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Relations Embedded In Research On Technological Innovation Performance

Posted on:2009-11-07Degree:DoctorType:Dissertation
Country:ChinaCandidate:G N XuFull Text:PDF
GTID:1119360242986215Subject:Management Science and Engineering
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Over the last two decades, the manufacturing paradigm of the world has been changing significantly along with the flourish of global manufacturing networks. The relationship among firms has been transformed from pure competition to competition and collaboration, where a win-win strategy can be carried out. Learning and innovation has become the key factors for firms to achieve competitive advantage. While globalization has opened many opportunity windows for firms in both developed countries and developing countries, Chinese firms should take these opportunities to speed up their integration into global manufacturing networks. Thus how to build up ties in global manufacturing networks and how to manage these relationships has become a most important issue for a firm to improve its technological innovation performance. However, although the existing research has outlined the characteristics of network resources and the competitive advantages they brought, there is a paradox about the mechanism of how a firm's relational embeddedness impacts on its performance, especially technological innovation performance, and the relative empirical studies are even insufficient.In order to facilitate firms to integrate and utilize network resources to improve their learning capabilities and innovation performances, and then to upgrade in global manufacturing networks, this dissertation aims to answer the basic question of "how relational embeddedness influences technological innovation performance". Specifically, this research question can be break down to the following four issues. First, what is the relationship between a firm's relational embeddedness in global manufacturing networks and its technological innovation performance? Second, what is the mechanism of relational embeddedness acting on the technological innovation performance? Third, what are the differences between the mechanism of upstream relational embeddedness and downstream relational embeddedness? Fourth, what are the effects of technological environment and market environment on the mechanism?This dissertation explores these issues by three sub-researches with combination of theoretical study and empirical study, literature review and investigation, and as well as qualitative research and quantitative research.Based on literature review, the first sub-research brings forward a primary theoretical supposition, and then conducts five explorative case studies of Chinese manufacturing firms to conclude with an initial theoretical framework of influence mechanism of relational embeddedness on technological innovation performance. On the basis of the first sub-research, the second sub-research goes on further theoretical analysis and puts forward a concept model of relational embeddedness influence mechanism. 228 firms in Zhejiang Province China are investigated via questionnaires, and Explorative Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) are conducted to establish and verify the measures, and Structural Equation Modeling (SEM) is applied to testify and modify the concept model. The result shows that relational embeddedness can promote technological innovation performance through explorative learning.Grounded on the results of the former two sub-researches, the third sub-research goes more deeply into the mechanism between relational embeddedness and explorative learning. Both upstream and downstream relational embeddedness are examined in a survey of 157 firms in Zhejiang Province China. Besides, technological dynamics and market dynamics of industrial environments are also taken in account in the mechanism. Thus the relationships among relational embeddedness, explorative learning and technological innovation performance have been elaborated step by step.Drawing on the above research, some conclusions can be presented asfollows:(1) Firm's relational embeddedness in global manufacturing networks has a positive effect on its technological innovation performance. Trust, information sharing and joint problem solving are all beneficial to the improvement of technological innovation performance.(2) Relational embeddedness influences technological innovation performance indirectly through the mediating role of explorative learning. In detail, inter-organizational trust promotes technological innovation performance through facilitating new knowledge acquisition and new knowledge application; information sharing enhances technological innovation performance through acting positively on new knowledge acquisition; joint problem solving improves technological innovation performance through accelerating new knowledge application; and new knowledge acquisition has a positive effect on new knowledge application.(3) Firm's relational embeddedness in both upstream networks and downstream networks has positive influence on explorative learning. Inter-organizational trust, information sharing and joint problem solving between a firm and its suppliers as well as customers facilitate new knowledge acquisition, while trust and joint problem solving between a firm and its suppliers or customers promote new knowledge application.(4) Environmental dynamics acts as a moderate factor in the influence mechanism of relational embeddedness on explorative learning. Relational embeddedness plays a more important role on explorative learning when the technological and market environment are more variable. Concretely speaking, in a more highly dynamic technological environment, trust as well as joint problem solving between a firm and its suppliers have a greater impact on its new knowledge acquisition; in a more highly dynamic market environment, trust as well as joint problem solving between a firm and its supplier have a more significant influence on its new knowledge application.As a whole, focusing on how relational embeddedness influences technological innovation, this dissertation conducts some theoretical innovations as follows.(1) It's a complement of the existing research on inter-firm network theories for it builds up linkages among theories of network embeddedness, organizational learning and technological innovation to open the black-box of how relational embeddedness acts on technological innovation performance. This dissertation puts forward a theoretical framework of "relational embeddedness - exploarative learning - technological innovation performance", which uncovers the nature of the action process of network embeddedness and emphasizes the mediating effect of explorative learning.(2) It's an enrichment of research on organizational learning because it brings inter-firm learning and intra-firm learning together and abstracts explorative learning into new knowledge acquisition and new knowledge application, on basis of which the contents and roles of explorative learning in global manufacturing networks are examined.(3) It's an expansion of the research on network embeddedness for it considers upstream relational embeddedness and downstream relational embeddedness comprehensively and try to find the similarities and differences between them. And it provides a new perspective of research on manufacturing firm's embeddedness and suggestions on upgrading in global manufacturing network with consideration of the roles of different technological environment and market environment in the mechanism of upstream and downstream embeddedness and explorative learning.
Keywords/Search Tags:relational embeddedness, explorative learning, technological innovation performance, global manufacturing network, network embeddedness
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