Governance of artificial intelligence applications in a business audit via a fusion fuzzy multiple rule‑based decision‑making model

A broad range of companies around the world has welcomed artificial intelligence(AI)technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their operations and assists them in formulating appropriate strategies without any hysteresis.This research identifies the essential components of AI applications under an internal audit framework and provides an appropriate direction of strategies,which relate to setting up a priority on alternatives with multiple dimensions/criteria involvement that need to further consider the interconnected and intertwined relationships among them so as to reach a suitable judgment.To obtain this goal and inspired by a model ensemble,we introduce an innovative fuzzy multiple rule-based decision making framework that integrates soft computing,fuzzy set theory,and a multi-attribute decision making algorithm.The results display that the order of priority in improvement—(A)AI application strategy,(B)AI governance,(D)the human factor,and(C)data infrastructure and data quality—is based on the magnitude of their impact.This dynamically enhances the implementation of an AI-driven internal audit framework as well as responds to the strong rise of the big data environment.Highlights Artificial intelligence(AI)promotes the sustainability development of audit tasks.A fuzzy MRDM model extracts key factors from large amounts of data.Fuzzy decision-making trial and evaluation laboratory analysis accounts for dependence and feedback among factors.An effective framework of AI-driven business audit is proposed in which“AI cognition of senior executives”is the most important criterion.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

A prospect theory-based methodfor linguistic decision making under risk

Based on the prospect theory, a novel linguisticdecision method under risk is proposed. First, the alternativesunder each risk state are rated using linguistic terms, and＇ thelinguistic decision matrix is constructed. Secondly, thelinguistic terms are transformed into triangular fuzzy numbers,so that the linguistic evaluations can be changed into numericalforms. Thirdly, with the aid of the prospect theory, theprobability weight functions and the linguistic value functionscan be computed, based on which the prospective values of thealternatives are obtained. Finally, the alternatives are rankedwith respect to the prospective values combined of probabilityweight and linguistic value functions. Thus, the optimalchoice is made. The decision process takes the psychologicalpreferences of the decision maker into consideration. Thepracticality of the proposed method is illustrated through anapplication on stock selection problems.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the Electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi time points and multi indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the Multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

Method for Risky Multiobjective Group Decision-Making and Its Application

The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and approach for solving multiobjective decision-making problem among uncertain system, which is applicable for practical problem. Finally a case study shows a satisfactory result.

A Method for Risky Multiple Attribute Decision Making with Four - dimensional Reference Point

A method based on cumulative prospect theory was proposed to solve risky multiple attribute decision making problems with Four -dimensional reference points. Considering the influence of different learning processes and corresponding features on decision-making, a new reference-learning behavior is added, and a risk-based multiple-attribute decision-making method based on four-dimensional reference point cumulative prospect theory is proposed. Firstly, according to the cumulative prospect theory, the prospect value and the decision function value of the four reference points of learning, time, evaluation value and expected value are calculated respectively, and the cumulative prospect value matrix of each program dynamic is formed. Secondly,according to the WAA operalor, Maximize the stage weighting model to obtain the integrated cumulative prospect value. Finally, on the basis of this, the alternatives are sorted according to the size of the total cumulative prospect value, and compared with other methods, the validity and scientific of the proposed method are proved.

Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty

Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR,by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly,a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

A Study of the Anatomy of Decision Making in the Planning and Appraisal of Hong Kong Section of Guangzhou-Shenzhen-Hong Kong High Speed Rail

This paper will study the anatomy of the decision making of Hong Kong Section of Guangzhou-Shenzhen-Hong Kong High Speed Rail(XRL).The paper will focus on five aspects.They are drivers of megaprojects,mega infrastructure project as an agent of change,early and effective stakeholder engagement,Iron Triangle and context awareness.XRL will be regarded as a resonance test of the international literature findings.

装配式建筑吊装施工安全关键风险分析的改进DEMATEL方法

为了解决装配式建筑吊装施工安全风险评估体系缺失、演化路径不清的共性问题,提高施工安全科学管理水平,提出了一种基于改进决策试验与实验室评估法(Decision Making Trial and Evaluation Laboratory,DEMATEL)的关键风险识别与演化路径分析方法。基于扎根理论构建装配式建筑吊装施工安全风险评价指标体系,利用基于组合数有序加权算子(Combination Ordered Weighted Averaging,C-OWA)改进直接影响矩阵,建立DEMATEL模型决策矩阵,并通过因果关系图识别关键风险因素,探究关键风险演化路径,以武汉市某工程项目为背景开展实证研究。结果表明:该项目存在X_(1)(工人的专业水平与素质差)、X_(5)(工人的技能培训与安全教育不到位)、X_(15)(人员没有进行定期的安全培训)、X_(18)(现场施工安全管理水平低)、X_(19)(风险意识缺乏)等关键风险因素;在4条基础路径和2条复合路径中,复合路径的权重高于基础路径,随着关键风险之间直接和间接作用的复杂化,发生风险事件的可能性将逐步增加;复合路径除了通过基础路径与关键风险耦合得到以外,还可以通过基础路径的相互作用演化得到。

