School of Economics & Management, Northwest University, Xi'an, China.
PLoS One. 2023 Dec 20;18(12):e0295327. doi: 10.1371/journal.pone.0295327. eCollection 2023.
Enterprise digitalization and intellectualization (EDI) is a crucial aspect of China's modernization process. However, uncertainty in market and business decisions hinders the EDI diffusion process in China. Therefore, this research aims to solve the uncertainty problem of EDI diffusion by examining market demand and government policy coordination. First, we utilize complex network game theory and establish a technology-organization-environment framework for the factors that influence the elements of EDI transformation by combining evidence from existing studies. Second, the network game model is constructed to analyze and optimize the updating rules in the network as a diffusion strategy that enterprises under the uncertain market can adopt. Finally, the impact of adjusting government subsidies and different premiums on the diffusion of EDI transformation strategies is examined. The degree of market diffusion and average revenue of EDI are higher after the optimization of network node strategy updating rules compared to before optimization. Further analysis reveals that only the premium effect of product pricing and inverted U-shaped subsidy support from the government affect the degree of market diffusion and the average revenue of EDI, while the other premium effects are not significant. These findings enrich research related to complex networks and nonlinear dynamic strategies. They also indicate recommendations for government policies to enhance diffusion efficiency and reasonable pricing for enterprises to promote returns.
企业数字化和智能化(EDI)是中国现代化进程的关键方面。然而,市场和商业决策的不确定性阻碍了 EDI 在我国的扩散过程。因此,本研究旨在通过考察市场需求和政府政策协调来解决 EDI 扩散的不确定性问题。首先,我们利用复杂网络博弈理论,结合现有研究证据,建立了一个影响 EDI 转型要素的技术-组织-环境框架。其次,构建网络博弈模型,分析和优化网络中作为企业在不确定市场下可采用的扩散策略的更新规则。最后,考察调整政府补贴和不同保费对 EDI 转型策略扩散的影响。与优化前相比,优化网络节点策略更新规则后,EDI 的市场扩散程度和平均收益更高。进一步的分析表明,只有产品定价的溢价效应和政府的倒 U 形补贴支持影响 EDI 的市场扩散程度和平均收益,而其他溢价效应不显著。这些发现丰富了与复杂网络和非线性动态策略相关的研究。它们还为政府政策提供了建议,以提高扩散效率和企业的合理定价,促进回报。