唐山区域内企业人力资源管理信息化SWOT模型分析

本文综合运用SWOT、PEST、AHP分析方法探讨唐山区域内企业人力资源管理信息化的影响因素,建立SWOT量化决策模型,并根据模型提出战略选择——退却保守型战略,旨在为唐山区域内企业人力资源管理信息化提供量化分析指导和参考.     

彩电供应链的环境绩效最优化研究

以彩电制造商为主的供应链为研究对象,从供应链对生态环境影响的角度应用生命周期方法建立一个多层次的闭环供应链环境绩效最优化模型,并运用MATLAB对实验数据进行求解,讨论制造商如何选择供应商和回收处理方式以达到最优化供应链对生态环境的影响的目的,并对优化方案的结果进行分析,旨在提高整个供应链的可持续性。     

基于AHP/DEA的物流中心选址问题研究

物流中心的选址问题是物流管理系统中一个非常重要的问题,影响物流中心选址的因素除建站费用、运输费用等可量化因素外,许多定性因素并未纳入考虑范畴.基于AHP/DEA分析基础上的选址方法将选址问题分成AHP分析、DEA评价及整数规划3个部分,运用AHP充分考虑定性因素,并将候选点进行DEA有效性排序,最后代入整数规划模型得到最终决策.此方法能增强选址合理性,并降低决策的复杂度.     

旅游者目的地选择的影响因素分析

本文以旅游者消费行为学为依据,运用旅游消费者"刺激——反应"购买决策模型,综合考虑各类影响因素,从而构建了旅游者目的地选择的概念模型,以提供一个较为全面的研究框架来分析旅游者在进行目的地选择过程中经历的整个决策过程。     

零售商竞争环境下分散式供应链的定价与交货期联合决策模型

考虑了由一个制造商和两个相互竞争的零售商组成的两阶段分散式供应链系统,建立了价格和时间双敏感需求下的供应链定价与交货期联合决策模型,并给出了基于Stackelberg博弈的供应链定价和承诺交货期的最优决策。随后,以集中式供应链的决策为基准,分析了分散式供应链决策的效率。最后,通过数值分析,研究了市场因素和营销渠道竞争因素对分散式供应链的决策效率及承诺交货期的影响。结果表明,供应链下游的渠道竞争有利于提高分散式供应链的决策效率和缩短承诺交货期,从而提高整个供应链的市场竞争力。     

基于就业选择的决策模型分析

决策分析是在不确定环境中对涉及决策及决策的各种问题做出理性与系统的决定。本文利用层次分析法,对就业选择的决策问题,建立一个辅助决策模型,通过构造判断矩阵、一致性检验和层次总排序,得出该决策模型的可实用性,以提高就业选择的决策水平,使就业选择更加科学、合理。     

基于灰色理论的项目多目标决策模型及在造船工程中的应用

针对项目实施中多目标决策的复杂问题,以方案的灰色关联度作为评价准则,建立了灰色关联决策模型,并针对模型中如何确定相对理想方案的问题提出了解决方法。最后文章对该方法在造船工程中的应用进行了研究。     

基于道德决策模型的会计诚信教育方法研究

在经济全球化背景下,会计面临诚信危机的严峻挑战,加强会计诚信教育已迫在眉睫.本文将道德决策模型引入会计诚信教育之中,建立基于道德决策模型的会计诚信教育方法.该方法从大学会计专业的教育开始,通过了解和认清事实、认识道德问题、识别相关的规范和价值、找到备选行动方案、选择行动方案、思考行动方案可能会产生的结果、做出决策等多个与道德相关的识别和决策步骤,培养未来会计师和审计师的诚信和道德品质.     

基于客户识别的客户保持决策模型与定价策略

建立了以客户识别为基础进行客户保持决策的理论框架和决策模型,提出了客户识别的三维框架模型,认为客户识别需要在包含客户生命周期价值、客户感知价值和竞争可得性3个维度的框架下进行;随后通过建立客户识别模型,定量分析了客户识别对于客户保持的重要意义;接着阐述了以客户识别为基础进行客户保持决策的过程和方法,并综合考虑客户忠诚度因素,通过建立客户保持的决策模型,分析了统一定价和差别定价2种模式下客户保持的企业产品定价策略。     

基于贝叶斯网络推理的双重不确定信息集结模型

针对一类不确定多属性决策问题,提出了基于贝叶斯网络推理的信息集结决策模型。根据决策依据信息,建立了决策方案综合属性值优劣的范围估计模型;由影响方案属性的因素构成的贝叶斯网络拓扑结构图,建立了基于贝叶斯推理的方案综合属性值确定模型;基于两类信息的内在关联性,提出了两种结果集结的最大相似度模型,最后得出方案综合属性值,算例表明基于贝叶斯网络推理的双重不确定信息集结模型是有效的。     

动态多指标决策问题的投影寻踪模型

针对动态多指标决策中指标和时段的权重确定问题,提出了基于投影寻踪(PP)的理想点法新模型(PP-IPM模型)。该模型利用决策矩阵样本的内部信息,把方案的三维决策矩阵综合成一维投影值,投影值越大表示该方案越优,根据投影值的大小就可对各方案进行综合排序决策。建议用实码加速遗传算法进行PP-IPM的建模,简化了PP技术的实现过程,克服了目前PP技术计算过程复杂、编程实现困难的缺点。实例计算的结果说明,直接由决策矩阵样本数据驱动的PP-IPM模型用于动态多指标决策问题简便可行,适用性和可操作性强,具有推广应用价值。     

Uses and Misuses of Multicriteria Decision Analysis (MCDA) in Environmental Decision Making

We focus on a class of multicriteria methods that are commonly used in environmental decision making—those that employ the weighted linear average algorithm (and this includes the popular analytic hierarchy process (AHP)). While we do not doubt the potential benefits of using formal decision methods of this type, we draw attention to the consequences of not using them well. In particular, we highlight a property of these methods that should not be overlooked when they are applied in environmental and wider decision-making contexts: the final decision or ranking of options is dependent on the choice of performance scoring scales for the criteria when the criteria weights are held constant. We compare this "sensitivity" to a well-known criticism of the AHP, and we go on to describe the more general lesson when it comes to using weighted linear average methods—a lesson concerning the relationship between criteria weights and performance scoring scales.     

