Collaborating for Innovation: the socialised management of knowledge

Although the importance of diverse knowledge is widely recognised for open innovation, there may be a gap in our understanding of the social processes that shape how collaborators engage in knowledge exchange. This social gap may be significant because of the powerful, but largely unexplained, role attributed to trust as a social artefact. Moreover, we see trust as a process and that different types of trust are involved in the collaborative process. Thus, this paper uses a qualitative methodology to capture the experiences of innovation collaborators. As explanation of the dynamic interplays of knowledge and trust, we offer a description of phases in the process. Our analysis finds that the relationship moves from transactional to social. The early phases are characterised by technical knowledge, but the later and mature phases are identified with knowledge of the person and by personal trust. The success of innovation is a result of relationships with augmented trust. We found that a fabric of trust is woven from the weft of professional knowledge and the warp of personal knowledge to support innovation. We propose that this developing of relationships might be conceived as becoming more open in the sense of sharing with one another. If so, we seem to have described and offered a social dimension of open innovation

Profit differentials and innovation

The article aims to investigate empirically the effects of innovative activities on corporate profitability, using a panel of 267 UK manufacturing firms, over the period 1988-1992. Using the Bayesian approach to, explicitly, consider heterogeneity among firms, we find: (i) a positive and well-determined effect of innovation on profits that smoothly decreases as time passes by; (ii) a difference in profitability between innovators and non-innovators, greater when the comparison is between persistent innovators and non-innovators; and (iii) a long-run persistence in profit differentials.Innovation, Profitability, Firms differentials, Bayesian estimation, Panel data models,