AI-Enabled Digital Technologies in Supply Chain Management for Competitive Advantage and Business Performance: A PLS-SEM Approach
DOI:
https://doi.org/10.47067/ramss.v8i4.575Keywords:
AI-based supply chain management system (AISCM), business performance (BP), Unique Competitive Advantage (UCA), Supply Chain Performance (SCP), SmartPLS-SEMAbstract
The present study has examined the use of an AI-based supply chain management system (AISCM) and its positive impact on international business performance (BP). Herein, a sequential mediation analysis has been performed using SmartPLS-SEM 4.0, with the constructs of Unique Competitive Advantage (UCA) and Supply Chain Performance serving as mediating variables in the study framework. The research has been conducted on a population sample of operations managers and supervisors working in international firms in Pakistan who oversee supply chain operations or strategic planning of international business. A non-probability, purposive sampling technique was employed to recruit study respondents, and a sample size of 205 was selected for statistical analysis using SmartPLS. The study's outcomes are significant for both theory and practice. The study has extended resource-based theory by employing AISCM in the study framework. Asia-based global firms can gain substantially from the findings of this study. For future research endeavors, it is recommended that moderating variables be identified among the relationships between study variables. The research framework may also be checked in GCC countries for a regional perspective and generalizability.
References
Abyaneh, A.G. et al. (2025) ‘An analytical review of artificial intelligence applications in sustainable supply chains’, Supply Chain Analytics, 12(April). Available at: https://doi.org/10.1016/j.sca.2025.100173.
Agship, F.L. and Paper, W. (2025) ‘Transformation of Industries in the Age of AI AI in Action?: Beyond Experimentation to Transform Industry’, (January).
AL-Shboul, M.A. (2024) ‘Artificial intelligence drivers’ effect on willingness to adopt the human capital supply chain in manufacturing firms: an empirical investigation from developing countries – a mediation model’, Industrial Management and Data Systems, 124(10), pp. 2919–2938. Available at: https://doi.org/10.1108/IMDS-12-2023-0977.
Aljoghaiman, A. and Mirzaliev, S. (2024) ‘Adoption of artificial intelligence and digital supply chain for enhancing supply chain performance?: mediating role of green supply’, 7(3), pp. 1–24.
Anwer AL-Shboul, M. (2023) ‘Enabling manufacturing firms’ supply chain performance in the Middle East region through boosting the quality of multi-directional relationship, and supply chain risk dilution: A moderated-mediation model’, Heliyon, 9(11), p. e22059. Available at: https://doi.org/10.1016/j.heliyon.2023.e22059.
Belhadi, A. et al. (2021) ‘Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation’, Annals of Operations Research [Preprint]. Available at: https://doi.org/10.1007/s10479-021-03956-x.
Che Hassan, M.H. and Kamarudin, N.N. (2025) ‘The Impact of Integration Artificial Intelligence into Supply Chain Management: A Scoping Review’, International Journal of Academic Research in Business and Social Sciences, 15(3), pp. 503–526. Available at: https://doi.org/10.6007/ijarbss/v15-i3/24870.
Cimino, A. et al. (2025) ‘Artificial Intelligence Adoption for Sustainable Growth in SMEs: An Extended Dynamic Capability Framework’, Corporate Social Responsibility and Environmental Management, 32(5), pp. 6120–6138. Available at: https://doi.org/10.1002/csr.70019.
Culot, G., Podrecca, M. and Nassimbeni, G. (2024) ‘Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions’, Computers in Industry. Elsevier B.V., p. 104132. Available at: https://doi.org/10.1016/j.compind.2024.104132.
Damtew, A.W. and Goshu, Y.Y. (2024) ‘The impacts of AWS from digital visions to action for supply chain resilience, performances, and inclusiveness’, International Journal of Advanced Manufacturing Technology, 130(9–10), pp. 4821–4834. Available at: https://doi.org/10.1007/s00170-023-12919-4.
