The Impact of Digital Transformation on Supply Chain Resilience in Manufacturing: An Empirical Analysis of A-Share Listed Manufacturing Enterprises in China_Vol. 2 No. 6 (JBM 2025)_Journal of Business and Marketing (ISSN: 3005-5717)

Home > Journal of Business and Marketing (ISSN: 3005-5717) > Vol. 2 No. 6 (JBM 2025) >

The Impact of Digital Transformation on Supply Chain Resilience in Manufacturing: An Empirical Analysis of A-Share Listed Manufacturing Enterprises in China

Download PDF

DOI: https://doi.org/10.62517/jbm.202509606

Author(s)

Zhipeng Cui

Affiliation(s)

Jiangxi University of Finance and Economics, Discipline: Finance, Nanchang, Jiangxi, China

Abstract

Against a backdrop of heightened global uncertainty, supply chain resilience has emerged as a core competitive advantage for the survival and development of manufacturing enterprises. This study employs a two-way fixed effects model based on panel data from Chinese A-share listed manufacturing firms (19,751 observations) spanning 2011–2023 to empirically examine the impact of digital transformation on manufacturing supply chain resilience and its underlying mechanisms. The supply chain resilience index was constructed using the entropy method; The level of digital transformation was measured using the Guotai An (CSMAR) Digital Transformation Index. The findings reveal that digital transformation exerts a significant positive effect on supply chain resilience (baseline regression coefficient:0.0158, p<0.01), realized through two key pathways: alleviating corporate financing constraints (coefficient:-0.0051, p<0.05) and enhancing innovation capacity (measured by patent applications, coefficient:0.2934, p<0.01). This conclusion remains robust after a series of stability tests, including endogeneity treatment (lagged variable method), sample screening, and explanatory variable substitution. Heterogeneity analysis indicates that this enhancement effect is particularly pronounced in non-state-owned enterprises, large enterprises (coefficient: 0.0186, p<0.01; coefficient for SMEs: 0.0107, p<0.01) and enterprises in western regions (coefficient: 0.0238, p<0.01). This study provides empirical evidence and practical insights for Chinese manufacturing enterprises to enhance supply chain resilience and achieve high-quality development by leveraging the digital transformation wave.

Keywords

Digital Transformation; Supply Chain Resilience; Financing Constraints; Innovation Capacity; Manufacturing

References

[1] Belhadi, A., et al. (2021). Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries. Technological Forecasting and Social Change, 163, 120447. [2] Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118-144. [3] Wu, F., Hu, H., Lin, H., & Ren, X. (2021). Corporate digital transformation and capital market performance: Empirical evidence based on stock liquidity. Management World, 37(7), 130-144. [4] Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1-14. [5] 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. [6] Kamalahmadi, M., & Mellat-Parast, M. (2016). Developing a resilient supply chain through supply chain agility and risk sharing. International Journal of Logistics Research and Applications, 19(6), 467–487. [7] Scholten, K., Sharkey Scott, P., & Fynes, B. (2019). Building routines for non-routine events: supply chain resilience learning mechanisms and their antecedents. Supply Chain Management: An International Journal, 24(3), 430-442. [8] Liu, W., et al. (2023). Digital transformation and supply chain resilience: Is contingency planning a missing link? International Journal of Production Economics, 255, 108657. [9] Galbraith, J. R. (1974). Organisation design: An information processing view. Interfaces, 4(3), 28–36. [10] Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93-102. [11] Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). A revised FMEA application for the SARS-CoV-2 outbreak in the supply chain. International Journal of Production Research, 57(15-16), 4935-4955. [12] Li, J., et al. (2020). Digital transformation and supply chain collaboration: A framework for resilience. Journal of Business Research, 132, 543-556. [13] Hadlock, C. J., & Pierce, J. R. (2010). New evidence on measuring financial constraints: Moving beyond the KZ index. Review of Financial Studies, 23(5), 1909-1940. [14] Du, J., et al. (2021). Digital transformation and corporate financial reporting: Evidence from China. Journal of Accounting and Public Policy, 40(5), 106878. [15] Song, H., et al. (2019). Blockchain-enabled supply chain finance: A conceptual framework and research agenda. International Journal of Production Economics, 215, 1-12. [16] Tao, F., et al. (2018). Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 15(4), 2405-2415. [17] Bharadwaj, A., et al. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471-482. [18] Hogan, S. J., & Coote, L. V. (2014). Organisational culture, innovation, and performance: A test of Schein's model. Journal of Business Research, 67(8), 1609-1621.