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Toward a more Efficient Knowledge Network in Innovation Ecosystems: A Simulated Study on Knowledge Management

1
School of Business Administration, Nanchang Institute of Technology, Nanchang 330099, China
2
Center for Israeli Studies of UESTC, University of Electronic Science and Technology of China, Chengdu 611731, China
3
Odette School of Business, University of Windsor, Windsor, ON N9B 3P4, Canada
4
School of Business, Nanjing Audit University, Nanjing 211815, China
5
School of Economics and Management, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(16), 6328; https://doi.org/10.3390/su12166328
Received: 3 July 2020 / Revised: 1 August 2020 / Accepted: 4 August 2020 / Published: 6 August 2020
(This article belongs to the Special Issue Digital Technologies for Collaborative Knowledge Networks)
Knowledge management has become increasingly important in the era of knowledge economy. This study explores what is an optimal knowledge network for more efficient knowledge diffusion among strategic partners in order to provide insights on sustainable enterprises and a more knowledge-efficient innovation ecosystem. Based on simulated analyses of the efficiency of knowledge network models, including regular network, random network, and small world network, this study shows that a random knowledge network is more efficient for knowledge diffusion when a mixture knowledge trade rule is used. This study thus helps identify which knowledge networks facilitate knowledge exchange among collaborative partners for sustainable knowledge management. Management practitioners and policymakers can use the findings to design more appropriate knowledge exchange networks to improve the efficiency of knowledge diffusion in an innovation ecosystem. View Full-Text
Keywords: knowledge network; knowledge management; network structure; innovation ecosystem knowledge network; knowledge management; network structure; innovation ecosystem
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MDPI and ACS Style

Tang, H.; Ma, Z.; Xiao, J.; Xiao, L. Toward a more Efficient Knowledge Network in Innovation Ecosystems: A Simulated Study on Knowledge Management. Sustainability 2020, 12, 6328. https://doi.org/10.3390/su12166328

AMA Style

Tang H, Ma Z, Xiao J, Xiao L. Toward a more Efficient Knowledge Network in Innovation Ecosystems: A Simulated Study on Knowledge Management. Sustainability. 2020; 12(16):6328. https://doi.org/10.3390/su12166328

Chicago/Turabian Style

Tang, Houxing; Ma, Zhenzhong; Xiao, Jiuling; Xiao, Lei. 2020. "Toward a more Efficient Knowledge Network in Innovation Ecosystems: A Simulated Study on Knowledge Management" Sustainability 12, no. 16: 6328. https://doi.org/10.3390/su12166328

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