Dash, G. and Paul, J. (2021) ‘CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting’, Technological Forecasting and Social Change, 173, p. 121092. Available at: https://doi.org/10.1016/j.techfore.2021.121092.
Duarte Alonso, A. et al. (2025) ‘Unleashing the process of Industry 4.0 adoption: a resource-based view and new stakeholder theory approach’, Business Process Management Journal [Preprint]. Available at: https://doi.org/10.1108/BPMJ-09-2024-0856.
Etikan, I. (2016) ‘Comparison of Convenience Sampling and Purposive Sampling’, American Journal of Theoretical and Applied Statistics, 5(1), p. 1. Available at: https://doi.org/10.11648/j.ajtas.20160501.11.
Grover, V. et al. (2024) ‘Blockchain, IoT, and AI Technologies for Supply Chain Management: Apply Emerging Technologies to Address and Improve Supply Chain Management’, Blockchain, IoT, and AI Technologies for Supply Chain Management: Apply Emerging Technologies to Address and Improve Supply Chain Management, pp. 1–544. Available at: https://doi.org/10.1007/979-8-8688-0315-4.
Guo, X. et al. (2025) ‘Research on supply chain resilience mechanism of AI-Enabled manufacturing enterprises -based on organizational change perspective’, Scientific Reports, 15(1), pp. 1–18. Available at: https://doi.org/10.1038/s41598-025-17138-3.
Hair, J.F. et al. (2019) ‘When to use and how to report the results of PLS-SEM’, European Business Review, 31(1), pp. 2–24. Available at: https://doi.org/10.1108/EBR-11-2018-0203.
Hassan, N.M. et al. (2023) ‘Interconnection between the role of blockchain technologies, supply chain integration, and circular economy: A case of small and medium-sized enterprises in Pakistan’, Science Progress, 106(3), pp. 1–22. Available at: https://doi.org/10.1177/00368504231186527.
Hossain, M.S. et al. (2025) ‘Ai-Driven Aggregate Planning for Sustainable Supply Chains: a Systematic Literature Review of Models, Applications, and Industry Impacts’, American Journal of Advanced Technology and Engineering Solutions, 1(1), pp. 382–437. Available at: https://doi.org/10.63125/3jdpkd14.
Jabbar, A., Sheikh, A.A. and Raza, S.H. (2023) ‘Examining the Role of Masstige Value Between Celebrity Endorsement and Consumer Engagement of Fashion Brands: An Empirical Study’, International Journal of Business and Economic Affairs, 8(3), pp. 103–111. Available at: https://doi.org/10.24088/ijbea-2023-83008.
Khan, F.A., Sheikh, D.A.A. and Zainab, F. (2024) ‘The Impact of SMEs Capability for Service Innovation and Its Tactical Green Marketing on Sustainable Business Performance’, Journal of Small Business Strategy, 34(2), p. 2024. Available at: https://doi.org/10.53703/001c.117659.
Khan, S.A.R. et al. (2023) ‘Green technology adoption paving the way toward sustainable performance in circular economy: a case of Pakistani small and medium enterprises’, International Journal of Innovation Science [Preprint]. Available at: https://doi.org/10.1108/IJIS-10-2022-0199.
Khan, S.A.R. et al. (2024) ‘Modeling the Intricate Association between Sustainable Service Quality and Supply Chain Performance: Moderating Role of Blockchain Technology and Environmental Uncertainty’, Sustainability (Switzerland) , 16(11). Available at: https://doi.org/10.3390/su16114808.
Khan, S.A.R. et al. (2025) ‘The Implications of Artificial Intelligence for Small and Medium-Sized Enterprises’ Sustainable Development in the Areas of Blockchain Technology, Supply Chain Resilience, and Closed-Loop Supply Chains’, Sustainability (Switzerland), 17(1), pp. 1–22. Available at: https://doi.org/10.3390/su17010334.
