Impacts of inter-organisational knowledge transfer networks on different types of innovations in SMEs

2.50
Hdl Handle:
http://hdl.handle.net/10547/296159
Title:
Impacts of inter-organisational knowledge transfer networks on different types of innovations in SMEs
Authors:
Poorkavoos, Meysam
Abstract:
This research aims to understand the contributions of inter-organisational knowledge transfer to innovation in SMEs from a social network perspective. The main objective is to identify the impact of the network characteristics on company’s innovation performance. Organisations are embedded in a network of relationships with other companies. They must make the best use of all available resources in order to survive and thrive in today’s competitive environment. However, most of the previous network studies focus on large organisations and studying network effects in the context of SMEs is not well explored. This study sheds light on the relationships between different network characteristics and two different types of innovation performance in High Tech SMEs. In this study inter-organisational knowledge transfer networks were investigated from ego-network perspective. Radical and incremental innovation was identified as specific types of innovation. More specifically this research studied the impact of the structural, relational and nodal properties of inter-organisational knowledge transfer network on radical and incremental innovation performance. In addition to network characteristics, internal capabilities of companies were also identified important. Pentathlon framework was used to capture firms’ innovation management capabilities. A survey instrument was used to collect data from a sample of UK Small to Medium size Enterprises (SMEs). A new innovation measurement instrument was developed to measure different types of innovation from companies’ and customers’ perspectives. The SMEs were chosen randomly from IT and Chemical industry. Inter-organisational relationships were mapped using social network techniques. Path analysis techniques including PLS were used to test the hypotheses of the study. In addition to the statistical method, Fuzzy set Qualitative Comparative Analysis was used to shed light on different combinations (various configurations) of factors that impact on radical and incremental innovation. This study has made theoretical contributions by identifying research gaps through review and synthesis of literature in innovation and inter-organisational relationships and social network theories. Moreover, a new framework was developed based on the concepts identified in social network and innovation literature. The integration of theories and concepts regarding inter-organisational relationships, innovation and social networks with a view of better understanding of the impact of network characteristics on specific types of innovation is another contribution of this study. This research shows how different network properties can help companies to achieve ambidextrousness, which is vital for organisations’ competitive advantages and long term survival. Moreover, this study reveals that the internal capabilities (innovation management practices) of a firm play a significant role in enabling the company to benefit from its network resources. It shows how different configuration of the internal capabilities and network resources can lead to a better radical/incremental innovation performance. Findings from this research can help managers to adapt their network resources according to their strategies and the level of the innovation that they want to achieve.
Publisher:
University of Bedfordshire
Issue Date:
May-2013
URI:
http://hdl.handle.net/10547/296159
Type:
Thesis or dissertation
Language:
en
Description:
A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy
Appears in Collections:
PhD e-theses

Full metadata record

DC FieldValue Language
dc.contributor.authorPoorkavoos, Meysamen_GB
dc.date.accessioned2013-07-16T08:49:29Z-
dc.date.available2013-07-16T08:49:29Z-
dc.date.issued2013-05-
dc.identifier.urihttp://hdl.handle.net/10547/296159-
dc.descriptionA thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophyen_GB
dc.description.abstractThis research aims to understand the contributions of inter-organisational knowledge transfer to innovation in SMEs from a social network perspective. The main objective is to identify the impact of the network characteristics on company’s innovation performance. Organisations are embedded in a network of relationships with other companies. They must make the best use of all available resources in order to survive and thrive in today’s competitive environment. However, most of the previous network studies focus on large organisations and studying network effects in the context of SMEs is not well explored. This study sheds light on the relationships between different network characteristics and two different types of innovation performance in High Tech SMEs. In this study inter-organisational knowledge transfer networks were investigated from ego-network perspective. Radical and incremental innovation was identified as specific types of innovation. More specifically this research studied the impact of the structural, relational and nodal properties of inter-organisational knowledge transfer network on radical and incremental innovation performance. In addition to network characteristics, internal capabilities of companies were also identified important. Pentathlon framework was used to capture firms’ innovation management capabilities. A survey instrument was used to collect data from a sample of UK Small to Medium size Enterprises (SMEs). A new innovation measurement instrument was developed to measure different types of innovation from companies’ and customers’ perspectives. The SMEs were chosen randomly from IT and Chemical industry. Inter-organisational relationships were mapped using social network techniques. Path analysis techniques including PLS were used to test the hypotheses of the study. In addition to the statistical method, Fuzzy set Qualitative Comparative Analysis was used to shed light on different combinations (various configurations) of factors that impact on radical and incremental innovation. This study has made theoretical contributions by identifying research gaps through review and synthesis of literature in innovation and inter-organisational relationships and social network theories. Moreover, a new framework was developed based on the concepts identified in social network and innovation literature. The integration of theories and concepts regarding inter-organisational relationships, innovation and social networks with a view of better understanding of the impact of network characteristics on specific types of innovation is another contribution of this study. This research shows how different network properties can help companies to achieve ambidextrousness, which is vital for organisations’ competitive advantages and long term survival. Moreover, this study reveals that the internal capabilities (innovation management practices) of a firm play a significant role in enabling the company to benefit from its network resources. It shows how different configuration of the internal capabilities and network resources can lead to a better radical/incremental innovation performance. Findings from this research can help managers to adapt their network resources according to their strategies and the level of the innovation that they want to achieve.en_GB
dc.language.isoenen
dc.publisherUniversity of Bedfordshireen_GB
dc.subjectN190 Business studies not elsewhere classifieden_GB
dc.subjectsmall to medium-sized enterprisesen_GB
dc.subjectSMEsen_GB
dc.subjectknowledge transferen_GB
dc.subjectknowledge transfer networksen_GB
dc.titleImpacts of inter-organisational knowledge transfer networks on different types of innovations in SMEsen
dc.typeThesis or dissertationen
dc.type.qualificationnamePhDen_GB
dc.type.qualificationlevelPhDen
dc.publisher.institutionUniversity of Bedfordshireen_GB
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