摘要
为探讨财险业非对称的竞争关系,本文利用网络分析法构建区域内财险企业竞争网络模型,以节点表示区域内的财险企业,以有向加权的边表示企业间的竞争强度,形成企业竞争网络拓扑结构。通过观测持续5 a的各类参量指标来反映其网络结构的演化及网络特性的动态变化过程,并分析其经济含义与可能的政策带来的影响。结果表明:财险产业竞争网络不是典型的小世界网络,其过大的核心节点的存在使得网络整体的平均路径过长,在2017年达到2.458,表明许多企业间不会存在直接的竞争关系;行业存在稳定的巨头,对于网络整体来说,此类节点对网络影响过大会使行业整体风险增大;行业呈现“顶端稳定性,中部活跃性,尾部上升性”的格局,且对于新进入企业而言,展开竞争的机会还有很多。
In order to explore the asymmetric competition relationship of the property insurance industry,this article uses network analysis to build a competitive network model for regional property insurance companies.The vertex represents a firm and the directed-weighted edges represent the competition intensity among enterprises,forming a competition network topology structure.The evolution of the network structure and the dynamic change process of the network characteristics are reflected by observing the various parameter indexes lasting for five years,and the economic implications and possible impacts of policies are analyzed.The results show that the competition network of property underwriting is not a typical small world network.The existence of oversized core vertexes makes the average path of the entire network too long,reaching 2.458 in 2017,indicating that there is no direct competition among many enterprises.Some stable giants exist in property insurance.For the network as a whole,the impact of such vertexes on the network will increase the overall risk of the industry.The underwriting presents a pattern of“top stability,central activity,and tail rise.”Moreover,there are many opportunities for new entrants to engage in the competition.
作者
朱建新
刘浏
ZHU Jianxin;LIU Liu(School of Economics and Management, Harbin Engineering University, Harbin 150001, China)
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2021年第3期439-446,共8页
Journal of Harbin Engineering University
基金
国家自然科学基金项目(71872057)
黑龙江省博士后科研启动金项目(LBH-Q17040)
黑龙江省社科基金项目(18GLB024).
关键词
网络分析
复杂网络
竞争关系
财产保险
结构参量
小世界网络
网络中心性
度分布
network analysis
complex network
competitive relationship
property insurance
structural parameters
small world network
network centrality
degree distribution
