Examining Multi-Channel Sourcing in Strengthening Supply Chain Persistence with Moderating Role of Advanced Technology Adoption

Authors

  • Sohail Tariq sohailtariq1990@gmail.com
  • Asad Javed Department of Business and Economics. University Malaysia Terengganu
  • Shahzad Ahmed Khan Department of Management, Buraimi University, Oman
  • Fahad Al Otaibi Department of Management, Lincoln University College
  • Junaid Zafar Department of Business and Economics. University Malaysia Terengganu

DOI:

https://doi.org/10.46977/amt.2026.v06i04.001

Keywords:

Advance Technology Adoption (ATA), Dynamic Capability Theory, Multi-Channel Sourcing (MCS), Structural Equation Modelling, Supply Chain Persistence (SCP)

Abstract

Purpose: In recent years, supply chain resilience has emerged as a crucial capability for firms which are operating in uncertain and disruption-prone environments, particularly in emerging economies. Manufacturing firms are increasingly required to implement multi-channel sourcing strategies to mitigate risks and enhance supply chain persistence. This study examines the role of multi-channel sourcing in improving supply chain resilience, with advanced technology adoption serving as a moderating variable within the Pakistan context. Methods: Data was collected through a cross-sectional survey from 325 individuals, managers of manufacturing firms and operating in four sectors: automotive, electrical and electronics, process, and machinery of Pakistan. Structural equation modeling was employed to test the influence of multi-channel sourcing on supply chain persistence. Supporting Theory: Grounded in dynamic capabilities theory, this study adopts an objective, non-manipulative research approach using primary survey data from managers involved in supply chain and operations management. Results: The findings confirm that multi-channel sourcing significantly enhances supply chain resilience, and firms with higher levels of advanced technology adoption demonstrate superior capabilities in managing multiple sourcing channels during disruptions. Conclusion: The practical implications of this study are very important because it gives evidence-based information to the Pakistani academic and industrial sectors that is useful to their business practices. This research provides valuable data to bridge the current gap in understanding the relationship between multi-channel sourcing and technology adoption in the creation of long-lasting and resilient supply chains in a dynamic and complex business environment.    

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References

Adobor, H., & McMullen, R. (2007). Supplier diversity and supply chain management: A strategic approach. Business Horizons, 50(3), 219–229. https://doi.org/10.1016/j.bushor.2006.10.003

Alshebami, A. S. (2025). Purpose-driven resilience: A blueprint for sustainable growth in micro-and small enterprises in turbulent contexts. Sustainability, 17(5), 2308. https://doi.org/10.3390/su17052308

Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33–34, 111–122. https://doi.org/10.1016/j.jom.2014.11.002

Bimpikis, K., Fearing, D., & Tahbaz-Salehi, A. (2018). Multisourcing and miscoordination in supply chain networks. Operations Research, 66(4), 1023–1039. https://doi.org/10.1287/opre.2018.1728

Bode, C., & Wagner, S. M. (2015). Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions. Journal of Operations Management, 36, 215–228. https://doi.org/10.1016/j.jom.2014.12.004

Bode, C., Wagner, S. M., Petersen, K. J., & Ellram, L. M. (2011). Understanding responses to supply chain disruptions: Insights from information processing and resource dependence perspectives. Academy of Management Journal, 54(4), 833–856. https://doi.org/10.5465/amj.2011.64870145

Brandon-Jones, A., Squire, B., Autry, C. W., & Petersen, K. J. (2014). A contingent resource-based perspective of supply chain resilience and robustness. Journal of Supply Chain Management, 50(3), 55–73. https://doi.org/10.1111/jscm.12050

Büyüközkan, G., & Göçer, F. (2018). Digital supply chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157–177. https://doi.org/10.1016/j.compind.2018.02.010

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In Modern methods for business research (pp. 295-336). Psychology Press.

