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Research on the knowledge transfer mechanism of digital platform in the digital innovation ecosystem: an improved model of SIR embedded in symbiosis theory

Jingtao Liu (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China)
Lianju Ning (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China)
Qifang Gao (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 23 October 2023

158

Abstract

Purpose

In the digital economy era, digital platforms are vital infrastructure for innovation subjects to perform digital innovation activities. Achieving efficient and smooth knowledge transfer between innovation subjects through digital platforms has become a novel research subject. This study aims to examine the knowledge transfer mechanism of digital platforms in the digital innovation ecosystem through modeling and simulation to offer a theoretical basis for digital innovation subjects to acquire digital value through knowledge-sharing and thus augment their competitive advantage.

Design/methodology/approach

This study explores the optimal symbiotic interaction rate between different users based on the classic susceptible-infected-removed (SIR) model. Additionally, it constructs a knowledge transfer mechanism model for digital platforms in the digital innovation ecosystem by combining the theories of communication dynamics and symbiosis. Finally, Matrix Laboratory (MATLAB) software is used for the model and numerical simulation.

Findings

The results demonstrate that (1) the evolutionary path of the symbiotic model is key to digital platforms' knowledge transfer in the digital innovation ecosystem. In the symbiotic model, the knowledge transfer path of digital platforms is “independent symbiosis—biased symbiosis (user benefit)—reciprocal symbiosis,” aligning with the overall interests of the digital innovation ecosystem. (2) Digital platforms' knowledge transfer effects within the digital innovation ecosystem show significant differences. The most effective knowledge transfer model for digital platforms is reciprocal symbiosis, whereas the least effective is parochial symbiosis (platform benefit). (3) The symbiotic rate has a significant positive impact on the evolutionary dynamics of knowledge transfer on digital platforms, especially in the reciprocal symbiosis model.

Originality/value

This study's results aid digital innovators in achieving efficient knowledge transfer through digital platforms and identify how symbiotic relationships affect the knowledge transfer process across the ecosystem. Accordingly, the authors propose targeted recommendations to promote the efficiency of knowledge transfer on digital platforms.

Keywords

Acknowledgements

The authors would like to thank Zhiyun for their significant input in revising the wording of this paper.

Citation

Liu, J., Ning, L. and Gao, Q. (2023), "Research on the knowledge transfer mechanism of digital platform in the digital innovation ecosystem: an improved model of SIR embedded in symbiosis theory", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-06-2023-0987

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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