Selection of Logistic Service Providers for the transportation of refrigerated goods

The aim of this article is to propose a decision model based on Analytic Hierarchy Process (AHP) for the evaluation and selection of Logistics Service Providers (LSPs) for a refrigerated products company. The results indicated that quality, responsiveness and reliability are the most important criteria for selecting an LSP for the transportation of perishable refrigerated goods, considering contractor’s profile, which is based on protection of its brand and reputation in the market. In addition, sensitivity analysis is performed to verify priority ranking stability. Therefore, this research illustrates how AHP model could be implemented to help the decision-making process for selecting third-party services in logistics for perishable refrigerated goods effectively.     

基于AHP的灰色关联法在企业战略决策中的应用研究

针对企业战略决策中的战略方案选择定量化问题,建立拟选方案的评价指标体系。在此基础之上,把层次分析法的思想融入到灰色关联法之中,运用层次分析法确定评价指标的权值,以待选方案的关联度作为评价标准,建立战略决策模型。最后,结合实际案例,对模型的建立过程和步骤进行验证,并与层次分析法所得的结果进行比较,证明了模型的可行性和有效性,而且对多方案多指标的决策更能体现其客观性。     

基于变精度粗集的判断矩阵构造方法

判断矩阵的一致性条件,是用AHP法进行排序的必要条件。由于专家的主观性,判断矩阵一般不能满足一致性条件。本文利用变精度粗集的依赖度因子,给出了一种判断矩阵的构造方法。这种方法充分利用排序方案因素的原始信息,又综合了多专家的判断。     

考虑安全性的层次分析法

本文从决策的现实特点出发,提出了安全矩阵、风险矩阵、安全指数等一系列概念;并进一步给出了在运用决策方法(如:AHP等)时考虑安全性的具体方法。该方法(1)可表示、度量、计算、分析决策结果对安全性要求的具体程度;(2)可解决某些AHP无法直接解决的决策问题;(3)可使决策者对决策结果有重要的安全感。值得指出的是,本文给出了安全指数的解析表达式,并解决了式中参数的辩识问题,从而使本方法更具实用价值。     

个体客户全生命周期价值的模型和实证研究

从企业的角度出发把隐马尔可夫与动态规划技术有效地结合起来,对任意单个客户的终生价值的量化、决策以及优化进行了探讨和分析,提出了个体客户全生命周期价值动态模型,并对所提模型进行了验证。该模型能以通过观察到的客户购买决策序列作为动态最优化问题的解来进行参数评估,而且还能以用所产生的客户状态序列对客户进行动态的评价和分类,判断客户与企业所处关系阶段,从而为企业进行一对一的动态客户关系管理提供了一种定量的方法,并为公司实施最优的营销策略打下基础。     

PAHAP: A Pairwise Aggregated Hierarchical Analysis of Ratio-Scale Preferences

In this paper, we present a Pairwise Aggregated Hierarchical Analysis of Ratio-Scale Preferences (PAHAP), a new method for solving discrete alternative multicriteria decision problems. Following the Analytic Hierarchy Process (AHP), PAHAP uses pairwise preference judgments to assess the relative attractiveness of the alternatives. By first aggregating the pairwise judgment ratios of the alternatives across all criteria, and then synthesizing based on these aggregate measures, PAHAP determines overall ratio scale priorities and rankings of the alternatives which are not subject to rank reversal, provided that certain weak consistency requirements are satisfied. Hence, PAHAP can serve as a useful alternative to the original AHP if rank reversal is undesirable, for instance when the system is open and criterion scarcity does not affect the relative attractiveness of the alternatives. Moreover, the single matrix of pairwise aggregated ratings constructed in PAHAP provides useful insights into the decision maker's preference structure. PAHAP requires the same preference information as the original AHP (or, altematively, the same information as the Referenced AHP, if the criteria are compared based on average (total) value of the alternatives). As it is easier to implement and interpret than previously proposed variants of the conventional AHP which prevent rank reversal, PAHAP also appears attractive from a practitioner's viewpoint.     

Supply Networks as a Complex Adaptive System: Toward Simulation‐Based Theory Building on Evolutionary Decision Making

In this article, we examine how the firms embedded in supply networks engage in decision making over time. The supply networks as a complex adaptive system are simulated using cellular automata (CA) through a dynamic evolution of cooperation (i.e., “voice” decision) and defection (i.e., “exit” decision) among supply network agents (i.e., firms). Simple local rules of interaction among firms generate complex patterns of cooperation and defection decisions in the supply network. The incentive schemes underlying decision making are derived through different configurations of the payoff‐matrix based on the game theory argument. The prisoner's dilemma game allows capturing the localized decision‐making process by rational agents, and the CA model allows the self‐organizing outcome to emerge. By observing the evolution of decision making by cooperating and defecting agents, we offer testable propositions regarding relationship development and distributed nature of governance mechanisms for managing supply networks.     

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent‐Based Model Approach

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent‐based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss‐reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low‐probability/high‐impact risks.