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PS-3.09: Trade, foreign direct investments, value chains and innovation network 4
10:30am - 12:00pm
Session Chair: Ebrahim Souzanchi Kashani, Sharif University of Technology Discussant: Rasmus Lema, Aalborg University, Globelics Secretariat
Location:Palace Room (Homann)
The Impact of Social Capital on Firm’s Innovation: Empirical Evidence from Armenia.
This study extends prior research that addresses the effects of network resources and reveals the multifaceted contribution of a board network to the firm innovative performance. In this study the social capital theory is applied to elaborate how board networks influence innovation. This study also moves beyond the structural aspects of the board network ties, and underscores the contribution of network resources, which directly capture the characteristics and resources that partner firms are endowed with. Analysis of 200 Armenian firms suggests that the contribution of network resources to the firms’ innovativeness varies with network structure. Furthermore, the study finds that diversity, resourcefulness and foreign ties of the firm’s network are important for improving innovative performance (including degree of novelty of firms innovation). Our empirical results show that a firm’s absorptive capacity is significant for innovation, especially when it complements centrality in board network.
Identifying New Ideal Types of Reverse Innovation of Enterprises from Developing Countries: Cases of Chinese Enterprises
Jun Jin1, Min Guo1, Maureen McKelvey2, Zhengyi Zhang1
1Zhejiang University, China, People's Republic of; 2University of Gothenburg, Sweden
The rapid growth of developing countries and increasing globalization of multinational enterprises from developing countries push the emergence of the reverse innovation, which the technology or innovation transfer from developing countries to advanced countries. However, the reverse innovation taken by enterprises from developing countries is still under research. The paper tries to illustrate reverse innovation types of enterprises from developing countries taken Chinese enterprises as cases, and propose a framework to identify three ideal types of reverse innovation. Chinese cases are used as cases to examine the three ideal types of reverse innovation and analyse their characteristics and implementation. Strategic suggestions on implementation of reverse innovation are provided to enterprises in developing countries at the end of paper.
The Development of the National Innovation System Research: Towards an Interdisciplinary Framework?
Marija Rakas, Daniel Hain
Aalborg University, Denmark
In this paper we map the development of the "National Innovation Systems" (NIS) research within the innovation studies literature as evident among its users towards a systemic and interdisciplinary approaches. Our first aim is to come to a more comprehensive understanding of the initial versions of the NIS framework as introduced in the three NIS books by Freeman, Lundvall, and Nelson, that shaped the development of the field. Despite differences in studying NIS between the three approaches, what is regarded as common is a focus on the constituents of systems of innovation, that is, institutions, organizations and interactions. Departing from this intellectual heritage, our second aim is to provide an insight into the development of NIS research over time, and it's influence on the broader field of innovation studies, in terms of whether (or not) it has advanced multidimensional and interdisciplinary research of socio-economic systems. Therefore, we map the structure of knowledge production of research in innovation studies as a network of academic publications, connected by their bibliographic coupling strength. Within this publication network, we use modularity-maximization techniques from network analysis to identify existing and emerging academic community structures. We use the coupling strength between communities as indicator of integrative and interdisciplinary research. Further, to derive a measure for multidimensionality, we manually categorize the central publications of the communities according to their inclusion of the identified constituents of systems of innovation; institutions, organizations and interactions. Further, we deploy methods from natural language processing, namely latent dirichlet allocation (LDA) topic modeling, to add in an unrestricted and data-driven way a qualitative layer of information on the context and themes of research. While we see an overall development towards more interdisciplinary and multidimensional research in innovation studies, we also observe substantial heterogeneity between the communities.