AMPLIFYING THE DIGITAL SUPPLY CHAIN MODEL: THE MODERATING ROLE OF BIG DATA ANALYTICS CAPABILITY ON PERCEPTIONS OF PERSONNEL IN THE MANUFACTURING INDUSTRY

Authors

  • Yuanyuan Xing Faculty of Management Sciences, Dhonburi Rajabhat University
  • Tachakorn Wongkumchai Faculty of Management Sciences, Dhonburi Rajabhat University

DOI:

https://doi.org/10.18623/rvd.v23.n3.4369

Keywords:

Big Data Analytics Capability (BDAC), Perception-Based Analysis, Digital Supply Chain Model, Dynamic Capabilities Theory, Chinese Manufacturing Industry

Abstract

This study investigates how Big Data Analytics Capability (BDAC) shapes the interplay among Corporate Digital Transformation (CDT), Supply Chain Digital Transformation (SCDT), Customer Data Engagement (CDE), and Corporate Performance (CP) in Chinese manufacturing firms. Grounded in the Resource-Based View and Dynamic Capabilities Theory, BDAC is conceptualized as a higher-order, VRIN-aligned strategic capability enabling firms to sense, seize, and reconfigure resources in digitally transformed environments. Survey data from 368 employees and managers were analyzed using structural equation modeling, revealing that CDT and SCDT significantly enhance CP, CDE partially mediates the CDT–CP relationship, and BDAC positively moderates both the CDT–CDE and SCDT–CP links. These findings underscore that technology adoption alone is insufficient; developing analytical capabilities, fostering a data-driven culture, and integrating BDAC into core supply chain functions are critical for realizing digital transformation value. The study contributes theoretically by elucidating BDAC’s role in bridging digital investments and perceived organizational outcomes, and practically by guiding managers to balance technological infrastructure with capability development. Limitations include its cross-sectional design and reliance on perception-based data, suggesting future longitudinal and cross-context research.

References

BARNEY, Jay. "Firm Resources and Sustained Competitive Advantage." Journal of Management, vol. 17, no. 1, 1991, pp. 99–120. https://doi.org/10.1177/014920639101700108.

BENDOLY, Elliot. "Linking Task Conditions to Performance Outcomes in Multi-task Work Settings: The Role of Information-Processing Requirements." Journal of Operations Management, vol. 27, no. 3, 2009, pp. 310–323.

CHOO, Chun Wei. "The Knowing Organization: How Organizations Use Information to Construct Meaning, Create Knowledge, and Make Decisions." International Journal of Information Management, vol. 16, no. 5, 1996, pp. 329–340.

DUBEY, Rameshwar, Angappa Gunasekaran, Stephen J. Childe, and Thanos Papadopoulos. "Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource-Based View and Big Data Culture." British Journal of Management, vol. 30, no. 2, 2019, pp. 341–361.

EISENHARDT, Kathleen M., and Jeffrey A. Martin. "Dynamic Capabilities: What Are They?" Strategic Management Journal, vol. 21, no. 10–11, 2000, pp. 1105–1121.

EKATA, N. "Information Management in Organizations: A Conceptual Framework." Information Management Review, vol. 28, no. 1, 2012, pp. 1–25.

EREVELLES, Sunil, Nobuyuki Fukawa, and Linda Swayne. "Big Data Consumer Analytics and the Transformation of Marketing." Journal of Business Research, vol. 69, no. 2, 2016, pp. 897–904. https://doi.org/10.1016/j.jbusres.2015.07.001.

GUPTA, Manish, and Joey F. George. "Toward the Development of a Big Data Analytics Capability." Information & Management, vol. 53, no. 8, 2016, pp. 1049–1064. https://doi.org/10.1016/j.im.2016.07.004.

HAIR, Joseph F., William C. Black, Barry J. Babin, and Rolph E. Anderson. Multivariate Data Analysis. 8th ed., Cengage Learning, 2019.

Hajli, Nick, Jonathan Sims, Ali H. Zadeh, and Marie-Odile Richard. "A Social COMMERCE Investigation of the Role of Trust in a Social Networking Site on Purchase Intentions." Journal of Business Research, vol. 68, no. 6, 2015, pp. 1084–1091.

HAYES, Andrew F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. 2nd ed., The Guilford Press, 2018. https://doi.org/10.4324/9781351045823.

IVANOV, Dmitry, and Alexandre Dolgui. "Viability of Intertwined Supply Networks: Extending the Supply Chain Resilience Angles towards Survivability." International Journal of Production Research, vol. 58, no. 10, 2020, pp. 2904–2915. https://doi.org/10.1080/00207543.2020.1750727.

KACHE, Florian, and Stefan Seuring. "Challenges and Opportunities of Digital Information at the Intersection of Big Data Analytics and Supply Chain Management." International Journal of Operations & Production Management, vol. 37, no. 1, 2017, pp. 10–36.

MIKALEF, P., Ioannis O. Pappas, John Krogstie, and Michail Giannakos. "Big Data Analytics Capabilities: A Systematic Literature Review and Research Agenda." Information Systems and e-Business Management, vol. 16, no. 3, 2018, pp. 547–578. https://doi.org/10.1007/s10257-017-0362-y.

TEECE, David J., Gary Pisano, and Amy Shuen. "Dynamic Capabilities and Strategic Management." Strategic Management Journal, vol. 18, no. 7, 1997, pp. 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7

WAMBA, Samuel Fosso, Rahul Dubey, Angappa Gunasekaran, and Shahriar Akter. "The Performance Effects of Big Data Analytics and Supply Chain Ambidexterity: The Moderating Effect of Environmental Dynamism." International Journal of Production Economics, vol. 222, 2020.

WARNER, Karl S. R., and Marcus Wäger. "Building Dynamic Capabilities for Digital Transformation: An Ongoing Process of Strategic Renewal." Long Range Planning, vol. 52, no. 3, 2019, pp. 326–349.

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Published

2026-01-26

How to Cite

Xing, Y., & Wongkumchai, T. (2026). AMPLIFYING THE DIGITAL SUPPLY CHAIN MODEL: THE MODERATING ROLE OF BIG DATA ANALYTICS CAPABILITY ON PERCEPTIONS OF PERSONNEL IN THE MANUFACTURING INDUSTRY. Veredas Do Direito, 23(3), e234369. https://doi.org/10.18623/rvd.v23.n3.4369