Simulation Analysis of Artificial Intelligence Technology Diffusion under Market Competition and Policy Incentives Based on Complex Network Evolutionary Game Models

IF 2.3 4区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Systems Pub Date : 2024-07-07 DOI:10.3390/systems12070242
Xiaofei Ma, Jia Wang
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引用次数: 0

Abstract

The relationship network between enterprises will change their adoption behavior of AI technology and this micro-decision-making mechanism will eventually decide whether AI technology can diffuse and the extent of diffusion on the macro level. However, the existing AI technology diffusion research mostly focuses on the integration of AI technology with other industries from the industrial level, ignoring the complexity of the micro-complex game process and interactions within the enterprise network on the macro technology diffusion. In this regard, this paper builds a game model of AI technology diffusion in core and non-core enterprises from the levels of market competition and policy incentives based on complex network evolutionary game theory. It does this through simulation analysis that examines the mechanism of key factors affecting the diffusion of AI technology, as well as the influence and combination effects of pertinent policies. The study shows that (1) AI technology diffuses more effectively in non-core enterprises than it does in core enterprises; (2) changes in parameters like technology cost and policy regimes have a more evident impact on core enterprises than non-core ones; (3) in market competition, increasing the network average degree, the proportion of AI technology products in the mainstream market, the opportunity cost, the cost reduction factor, or decreasing the cost of AI technology can all promote the diffusion of AI technology; (4) under policy incentives, increasing the proportion of AI technology subsidies and the influence of high-tech identification of enterprises can both promote the diffusion of AI technology.
基于复杂网络演化博弈模型的市场竞争和政策激励下的人工智能技术扩散仿真分析
企业间的关系网络会改变企业对人工智能技术的采用行为,这种微观决策机制最终将决定人工智能技术能否扩散以及在宏观层面的扩散程度。然而,现有的人工智能技术扩散研究多从产业层面关注人工智能技术与其他产业的融合,忽视了宏观技术扩散的微观复杂博弈过程和企业网络内部互动的复杂性。为此,本文基于复杂网络演化博弈理论,从市场竞争和政策激励两个层面构建了核心企业与非核心企业人工智能技术扩散的博弈模型。本文通过模拟分析,研究了影响人工智能技术扩散的关键因素的作用机理,以及相关政策的影响和组合效应。研究表明:(1) 人工智能技术在非核心企业的扩散比在核心企业更有效;(2) 技术成本和政策制度等参数的变化对核心企业的影响比非核心企业更明显;(3)在市场竞争中,提高网络平均程度、人工智能技术产品在主流市场中的比例、机会成本、成本降低系数或降低人工智能技术成本都能促进人工智能技术的扩散;(4)在政策激励下,提高人工智能技术补贴比例和企业高新技术认定的影响力都能促进人工智能技术的扩散。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Systems
Systems Decision Sciences-Information Systems and Management
CiteScore
2.80
自引率
15.80%
发文量
204
审稿时长
11 weeks
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