The Impact of Supply Chain Digitalization on Competitive Advantage: An Applied Study on Maersk Company in the Kingdom of Saudi Arabia
DOI:
https://doi.org/10.59992/IJSR.2026.v5n8p19Keywords:
Supply Chain Digitalization, Competitive Advantage, Enterprise Resource Planning (ERP), Internet of Things (IoT), Logistics SectorAbstract
This study examines the impact of supply chain digitalization on competitive advantage at Maersk Company in the Kingdom of Saudi Arabia. Digitalization is operationalized through two measurable dimensions: internal functional integration supported by Enterprise Resource Planning (ERP) systems, and inter-organizational information sharing supported by Internet of Things (IoT)-enabled connectivity. The study adopted a descriptive-analytical approach and used a structured questionnaire built on a five-point Likert scale, administered to employees of the target company; 66 valid responses were obtained. The instrument recorded a Cronbach's alpha of 0.933 across its 20 items, indicating a high level of internal consistency. Descriptive results showed a very high level of both digitalization dimensions, with the ERP-supported integration dimension recording a mean of 4.38 and the IoT-supported information-sharing dimension recording a mean of 4.26. The competitive advantage constructed recorded a mean of 4.24, with indicators describing organizational capabilities and practices ranking above indicators describing end outcomes such as market share, operating cost, and entry into new markets. Analysis of response dispersion revealed a systematic pattern: variance was consistently lower on items concerning internal integration and higher on items concerning the actual mechanics of information exchange with external partners, suggesting that the willingness to cooperate is more uniform than the regularity of its execution. Simple linear regression revealed a strong positive and statistically significant relationship between the combined digitalization construct and competitive advantage, with a correlation coefficient of 0.757 and a coefficient of determination of 0.574, indicating that supply chain digitalization explains approximately 57.4% of the variance in competitive advantage, F(1,64) = 86.128, p = 0.001. The study is theoretically anchored in the Resource-Based View and the dynamic capabilities perspective, which together explain why returns on digital investment depend not on the technology itself but on the organizational routines built around it. The paper concludes with practical recommendations concerning system integration, partner-maturity segmentation, data governance, and human capability development, and candidly discusses the measurement and design limitations that bound the generalizability of its findings.
References
1. Christopher, M. (2016). Logistics and supply chain management (5th ed.). Pearson.
2. Davenport, T. H. (1998). Putting the enterprise into the enterprise system. Harvard Business Review, 76(4), 121–131.
3. Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4719–4742.
4. Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 66–77.
5. Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance — An integrative model of IT business value. MIS Quarterly, 28(2), 283–322.
6. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.
7. Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482.
8. [8] Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), 333–347.
9. Hitt, L. M., Wu, D. J., & Zhou, X. (2002). Investment in enterprise resource planning: Business impact and productivity measures. Journal of Management Information Systems, 19(1), 71–98.
10. Zhu, K., & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: Cross-country evidence from the retail industry. Information Systems Research, 16(1), 61–84.
11. Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805.
12. Verdouw, C. N., Wolfert, J., Beulens, A. J. M., & Rialland, A. (2016). Virtualization of food supply chains with the internet of things. Journal of Food Engineering, 176, 128–136.
13. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558.
14. Barratt, M., & Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: A resource-based theory perspective. Journal of Operations Management, 25(6), 1217–1233.
15. Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(2), 514–522.
16. 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.
17. Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. Free Press.
18. Fugate, B. S., Mentzer, J. T., & Stank, T. P. (2010). Logistics performance: Efficiency, effectiveness, and differentiation. Journal of Business Logistics, 31(1), 43–62.
19. Büyüközkan, G., & Göçer, F. (2018). Digital supply chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157–177.
20. Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 23–34.
21. Schniederjans, D. G., Curado, C., & Khalajhedayati, M. (2020). Supply chain digitisation trends: An integration of knowledge management. International Journal of Production Economics, 220, 107439.
22. Albalwy, H. R. (2025). Impact of modern digitization of logistics operations on supply chain performance: A case study of Almarai Company, Saudi Arabia. Journal of Economic, Administrative and Legal Sciences, 9(8), 44–60.
23. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
24. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.
25. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
26. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
27. Green, S. B. (1991). How many subjects does it take to do a regression analysis? Multivariate Behavioral Research, 26(3), 499–510.
28. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.
29. Rindfleisch, A., Malter, A. J., Ganesan, S., & Moorman, C. (2008). Cross-sectional versus longitudinal survey research: Concepts, findings, and guidelines. Journal of Marketing Research, 45(3), 261–279.
