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Scientometrics

, Volume 119, Issue 2, pp 657–685 | Cite as

Cooperative knowledge creation in an uncertain network environment based on a dynamic knowledge supernetwork

  • Liming Zhao
  • Haihong Zhang
  • Wenqing WuEmail author
Article
  • 143 Downloads

Abstract

Cooperative knowledge creation among enterprises is becoming increasingly common in uncertain environments with rapidly changing technology and increasingly complex network relationships. The objective of this paper is to better understand why and how an uncertain network environment affects an enterprise’s knowledge creation performance and knowledge creation decision-making based on a dynamic knowledge supernetwork. Regarding the methodology, we proposed a dynamic knowledge supernetwork model that contains an enterprise subnetwork and a knowledge subnetwork, constructed the knowledge creation and knowledge diffusion mechanisms, and simulated the process of knowledge creation and diffusion through a multi-agent simulation. Moreover, we utilized the empirical patent data of power technology to prove the rationality and effectiveness of our model and simulation results. The results involve three main aspects. First, knowledge performance shows an exponential growth pattern. Second, in the dynamic network, we obtain a U-shaped relationship only when the effort needed to establish new cooperation is relatively small, and the inverted U-shaped relationship disappears when the above parameter exceeds a certain threshold. Third, the knowledge-based cooperation strategy is superior to the network-based cooperation strategy, and knowledge performance increases linearly and decreases exponentially with increasing network dynamics when the effort needed to establish new cooperation does not exceed and exceeds the threshold, respectively.

Keywords

Cooperative knowledge creation Uncertain network environment Dynamic knowledge supernetwork Network dynamics Multi-agent simulation 

Mathematics Subject Classification

05C82 68U20 91B74 

JEL Classification

C63 L53 

Notes

Acknowledgements

This work was supported by the National Social Science Foundation of China (Grant No. 17BGL025). The authors are grateful to an anonymous referee for instructive comments that improved this paper.

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2019

Authors and Affiliations

  1. 1.College of Management and EconomicsTianjin UniversityTianjinChina

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