Khan, S.A.R., Sheikh, A.A. and Tahir, M.S. (2024a) ‘Corporate social responsibility-an antidote for sustainable business performance: interconnecting role of digital technologies, employee eco-behavior, and tax avoidance’, Environmental science and pollution research international, 31(3), pp. 4365–4383. Available at: https://doi.org/10.1007/S11356-023-31377-9.
Khan, S.A.R., Sheikh, A.A. and Tahir, M.S. (2024b) ‘Corporate social responsibility-an antidote for sustainable business performance: interconnecting role of digital technologies, employee eco-behavior, and tax avoidance’, Environmental science and pollution research international, 31(3), pp. 4365–4383. Available at: https://doi.org/10.1007/s11356-023-31377-9.
Khan, S.A.R., Tahir, M.S. and Sheikh, A.A. (2024) ‘Sustainable performance in SMEs using big data analytics for closed-loop supply chains and reverse omnichannel’, Heliyon, 10(16). Available at: https://doi.org/10.1016/j.heliyon.2024.e36237.
Khedr, A.M. and S, S.R. (2024) ‘Enhancing supply chain management with deep learning and machine learning techniques: A review’, Journal of Open Innovation: Technology, Market, and Complexity, 10(4), p. 100379. Available at: https://doi.org/10.1016/j.joitmc.2024.100379.
Kurrahman, T. et al. (2025) ‘Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view’, International Journal of Logistics Research and Applications [Preprint]. Available at: https://doi.org/10.1080/13675567.2025.2479006.
Lamees, A.Z. and Ramayah, T. (2025) ‘How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective’, Supply Chain Management, 30(2), pp. 233–249. Available at: https://doi.org/10.1108/SCM-09-2024-0558.
Larabi, C. (2025) ‘The role of resource orientation, technology innovation, and strategic flexibility in driving firm performance’, Management and Sustainability [Preprint]. Available at: https://doi.org/10.1108/MSAR-08-2024-0083.
Lima, B. et al. (2025) ‘Timing and interdependencies in blockchain capabilities development for supply chain management: a resource-based view perspective’, Industrial Management and Data Systems, 125(5), pp. 1645–1685. Available at: https://doi.org/10.1108/IMDS-09-2024-0859.
Mailani, D. et al. (2024) ‘Resource-Based View Theory to Achieve a Sustainable Competitive Advantage of the Firm?: Systematic Literature Review’, 4(1), pp. 1–15.
Mikalef, P. et al. (2023) ‘Artificial intelligence ( AI ) competencies for organizational performance?: A B2B marketing capabilities perspective’, 164(April).
Mvududu, N.H. and Sink, C.A. (2013) ‘Factor Analysis in Counseling Research and Practice’, Counseling Outcome Research and Evaluation, 4(2), pp. 75–98. Available at: https://doi.org/10.1177/2150137813494766.
Petropoulos, F. et al. (2025) ‘Operations & Supply Chain Management: Principles and Practice’, International Journal of Production Research [Preprint]. Available at: https://doi.org/10.1080/00207543.2025.2555531.
Rashid, A. Bin and Kausik, M.A.K. (2024) ‘AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications’, Hybrid Advances, 7(August), p. 100277. Available at: https://doi.org/10.1016/j.hybadv.2024.100277.
Rehman Khan, S.A. et al. (2022) ‘Digital transformation, smart technologies, and eco-innovation are paving the way toward sustainable supply chain performance’, Science Progress, 105(4), pp. 1–26. Available at: https://doi.org/10.1177/00368504221145648.
Sai Dhruv, G.P. et al. (2023) ‘Enhancing Track And Trace: A Blockchain Use-Case In Supply Chain Management Systems’, in 7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. Available at: https://doi.org/10.1109/CSITSS60515.2023.10334090.
Shaiful Fitri Abdul Rahman, N. et al. (2022) ‘The adoption of industry 4.0 practices by the logistics industry: A systematic review of the gulf region’, Cleaner Logistics and Supply Chain, 5(August), p. 100085. Available at: https://doi.org/10.1016/j.clscn.2022.100085.