Choi, T. Y., & Krause, D. R. (2006). The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation. Journal of Operations Management, 24(5), 637–652. https://doi.org/10.1016/j.jom.2005.07.002

Dubey, R., Bryde, D. J., Foropon, C., Tiwari, M., Dwivedi, Y. K., & Schiffling, S. (2021). An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain. International Journal of Production Research, 59(5), 1586–1605. https://doi.org/10.1080/00207543.2020.1865583

Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism. International Journal of Production Economics, 226, 107599. https://doi.org/10.1016/j.ijpe.2019.107599

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26. https://doi.org/10.1016/j.ijpe.2019.01.004

Gupta, S., Starr, M. K., Farahani, R. Z., & Matinrad, N. (2019). Disaster management from a POM perspective: Mapping a new domain. Production and Operations Management, 28(10), 801–811. https://doi.org/10.1111/poms.12969

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Humphrey, J. (2003). Globalization and supply chain networks: The auto industry in Brazil and India. Global Networks, 3(2), 121–141. https://doi.org/10.1111/1471-0374.00056

Ivanov, D. (2021). Digital supply chain management and technology to enhance resilience by building and using end-to-end visibility during the COVID-19 pandemic. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2020.3017095

Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846. https://doi.org/10.1080/00207543.2018.1488086

Javed, A., Ibrahim, M. Y., Ngah, A. H., Zafar, M. J., Hammad, M., Khan, A. Z., & Mir, F. (2025). Impact of inclusive leadership on project success with mediating role of organizational commitment and top management support as moderator. Multidisciplinary Reviews, 8(8), 2025250. https://doi.org/10.31893/multirev.2025250

Kamble, S. S., Gunasekaran, A., & Sharma, R. (2018). Analysis of the driving and dependence power of barriers to adopt Industry 4.0 in Indian manufacturing industry. Computers in Industry, 101, 107–119. https://doi.org/10.1016/j.compind.2018.06.004

Modgil, S., Singh, R. K., & Hannibal, C. (2023). The influence of artificial intelligence techniques on disruption management: Does supply chain dynamism matter? Technology in Society, 75, 102394. https://doi.org/10.1016/j.techsoc.2023.102394

Osiyevskyy, O., Troshkova, M., & Ray, S. (2020). Multi-channel sourcing and procurement strategy: A review and research agenda. The International Journal of Logistics Management, 31(4), 671–698. https://doi.org/10.1108/IJLM-07-2019-0185

Queiroz, M. M., Telles, R., & Bonilla, S. H. (2020). Blockchain and supply chain management integration: A systematic review of the literature. Supply Chain Management: An International Journal, 25(2), 241–254. https://doi.org/10.1108/SCM-03-2018-0143

Samuels, A. (2025). Digital transformation in supply chains: improving resilience and sustainability through AI, Blockchain, and IoT. Frontiers in Sustainability, 6, 1584580. https://doi.org/10.3389/frsus.2025.1584580

Scholten, K., & Stevenson, M. (2020). Building more resilient supply chains through research on post-pandemic supply chain management. Journal of Supply Chain Management, 56(4), 3–5. https://doi.org/10.1111/jscm.12262

Sheffi, Y., & Rice, J. B. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41–48. https://sloanreview.mit.edu/article/a-supply-chain-view-of-the-resilient-enterprise/

Song, S., Shi, X., Tappia, E., Song, G., Melacini, M., & Cheng, T. C. E. (2022). Why does omni-channel allow retailers to foster supply chain resilience? Evidence from sequential mixed methods research. International Journal of Logistics Research and Applications, 27(9), 1505-1528. https://doi.org/10.1080/13675567.2022.2159350

Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of sustainable enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7

Wagner, S. M., & Bode, C. (2014). Supplier relationship-specific investments and the role of safeguards for supplier innovation sharing. Journal of Operations Management, 32(3), 65–78. https://doi.org/10.1016/j.jom.2014.01.005

Wamba, S. F., & Queiroz, M. M. (2022). Industry 4.0 and supply chain digitalization: A blockchain diffusion perspective. Production Planning & Control, 33(2–3), 193–210. https://doi.org/10.1080/09537287.2020.1810756

Wieland, A., & Durach, C. F. (2021). Two perspectives on supply chain resilience. International Journal of Logistics Management, 32(2), 784–804. https://doi.org/10.1108/IJLM-07-2019-0202

Wu, J., Wang, H., & Shang, J. (2019). Multi-sourcing and information sharing under competition and supply uncertainty. European Journal of Operational Research, 278(1), 175–186. https://doi.org/10.1016/j.ejor.2019.03.033

Published

2026-04-27

How to Cite

Tariq, S. ., Javed, A. ., Ahmed Khan, S. ., Al Otaibi, F. ., & Zafar, J. . (2026). Examining Multi-Channel Sourcing in Strengthening Supply Chain Persistence with Moderating Role of Advanced Technology Adoption. Advancement in Management and Technology (AMT) , 6(4), 01-17. https://doi.org/10.46977/amt.2026.v06i04.001

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