Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms

Babu, Mujahid Mohiuddin; Rahman, Mahfuzur; Alam, MA; Dey, Bidit Lal

Abstract

Although innovation from analytics is surging in the manufacturing sector, the understanding of the data-driven innovation (DDI) process remains a challenge. Drawing on a systematic literature review, thematic analysis and qualitative interview findings, this study presents a seven-step process to understand DDI in the context of the UK manufacturing sector. The findings discuss the significance of critical seven-step in DDI, ranging from conceptualisation to commercialisation of innovative data products. The results reveal that the steps in DDI are sequential, but they are all interlinked. The proposed seven-step DDI process with solid evidence from the UK manufacturing and research implications based on dynamic capability theory, institutional theory and TOE framework establish the building blocks for future studies and industry practice.

Citation

Babu, M. M., Rahman, M., Alam, M., & Dey, B. L. (2024). Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms. Annals of Operations Research, 333(2-3), 689-716. https://doi.org/10.1007/s10479-021-04077-1

• Journal Article Type: Article
• Acceptance Date: Apr 8, 2021
• Online Publication Date: Apr 21, 2021
• Publication Date: Feb 1, 2024
• Deposit Date: Apr 14, 2021
• Publicly Available Date: May 5, 2021
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer Verlag
• Volume: 333
• Issue: 2-3
• Pages: 689-716
• DOI: https://doi.org/10.1007/s10479-021-04077-1
• Keywords: Data products, Big data analytics, Data-driven innovation (DDI), Data governance
• Publisher URL: https://doi.org/10.1007/s10479-021-04077-1
• Related Public URLs: https://www.springer.com/journal/10479/