Sheikh, A.A. et al. (2024) ‘Impact of green human resource management practices on hotels environmental performance: A mediation and moderation analysis’, Sustainable Futures, 8, p. 100409. Available at: https://doi.org/10.1016/j.sftr.2024.100409.
Sheikh, A.A., Shahzad, A. and Ku Ishaq, A. (2017) ‘The Growth of E-Marketing in Business-to-Business Industry and its effect on the Performance of Businesses in Pakistan: Marketing Success’, International and Multidisciplinary Journal of Social Sciences, 6(2), p. 178. Available at: https://doi.org/10.17583/rimcis.2017.2704.
Shirkoohi, S.M. (2025) ‘Creating Value in Metaverse-Driven Global Value Chains?: Blockchain Integration and the Evolution of International Business’, pp. 1–23.
Srivastava, A. et al. (2025) ‘Sustaining supply chain with automation and robotics’, in Transformation of Supply Chain Ecosystems: Technological Innovations and Collaborations. Emerald Publishing, pp. 173–188. Available at: https://doi.org/10.1108/978-1-83549-246-820251011.
Sruthy, S.K. (2024) ‘Enhancing Supply Chain Resilience through Artificial Intelligence: A Strategic Framework for Executives’, Emerging Science Journal, 8(4), pp. 1462–1473. Available at: https://doi.org/10.28991/ESJ-2024-08-04-013.
Teece, D.J. (2025) ‘The multinational enterprise, capabilities, and digitalization: governance and growth with world disorder’, Journal of International Business Studies [Preprint]. Available at: https://doi.org/10.1057/s41267-024-00767-7.
WEF (2025) AI will protect global supply chains from the next major shock | World Economic Forum.
Wu, H., Liu, J. and Liang, B. (2024) ‘AI-Driven Supply Chain Transformation in Industry 5.0: Enhancing Resilience and Sustainability’, Journal of the Knowledge Economy, 16(1), pp. 3826–3868. Available at: https://doi.org/10.1007/s13132-024-01999-6.
Yadav, S. et al. (2024) ‘Exploring the relationship between digitalization, resilient agri-food supply chain management practices and firm performance’, Journal of Enterprise Information Management, 37(2), pp. 511–543. Available at: https://doi.org/10.1108/JEIM-03-2022-0095.
Yin, F. et al. (2025) ‘The impact of AI applications, information sharing, and supply chain resilience on agricultural supply chain performance’, Journal of Data, Information and Management [Preprint]. Available at: https://doi.org/10.1007/s42488-025-00155-2.
Zaid, M., Farooqi, R. and Azmi, S.N. (2025) ‘Driving sustainable supply chain performance through digital transformation: the role of information exchange and responsiveness’, Cogent Business and Management, 12(1), p. Available at: https://doi.org/10.1080/23311975.2024.2443047.
Zhang, C., Li, S. and Liu, X. (2025) ‘Data-driven supply chain orientation and supply chain performance: empirical investigation using a contingent resource-based view perspective’, European Journal of Innovation Management [Preprint]. Available at: https://doi.org/10.1108/EJIM-01-2024-0017.
Zhang, Y., Hassan, N.M. and Sheikh, A.A. (2024a) ‘Unboxing the dilemma associated with online shopping and purchase behavior for remanufactured products: A smart strategy for waste management’, Journal of Environmental Management, 351. Available at: https://doi.org/10.1016/j.jenvman.2023.119790.
Zhang, Y., Hassan, N.M. and Sheikh, A.A. (2024b) ‘Unboxing the dilemma associated with online shopping and purchase behavior for remanufactured products: A smart strategy for waste management’, Journal of Environmental Management, 351(June 2023), p. 119790. Available at: https://doi.org/10.1016/j.jenvman.2023.119790.
