Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence. (October 2021)
- Record Type:
- Journal Article
- Title:
- Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence. (October 2021)
- Main Title:
- Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence
- Authors:
- Wu, Mengjia
Kozanoglu, Dilek Cetindamar
Min, Chao
Zhang, Yi - Abstract:
- Abstract: Digital transformation (DT) is prevalent in businesses today. However, current studies to guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly what DT is and the capabilities needed to enable it successfully. With the aim of filling the gaps, this paper presents a novel bibliometric framework that unearths clues from scientific articles and patents. The framework incorporates the scientific evolutionary pathways and hierarchical topic tree to quantitatively identify the DT research topics' evolutionary patterns and hierarchies at play in DT research. Our results include a comprehensive definition of DT from the perspective of bibliometrics and a systematic categorization of the capabilities required to enable DT, distilled from over 10, 179 academic papers on DT. To further yield practical insights on technological capabilities, the paper also includes a case study of 9, 454 patents focusing on one of the emerging technologies - artificial intelligence (AI). We summarized the outcomes with a four-level AI capabilities model. The paper ends with a discussion on its contributions: presenting a quantitative account of the DT research, introducing a process-based understanding of DT, offering a list of major capabilities enabling DT, and drawing the attention of managers to be aware of capabilities needed when undertaking their DT journey.
- Is Part Of:
- Advanced engineering informatics. Volume 50(2021)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 50(2021)
- Issue Display:
- Volume 50, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 50
- Issue:
- 2021
- Issue Sort Value:
- 2021-0050-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10
- Subjects:
- Digital transformation -- Digital capabilities -- Bibliometrics -- Topic analysis -- Artificial intelligence
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2021.101368 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 19763.xml