Abstract
We systematically review the data-driven innovation (DDI) literature spanning 2009-2022, analyzing key studies, assessing the current state of DDI research in information systems and operations management, and highlighting the research gaps. A classification framework to organize the DDI research literature is proposed. Using Gregor's (2006) theory classification framework, we identify theory types in the DDI literature. By applying the structural view (level of analysis) of Smith et al. (2011), we also investigate the level of analysis in the DDI literature. Our systematic literature review and analysis provide a roadmap both to facilitate knowledge creation and accumulation and to guide future DDI research. This review, the first of its kind focusing on DDI, summarizes DDI development, and identifies opportunities for new research, concluding with directions for future exploration in the field.
Original language | English |
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Pages (from-to) | 5815-5828 |
Number of pages | 14 |
Journal | IEEE Transactions on Engineering Management |
Volume | 71 |
DOIs | |
Publication status | Published - 9 Feb 2024 |
Keywords
- Conceptual framework
- data-driven innovation
- innovation
- literature review
- research agenda
ASJC Scopus subject areas
- Strategy and Management
- Electrical and Electronic Engineering