砖木结构古建筑火灾风险影响因子评估研究

提出模糊DEMATEL-ISM的方法,在建立古建筑火灾评价指标体系的基础上,对归属于4大类风险因素的25个潜在风险因子进行关联性分析,得出因子的因果属性及因子间的逻辑层次结构关系,从而对古建筑火灾风险进行评估。利用模糊DEMATEL-ISM法对华阴市西岳庙灏灵殿进行实例分析,结果表明:疏散与扑救条件、电器设备隐患的原因度较大,需要对其予以控制;耐火等级、火灾荷载的结果度大,为事故发生的主要原因;疏散与扑救条件、易燃易爆危险品、电器设备隐患、安全责任制、灭火应急预案和演练为古建筑火灾事故的关键风险因子,可为古建筑火灾风险管控工作提供相应参考。

基于装置运行平稳性的石油化工安全管理策略研究

为了找出并评价石化装置支配性风险因素,实现安全生产风险源头控制和管理,满足石化装置安全生产风险控制的高效性要求,通过建立石化装置事故风险影响模型,运用决策试验与评估实验室方法(DEMATEL)从“现代事故因果连锁理论”视角分析发现人、机(物)等风险因素都受管理因素支配。进而,基于工艺稳定性、工艺稳定性修正、非计划停工3个指标建立石化装置平稳性模型,对装置运行平稳率进行追踪统计,并通过实例对该模型进行了分析和验证。结果表明:该石化装置运行平稳性模型可以量化追踪事故风险支配性因素的控制效果,可展示石化装置不同阶段下的风险特点,可作为装置事故风险预警指标和安全管理绩效指标,可提高装置的安全管理水平。

经营投资责任追究与国有企业投融资期限错配改善

经营投资责任追究作为国有企业改革的重要举措,对投融资决策行为有着重要影响。文章选取2011—2021年我国沪深A股上市企业为样本,实证检验了经营投资责任追究对国有企业投融资期限错配的影响。结果表明,经营投资责任追究能够显著改善国有企业投融资期限错配;机制检验显示,经营投资责任追究通过提高投资决策质量和强化管理层风险规避意识,改善国有企业投融资期限错配;异质性分析发现,在管理层过度自信程度较高、股权激励水平较低和内源融资能力较差时,经营投资责任追究改善国有企业投融资期限错配的作用更明显。研究结果有助于规范和约束管理层非理性决策行为,推动国有企业做强做优做大,对加快建设世界一流企业具有重要借鉴意义。

水利工程施工的IT2FS-MARCOS风险评价

为解决专家决策的主观性造成的风险评价不确定性和不同风险参数权重下考虑多种风险因子评价问题,这里提出一种基于IT2FS-MARCOS法的水利工程施工风险评价方法。首先确定水利工程施工风险指标评估体系,运用最优最劣法(BWM)融合基于层间相关性的客观赋权法(CRITIC)的组合赋权法对各风险参数的权重进行分析;然后引入区间2型模糊集(IT2FS)改进多准则决策中的基于折衷方案的备选方案排序法(MARCOS)计算各风险因素的效用函数值,基于效用函数值进行风险因素分析和评价。结合工程实例应用,表明:地质、天气条件和作业计划安排等风险因素危险程度较高,其中地质条件对该施工项目安全威胁最大,为水利工程施工需重点管理的风险因子。该模型的特点是不仅考虑了专家评价的模糊性,而且采用多准则决策方法避免对风险参数简单加权,与优劣解距离法(TOPSIS)相比,本方法与工程实际符合得更好,有望为处理水利工程不确定信息下的风险评价提供一种新的思路。

基于D-I-M协同模型的企业数字化转型财务管理风险识别研究

数字化正在重塑经济发展的轨道,成为赋能经济增长新动力。精准识别财务管理风险中的关键指标及其相互关系,对企业更好地完成数字化转型尤为关键。融合企业人力、运营、财务、环境4个基本维度,从链式传导视角构建转型背景下企业财务管理风险指标体系。通过决策试验与评价实验室(DEMATL)法,分析各影响因素之间中心度和原因度关系,并利用解释结构模型(ISM),将矩阵进一步分析得到影响因素的层级划分,归纳影响因素之间的内在指向关系,最后运用交叉影响矩阵相乘(MICMAC)法计算各因素的驱动—依赖关系以判断其属性类别。提出通过D-I-M协同分析的方法,识别财务管理风险路径,为企业进行多链融合数字化转型、规避财务管理风险提供参考。

