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

Mujahid Mohiuddin Babu, Mahfuzur Rahman, Ashraful Alam, Bidit Lal Dey

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)
182 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)689-716
Number of pages28
JournalAnnals of Operations Research
Issue number2-3
Early online date21 Apr 2021
Publication statusPublished - Feb 2024

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  • Big data analytics
  • Data-driven innovation (DDI)
  • Data products
  • Data governance


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