Data-Driven Innovation: A Literature Review, Conceptual Framework, and Research Agenda
系统综述2009-2022年数据驱动创新文献，提出分类框架并识别研究空白，为未来研究提供路线图。
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 [1] theory classification framework, we identify theory types in the DDI literature. By applying the structural view (level of analysis) of Smith et al. [2], we also investigate the level of analysis in the DDI literature. Our systematic literature review (SLR) 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.