Using big data for co-innovation processes: Mapping the field of data-driven innovation, proposing theoretical developments and providing a research agenda. (October 2021) - Bresciani, Stefano; Ciampi, Francesco; Meli, Francesco; Ferraris, Alberto
Highlights: Literature on open innovation, co-creation and collaborative innovation should be merged to understand data-driven innovation. Big data allows for the development of passive and unintentional co-innovation processes. Future studies on big data should be developed mainly around three key lines of research. Abstract: This is the first systematic literature review concerning the interconnections between big data (BD) and co-innovation. It uses BD as a common perspective of analysis as well as a concept aggregating different research streams (open innovation, co-creation and collaborative innovation). The review is based on the results of a bibliographic coupling analysis performed with 51 peer-reviewed papers published before the end of 2019. Three thematic clusters were discovered, which respectively focused on BD as a knowledge creation enabler within co-innovation contexts, BD as a driver of co-innovation processes based on customer engagement, and the impact of BD on co-innovation within service ecosystems. The paper theoretically argues that the use of BD, in addition to enhancing intentional and direct collaborative innovation processes, allows the development of passive and unintentional co-innovation that can be implemented through indirect relationships between the collaborative actors. This study also makes eleven unique research propositions concerning further theoretical developments and managerial implementations in the field of BD-driven co-innovation.