DEMATEL和模糊认知图在地铁深基坑施工安全风险动态评估中的应用

为探究地铁深基坑施工安全风险因素动态作用规律,科学预防施工安全事故,针对目前缺乏因素系统识别、因果关系量化和动态推理分析等共性问题,提出一种基于决策试验和评估实验室(Decision Making Trial and Evaluation Laboratory DEMATEL)与模糊认知图(Fuzzy Cognitive Map,FCM)的地铁深基坑施工安全风险分析方法。首先,通过理论分析与文献梳理,采用扎根理论识别风险因素;其次,结合专家调研与量化分析,利用DEMATEL方法分析风险因素的因果关系;再次,将DEMATAL决策矩阵转化为FCM模型的交互作用矩阵,展开风险因素的预测与诊断推理分析;最后,选取案例进行实证,验证模型方法的可用性与有效性。结果显示:因素X_(1)(人员安全风险意识)对其他因素的影响程度最高;因素X_(1)(人员安全风险意识)、X_(8)(安全施工组织设计方案)和X_(7)(施工安全风险管理措施)是排名前3的关键风险因素;完善安全施工组织设计方案是最有效的管控对策。

算法嵌入政府环境治理的正向效应、潜在风险与规制路径

与传统的政府环境治理模式相比,政府运用算法开展环境治理具有明显的正向效应:能够提升环境治理的精准性、预测性和高效性。算法嵌入政府环境治理的过程容易引发伦理、工具和法治三个维度的风险。伦理维度中面临价值失衡风险,工具维度中包含环境数据结构性不足、环境算法模型透明度不足的风险,法治维度中则存在环境算法模型掌控者权力滥用和责任分配不均的风险,故有必要对算法嵌入政府环境治理所诱发的风险建构系统性的法律规制体系,从而充分发挥算法自动化决策的环境治理优势。在规制路径的选择上,应当立足于宏观基本原则指引和具体规制方案设计两个方面,对算法嵌入政府环境治理的潜在风险进行系统规范:宏观层面上,算法嵌入政府环境治理应该遵循依法治理、公平正义、浮动比例和正当程序的基本原则。在具体的规制方案上,既要建立算法嵌入政府环境治理的支持结构,以发挥算法嵌入政府环境治理的优势,又要根据算法本身的漏洞,进行适当的规则变动,从而通过“支持性结构和适应性流变相平衡”的方式,提升具体规制方案的可行性。在具体规制方案的架构上,应秉持全过程治理的视角,实现事前预防、事中监管和事后归责相统一:在事前预防部分,要求算法嵌入政府环境治理能够切实符合伦理要求,建立完善的环境数据核准、反馈和保护机制以及环境算法模型的解释机制。在事中监管部分,应当建立算法嵌入政府环境治理的部门、社会组织和社会公众监管制度。在事后归责部分,需要压实算法嵌入政府环境治理的责任分配制度。

数字孪生城市建设与公共决策风险治理

数字孪生城市建设将数字孪生嵌入城市治理中,有助于提升决策能力、增进决策质量,进而优化民众认知与行动,形成相应的良性互动关系。数字孪生城市建设与公共决策风险治理之间高度契合,凭借其技术优势能够为决策者提供更为全面的支持,也有助于公共决策更加符合民众期望,促进公共决策公共价值的实现。基于公共决策重要性、风险社会中民众需求、数字孪生技术赋能等因素考量,文章结合当前数字孪生城市建设实际,分别从风险源头、风险认知与风险行动三个维度对数字孪生城市建设中的公共决策风险治理进行研究。数字孪生城市建设应坚持人民城市理念,在提升算法算力的基础上从治理公共决策风险源头、转变公共决策风险认知、引导公共决策风险行动等入手,以城市治理共同体构建促进公共决策风险治理。

食品安全风险监测计划何以高效决策?——基于组织规范构造的视角

食品安全风险监测计划决策的时效性、科学性乃至执行效率,往往受制于相关政府职能部门的组织机构建制水平。有必要基于组织规范构造的视角,围绕所涉政府职能部门的权责配置与职权行使事项,来系统性约束和保障其机构能力。一方面,应针对专有权责与共有权责来设定其权责配置规范,以彰显相应职能部门在该类决策过程中的差异性决策设计与多元化决策考量。另一方面,应针对监测计划设置与监测信息传递来设定其职权行使规范,以厘清相应职能部门在该类决策过程中的内部决策定位与外部决策整合。最终尝试依托复合决策维度中、决策要素驱动下的协同履职,来明晰实现高效决策的可行规范进路。