Digital Threads and IT Power: Decoding Their Combined Effect on Manufacturing Performance

This research aims to evaluate the impact of digital supply chain on that of organizational performance in the manufacturing industry with IT capabilities as mediating factor. Quantitative approach is utilized to conduct this research, using a snowball sampling approach, focusing on the five largest organizations that manufacture oil and gas. Overall, a sample of 170 Digital Supply Chain Managers is gathered to provide valuable insight with the help of an online survey questionnaire. Findings suggest that funding in continuous training, nurturing culture of innovation, enhancing cybersecurity measures, adopting advanced IT infrastructure and leveraging data analytics are crucial for maximizing the advantages of digital supply chains. The aforementioned strategies facilitate organizations to attain substantial progress in strategic agility, and operational efficiency; thereby, maintaining competitive advantage in a technology-driven corporate environment. The discussion highlights pivotal role of IT capabilities in elevating supply chain processes through AI and IoT which enhance predictive analytics, supports strategic planning, improves organizational performance and improve operational efficiency. Survey data analysis revealed a strong positive relationship between digital supply chains, organizational performance and IT capabilities. Regression analysis also validated the relationship, with an adjusted R square of 0.934, signifying a vigorous correlation. Besides, ANOVA results confirmed minimal variance, supporting the consistency of data. The analysis offer valuable insights and emphasize on the significance of integrating digital supply chain with modern IT capabilities so as to drive organizational success particularly for manufacturing organizations.

• Publication year

  2025

• Venue

  International Journal of Technology Innovation and Management (IJTIM)

• Publication date

  2025-11-10

• Fields of study

  Not labeled

• Identifiers
  DOI 10.54489/ijtim.v5i1.534
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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