Abstract

This paper investigates the effect of different Internet application scenarios on the forward and reverse knowledge transfer between architecture enterprises and component enterprises in the context of modular production in manufacturing enterprises. After dividing the Internet contexts into three the perspectives of Internet tools, Internet platforms, and Internet resources, this paper adopts a system dynamics approach to construct a causality model and a system flow diagram of the influence of different Internet contexts on the knowledge transfer between architecture enterprises and component enterprises, and uses Vensim PLE software to simulate and conduct a sensitivity analysis of the model. The results show that the three Internet contexts, namely Internet tools, Internet platforms, and Internet resources, can promote both positive and negative knowledge transfer between architecture enterprises and component enterprises, and exhibit a steadily growing trend of promotion; Internet tools and Internet resources are more conducive to positive knowledge transfer from architecture enterprises to component enterprises, and Internet platforms have a stronger facilitation effect on the reverse knowledge transfer from the component enterprises to the architecture enterprises. Our research offers useful recommendations for businesses on how to utilize various Internet settings to promote and assist effective knowledge transfer.

Highlights

  • The process of technology transfer is accompanied by knowledge flows [1]

  • Globalization has decentralized the production of components linked through global value chains (GVCs) in the emerging market countries such as China, where GVCs are embedded in the form of subcontractors or original equipment manufacturers (OEMs) who are gradually acquiring, upgrading technologies, and accumulating a wealth of production knowledge [2]

  • (2) Internet tools and Internet resources are more conducive to forplatforms, and Internet resources, can facilitate forward and reverse knowledge transfer between architecture enterprises and component enterprises and show a trend of gradually increasing facilitation

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Summary

Introduction

The process of technology transfer is accompanied by knowledge flows [1]. Globalization has decentralized the production of components linked through global value chains (GVCs) in the emerging market countries such as China, where GVCs are embedded in the form of subcontractors or original equipment manufacturers (OEMs) who are gradually acquiring, upgrading technologies, and accumulating a wealth of production knowledge [2]. This paper uses a system dynamics approach to explore the differential effect of different Internet application scenarios on the knowledge transfer process between architecture and component enterprises in the context of modular production in manufacturing enterprises. The application of Internet tools has enhanced the ability of enterprises to collect information, process data, and apply digital technologies to aid in decision-making [42]; enterprises can use Internet platforms to explore new models for business growth [43], and to take advantage of the learning opportunities created for the enterprises by the Internet platforms [44], to access online communities such as business incubators and accelerators [45], and to establish instant connections with professionals [46], thereby increasing the efficiency of inter-enterprise knowledge transfer. This paper constructs a system dynamics model and uses causality diagrams, system flow diagrams, and simulation analysis to comprehensively analyze the influence mechanism of knowledge transfer between architecture enterprises and component enterprises in a manufacturing modular production under different Internet contexts

The Causality Model and Main Feedback Loops
Model Assumptions and System Flow Chart
Model Equation Design and Parameter Explanation
Design Equation
Simulation Analyses
Extreme Conditions Test
Sensitivity Analysis
Conclusions and Implications
Theoretical Contributions
Managerial Implications
Limitations and Future Research Directions
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