroz, M. M. and Oyedijo, A (2024) Building AI-enabled capabilities for improved environmental and manufacturing performance: evidence from the US and the UK0.51121100%
5Pandey, B. and Khurana, M. K (2024) An integrated Pythagorean fuzzy SWARA-COPRAS framework to prioritise the solutions for mitigating Industry 4.0 risks0.51121100%
6Abou-Foul, M. and Ruiz-Alba, J. L. and López-Tenorio, P. J (2023) The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabi…0.40511100%
7Agrawal, R. and Majumdar, A. and Kumar, A. and Luthra, S (2023) Integration of artificial intelligence in sustainable manufacturing: current status and future opportunities0.40511100%
8Akram, R. and Li, Q. and Srivastava, M. and Zheng, Y. and Irfan, M (2024) Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an e…0.40511100%
9Bonab, A. B. and Fedele, M. and Formisano, V. and Rudko, I (2023) In complexity we trust: A systematic literature review of urban quantum technologies0.40511100%
10Centobelli, P. and Cerchione, R. and Singh, R (2019) The impact of leanness and innovativeness on environmental and financial performance: Insights from Indian SMEs0.40511100%

Showing the top 10 of 34 scored citations.