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通过量化风险网络 (QRNs) 推进复杂的适应性系统方法来实现企业风险管理
Ananya Sheth1, Joseph V Sinfield2
1Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA, USA. abs@calpoly.edu.
Scientific reports
|September 27, 2024
概括
本研究引入了量化风险网络 (QRN),以可视化企业风险,超越传统的合规性. 该QRN通过识别易受复杂风险级联故障的关键功能来帮助建立业务弹性.
科学领域:
- 企业管理 企业管理
- 网络科学 网络科学
- 风险管理 风险管理
背景情况:
- 企业是复杂的适应性系统 (CAS),易受不确定的风险的影响.
- 传统的风险管理往往忽视了风险的相互依赖性和非线性影响.
- 需要在企业风险管理 (ERM) 中转向弹性和CAS视角.
研究的目的:
- 开发一种系统的方法来使用CAS框架来表示ERM.
- 创建一个行业无关的风险因素清单,并将其映射到企业功能.
- 为了解和管理复杂的企业风险引入一种新的网络视图.
主要方法:
- 从大型文本数据中提取信息,以建立风险因素清单.
- 对业务经理进行调查,以了解风险功能和功能之间的相互依赖.
- 构建量化风险网络 (QRN) 以可视化企业风险.
主要成果:
- 开发了一个行业无关的可信风险因素清单.
- 创建了一个新的企业风险 (QRN) 复杂网络视图,展示小世界属性.
- 识别的中央公司功能对于使用网络分析 (例如,边缘中间中心性) 来进行非线性风险传播至关重要.
结论:
- 量化风险网络 (QRN) 为提高企业性提供了一个新的视角.
- 企业应该开发特定于公司的QRN,以识别漏洞并防止级联失败.
- 这种方法将ERM从降低风险转变为主动的弹性建设.
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