Strong Ties, Weak Ties and the Management of Innovation: The Case of Danish and German SMEs

Gretzinger, Susanne; Hinz, Holger; Matiaske, Wenzel

doi:10.1007/978-3-7908-2615-9_16

Cited by 9 publications

(7 citation statements)

References 38 publications

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“…"Weak ties aid exploration (the generation of new ideas), whereas strong ties aid exploitation (the implementation of new ideas)" (Barrie, Zawdie, & João, 2019: 212). The creation and diffusion of innovation are mostly attributed to weak ties (Gretzinger, Hinz, & Matiaske 2011).…”

Section: 2mentioning

confidence: 99%

Theorizing the Triple Helix model: Past, present, and future

2020

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The Triple Helix of university-industry-government interactions, highlighting the enhanced role of the university in the transition from industrial to knowledge-based society, has become widespread in innovation and entrepreneurship studies. We analyze classic literature and recent research, shedding light on the theoretical development of a model that has engendered controversy for being simultaneously analytical and normative, theoretical, practical and policy-relevant. We identify lacunae and suggest future analytical trajectories for theoretical development of the Triple Helix model. The explanatory power of Triple Helix has been strengthened by integrating various social science concepts, e.g. Simmel’s triad, Schumpeter’s organizational entrepreneur, institutional logics and social networks, into its framework. As scholars and practitioners from various disciplinary and inter-disciplinary research fields, e.g. artificial intelligence, political theory, sociology, professional ethics, higher education, regional geography and organizational behavior join Triple Helix studies or find their perspectives integrated, new directions appear for Triple Helix research.

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Section: 2mentioning

confidence: 99%

Theorizing the Triple Helix model: Past, present, and future

2020

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“…"Weak ties aid exploration (the generation of new ideas), whereas strong ties aid exploitation (the implementation of new ideas)" [35] (p. 212). The creation and diffusion of innovation are mostly attributed to weak ties [104]. For instance, one reason why the Triple Helix Model [8,71] provides optimal conditions for innovation is because through the interactions of university, industry and government-three traditionally not overly connected sectors or networks-a large variety of new ideas and technologies are likely to be created.…”

Section: Social Network Theorymentioning

confidence: 99%

Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence

2019

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This paper presents a potential solution to fill a gap in both research and practice that there are few interactions between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems. To strengthen the synergies between TIC and TUC for innovation, the first step is to match suitable industrial firms from two countries for collaboration through their common connections to transnational university/academic partnerships. Our proposed matching solution is based on the integration of social science theories and specific artificial intelligence (AI) techniques. While the insights of social sciences, e.g., innovation studies and social network theory, have potential to answer the question of why TIC and TUC should be looked at as synergetic entities with elaborated conceptualization, the method of machine learning, as one specific technic off AI, can help answer the question of how to realize that synergy. On the way towards a transdisciplinary approach to TIC and TUC synergy building, or creating transnational university-industry co-innovation networks, the paper takes an initial step by examining what the supports and gaps of existing studies on the topic are, and using the context of EU–China science, technology and innovation cooperation as a testbed. This is followed by the introduction of our proposed approach and our suggestions for future research.

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“…The most common collaboration partners for organizations on the Danish side of the border (excluding other campuses of SDU) include Danish universities and hospitals, but also North American technical universities (Table 4) There are only three papers with local (meaning within the border region) cross-border collaboration in the dataset: the two collaborations (Gretzinger, Hinz, & Matiaske, 2011;Royer, Simons, Boyd, & Rafferty, 2008) in the research area of business and economics between the Department of Border Region Studies (at SDU) and the Institute of International Management (at the University of Flensburg) and the List-Tønder link (Strasser et al, 2003) in the research areas of marine and freshwater biology and oceanography.…”

Section: <Table 2 About Here>mentioning

confidence: 99%

Scientific collaboration in the Danish–German border region of Southern Jutland–Schleswig

Makkonen

2015

Geografisk Tidsskrift-Danish Journal of Geography

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This paper investigates the geographical and organizational patterns of scientific collaboration, in terms of co-authored scientific articles, in the Danish-German border region of Southern Jutland-Schleswig. The motivation behind the approach lies in the fact that scientific collaboration in border regions, in general, and the studied region, in particular, has rarely been discussed in the academic literature.The integration model of cross-border regional innovation systems provides the conceptual framework for the task. The paper, thus, gives methodological insights for the measurement of cross-border integration of knowledge infrastructures. The analysis reveals that collaborating with partners close but on the opposite side of the border is rare. Instead, cross-border collaboration takes place with partners from more faraway international research organizations. The reasons behind this can be found in the science bases-arguably more than from historic, linguistic or ethnic reasons-of the adjacent sides of the border. The research fields that the local scientists are engaged in seem to be too different between the Danish and German sides of the border region to foster large numbers of co-authored publications and, thus, the knowledge infrastructure of the border region can be considered as weakly integrated.

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Strong Ties, Weak Ties and the Management of Innovation: The Case of Danish and German SMEs

Cited by 9 publications

References 38 publications

Theorizing the Triple Helix model: Past, present, and future

Theorizing the Triple Helix model: Past, present, and future

Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence

Scientific collaboration in the Danish–German border region of Southern Jutland–Schleswig

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