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Simulation study of enterprise intelligent transformation behavior based on complex network evolutionary game.

Liang Su1, Can Xie2, Yufeng Jiang3

  • 1Shandong Xiandai University, Ji'nan, Shandong, China.

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Summary
This summary is machine-generated.

Intelligent transformation is key for business competitiveness. This study uses a complex network model to show that government support, lower server costs, and better pricing strategies foster cooperation between tech providers and adopting enterprises.

Keywords:
Complex networkEvolutionary gameIntelligent transformationSimulation analysis

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Area of Science:

  • Business Strategy
  • Complex Systems
  • Economic Modeling

Background:

  • Global competition and intelligent technologies drive enterprise evolution.
  • Intelligent transformation is crucial for competitiveness, but Chinese firms are in early stages.
  • Existing research often lacks dynamic and network-aware perspectives on enterprise transformation.

Purpose of the Study:

  • To analyze the dynamic evolutionary mechanisms of intelligent transformation.
  • To identify key factors influencing strategic choices for intelligent server providers and adopting enterprises.
  • To develop a two-layer heterogeneous complex network model for simulating enterprise intelligent transformation.

Main Methods:

  • Utilized complex network theory and evolutionary game theory.
  • Developed a two-layer heterogeneous complex network model.
  • Conducted Python-based simulations and calibrated parameters with real financial data.

Main Results:

  • Government subsidies, reduced server costs, higher transformation benefits, and strategic pricing promote cooperation.
  • Network structure significantly influences strategic selection between supply and demand sides.
  • Simulations provide insights into dynamic evolutionary cooperation in intelligent transformation.

Conclusions:

  • The study offers a dynamic, spatial-relationship-aware view of intelligent transformation.
  • The two-layer heterogeneous network model addresses participant homogeneity limitations.
  • Provides theoretical support and context-specific insights for enterprise intelligent transformation strategies.