Innovation in the supply chain and big data: a critical review of the literature

Purpose - This paper aims to propose a framework investigating the diffusion and adoption process of big data (BD) in the supply chain (SC) as a tool to manage process innovation at technological, operational and strategical levels. Design/methodology/approach - A comprehensive systematic literature methodology is used to develop the theoretical conceptual framework, which comprehensively describes and captures the innovative stages of BD technology adoption process in SC with a multilevel perspective. Findings - Results show that BD has modified the supply network concept, starting from the dyadic relationships, triads up to the creation of a streamlined and integrated network. These changes are reflected in a novel integrated vision including both benefits and barriers. Research limitations/implications - The proposed framework supports companies in redesigning the processes affected by the adoption of BD, helping them in identifying the critical elements, barriers, benefits and expected performance. One limitation is the focus of the study on the analysis of the processes of adoption of BD technology in the SC considering a particular structure of SC characterized by only two levels of supply and by a reduced number of members. Originality/value - Although the role of BD in supply chain operations management (SCOM) is well acknowledged in the literature, its adoption and diffusion process from an interorganizational perspective is still missing. Specifically, the adoption stages of BD in SC have been defined at a strategic level, and successively the SC operations and technological perspective have been integrated to depict the operationalization of BD implementation and diffusion.