Mon–Fri 10:00–17:00 IST
IJMEM Logo

International Journal of Modern Engineering and Management

Multidisciplinary
Open Access Journal
ISSN No: 3048-8230
Follows UGC–CARE Guidelines
Scope Indexing Publication Charges Archives Editorial Board Downloads Contact Us

Supply Chain Digitalisation, Operational Resilience and Firm Profitability: Longitudinal Evidence from Indian Manufacturing Firms

Author(s):

Deepa Srinivasan, Ravi Menon

Affiliation: Department of Operations and Supply Chain Management, Indian Institute of Technology Bombay, Mumbai, India

Page No: 54-59-

Volume issue & Publishing Year: Volume 3, Issue 6, 2026/06/12

Journal: International Journal of Modern Engineering and Management | IJMEM

ISSN NO: 3048-8230

DOI:

Download PDF Cite this article

Abstract:

The digitalisation of supply chain operations — encompassing real-time visibility platforms, IoT-enabled logistics tracking, AI-driven demand forecasting, and blockchain-based provenance verification — has been widely promoted as a route to simultaneous gains in operational resilience and cost efficiency. Yet rigorous longitudinal evidence on the magnitude, sequencing, and boundary conditions of these performance effects in emerging market manufacturing contexts remains scarce. This study examines the relationship between supply chain digitalisation investments and two distinct outcome constructs — operational resilience (the capacity to absorb, adapt to, and recover from disruptions) and firm profitability (EBITDA margin and return on assets) — across 198 Indian manufacturing firms over a five-year panel (FY2019–FY2024) spanning the COVID-19 disruption and its aftermath. Fixed-effects panel regression with instrumental variable estimation reveals that supply chain digitalisation intensity positively predicts operational resilience (β = 0.44, p < 0.001) with a one-to-two year lag, and that resilience in turn positively mediates the digitalisation–profitability relationship (indirect β = 0.28, 95% CI [0.19, 0.38]). Direct digitalisation-to-profitability effects are initially negative (Year 1: β = −0.17, p < 0.05) before turning significantly positive by Year 3 (β = 0.31, p < 0.001), reflecting implementation costs preceding performance returns. Sector moderates the digitalisation–resilience relationship: automotive and electronics firms show the largest resilience gains, while process industries (chemicals, FMCG) show attenuated effects, suggesting that supply chain architecture complexity mediates digitalisation returns. Firms that digitalise demand sensing before logistics visibility show faster profitability recovery post-disruption than those adopting the reverse sequence. These findings offer a sequenced implementation roadmap and realistic timeline expectations for Indian manufacturing executives investing in supply chain digital transformation.

Keywords:

supply chain digitalisation, operational resilience, firm profitability, panel data, fixed-effects regression, IoT, AI demand forecasting, Indian manufacturing, COVID-19, digital transformation

Reference:

  • 1.       Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance. MIS Quarterly, 24(1), 169–196.

  • 2.       Brandon-Jones, E., 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.

  • 3.       Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1–14.

  • 4.       Gu, M., Yang, L., & Huo, B. (2021). The impact of information technology usage on supply chain resilience and performance. International Journal of Production Economics, 235, 108073.

  • 5.       Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains. Transportation Research Part E, 136, 101922.

  • 6.       Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance. MIS Quarterly, 28(2), 283–322.

  • 7.       Ministry of Commerce and Industry. (2023). Production Linked Incentive Scheme: Annual progress report FY2022-23. Government of India.

  • 8.       Rogers, E. M. (1995). Diffusion of innovations (4th ed.). Free Press.

  • 9.       Sheffi, Y. (2005). The resilient enterprise: Overcoming vulnerability for competitive advantage. MIT Press.

  • 10.    Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.

  • 11.    Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology. MIS Quarterly, 27(3), 425–478.

  • 12.    Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience. International Journal of Physical Distribution & Logistics Management, 43(4), 300–320.

  • 13.    Yao, Y., & Meurier, B. (2012). Understanding the supply chain resilience. Procedia Social and Behavioral Sciences, 58, 3–10.

  • 14.    Zsidisin, G. A., & Ritchie, B. (Eds.). (2009). Supply chain risk: A handbook of assessment, management, and performance. Springer.

πŸ“š Explore Our Related Journals

Looking for the right journal for your next manuscript? Explore our international peer-reviewed journals covering multidisciplinary research, engineering, computer science, artificial intelligence and advanced engineering applications.

IJAMA

International Journal of Advanced Multidisciplinary Application

Publishes peer-reviewed research articles in Engineering, Management, Computer Science, Artificial Intelligence, Science, Humanities, Social Sciences and multidisciplinary research.

➜ Visit Journal

IJAEA

International Journal of Advanced Engineering Application

Publishes peer-reviewed research articles in Civil, Mechanical, Electrical, Electronics, Computer Science, Artificial Intelligence, Machine Learning, Data Science and Advanced Engineering Applications.

➜ Visit Journal