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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.

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.

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.

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.

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.

Despite the multiple calls for research on the dark side of open innovation, very few studies have approached the topic so far. This study aims to analyse successful and unsuccessful open innovation projects.

This study uses thematic analysis to describe the factors determining their (un)success. The researchers interviewed 27 managers and owners in the manufacturing sector. Then, the respondents were asked to discuss one successful and one unsuccessful open innovation project to explore the differences in triggers and setbacks, focusing on the causes that determined the failures.

Findings show that many interviewees are reluctant to identify failure cases, which somewhat explains the paucity of studies on the topic, and others do so when the failure is recognised by a third party (such as a public institution not granting funds to the project). This study discussed how this phenomenon is linked with the paradoxical relation between innovation success and failure. It is also found that triggers and setbacks determining the project's (un)success are markedly differently based on the technological intensity of the firm. Implications for scholars and practitioners are also drawn.

This study provides a balanced view between open innovation successes and failures to offer informative recommendations to practitioners. Furthermore, it contributes to filling the scarcity of studies related to risks and failures of open innovation projects. This gap has been addressed by studying the factors that determine the success and unsuccess of an open innovation project.