Firms need to continuously innovate to maintain or enhance their competitive advantage. Technological advances are driving the proliferation of increasingly complex knowledge and firms no longer can solely rely on their internal knowledge assets for innovation. A growing number of firms are embracing open innovation as a competitive strategy. Open innovation is a distributed innovation process based on purposively managed knowledge flows to accelerate internal innovation and expand markets for external use of innovation.
Some firms are better than others in capturing value from open innovation due to their ability to acquire, transform and exploit new knowledge for commercial purposes – an ability known as absorptive capacity. The social mechanisms through which firms acquire and use external knowledge to innovate remain under-investigated. One may view absorptive capacity as a specific example of organisational learning concerning a firm’s relationship with new external knowledge. Looking at absorptive capacity through the lens of socio-psychological learning processes may provide insight into critical firm-based factors that develop it.
The CSIRO is exploring how social networks affect absorptive capacity in open innovation collaborations. A major goal is to gain insight into personal and organisational factors influencing boundary-spanning knowledge sharing, idea generation, idea realisation, and trust networks, and how these different networks relate to each other. A secondary goal is to discover how tacit knowledge and power relationships influence intra- and inter-organisational learning processes that underpin absorptive capacity.
Mixed method social network analysis will be used to scrutinise the structure and content of boundary-spanning social networks in three open innovation case studies drawn from the agricultural and food products industry. This industry must become increasingly innovative to deal with expanding markets and increased competition arising from the implementation of multilateral free-trade agreements.
The mixed method social network analysis uses socio-centric network analysis to observe different patterns of connection across the open innovation collaboration as a whole, and semi-structured interviews to assess the nature of communication between selected individuals in central positions or at the fringes of networks. Patterns of brokerage, network closure and reciprocity will be examined using a multi-theoretical analytical framework that allows simultaneous assessment of social mechanisms operating at the individual, relational, group and organisational levels. The semi-structured interviews will explore how patterns of connection are shaped by industry and organisational factors and what this means in terms of intra- and inter-organisational learning and level of collaboration.
A network perspective of open innovation that focuses on the social mechanisms of absorptive capacity operating at different levels fills an existing gap in knowledge and will contribute to more effective management of knowledge flows in open innovation.
For more information about this research, please contact Andrew Terhorst.