具过度自信零售商的双渠道供应链网络均衡研究

将零售商的过度自信行为纳入双渠道供应链网络均衡模型,研究了由供应商、分销商以及具过度自信行为的零售商构成双渠道供应链网络均衡问题。借助变分不等式以及互补理论,刻画了制造商、分销商以及过度自信零售商的最优行为,并构建了双渠道供应链网络均衡条件。解析分析了市场出现有利信息和不利信息两种情形下,零售商的过度自信行为对其订购决策的影响。最后,数值算例验证上述结论,并借助数值结果分析了零售商的过度自信行为对双渠道网络均衡的影响。     

基于做市商过度自信行为的市场均衡分析

针对做市商的过度自信行为对金融市场的影响,通过建立的数学模型对市场均衡时的价格波动、市场交易量、价格质量、市场深度以及市场参与者的利润做了相应的分析。结果表明:做市商的过度自信行为对市场的影响不同于以往研究中过度自信的信息交易者。在市场均衡时,做市商的过度自信行为使得市场交易量增大、市场深度增大、价格质量改善,同时价格波动降低,即做市商的过度自信行为提高了市场的流动性、稳定性与有效性。另外,市场中的信息交易者与噪音交易者都能从做市商的过度自信行为中获利,但同时过度自信行为会损害做市商的利益,影响其在市场中的地位。较小程度的过度自信不会使做市商退出市场,其对市场的影响得以维持;但当这种过度自信达到一定程度后,做市商就会退出市场。     

管理者过度自信对并购绩效的影响——基于群体决策视角的分析和实证

我国公司决策更多的是群体而非个体决策,群体决策强化还是弱化了过度自信偏差?本文从群体决策的层面研究了管理者的过度自信对公司并购绩效的影响。摈弃传统公司并购理论中的管理者理性假设,从行为公司金融理论出发,以我国422家上市发行A股的并购公司为样本进行了实证分析和研究。结果表明:群体决策中的管理者普遍存在着过度自信;管理者过度自信与并购长期绩效显著负相关;与短期绩效也负相关,但在统计上不显著。最后,根据分析结果提出了克服或减少管理者决策偏差行为的若干可行的举措。     

管理者过度自信行为下煤矿安全监管机制设计研究

针对我国煤矿安全监管的现状以及管理者的过度自信行为,建立了包括政府、煤矿企业以及过度自信的煤矿管理者的两阶段多任务委托代理模型,并从理论上分析了过度自信行为对煤矿管理者自身的安全管理投入、煤矿企业的激励参数、政府奖惩力度以及政府安全绩效的影响,并与煤矿管理者完全理性的情况对比。研究表明,煤矿管理者的安全管理投入、政府奖惩力度以及政府的安全绩效在过度自信程度增大时都会越来越偏离煤矿管理者完全理性时的情形,最后给出算例并验证了相关结论,为我国煤矿安全监管和实践提供了决策支持。     

整体视角下的投资者过度自信实证研究

过度自信是行为金融学中的一个重要假说。本文以证券市场整体为研究对象,采用可行的广义最小二乘法(FGLS)估计线性回归模型并结合格兰杰因果检验、指数自回归条件异方差模型(EGARCH)等对中国证券投资者过度自信情况进行实证研究。结果显示,中国投资者普遍存在着过度自信,且这种心理偏差对其投资行为产生了明显影响;与美国等成熟证券市场不同,中国投资者过度自信程度在牛市和熊市中并没有统计上的显著差别。     

离散事件系统静态稳定性的马氏决策过程方法

本文用马氏决策过程方法来讨论离散事件系统（DES）的静态稳定性问题,包括强吸引域和弱吸引域的计算,同时讨论了弱吸引域的稳定控制器的计算问题,所用方法不要求给定谓词的∑－（或∑u-）不变性和对环路的判别。     

信息不对称下具有过度自信零售商的供应链激励契约研究

在有过度自信零售商的分销供应链中,利用委托代理模型分别得出了信息对称及信息不对称时(努力程度无法监控)的最优特许经营费契约。探究了在两种情况下,零售商过度自信程度对其努力程度及制造商利润的影响。从比较中得知信息不对称下零售商的努力程度及制造商利润都小于信息对称下的情况,两种差别分别与零售商的过度自信程度成反比。零售商的过度自信行为有正面的信息价值,能减少信息不对称的影响;制造商偏爱过度自信程度较高的零售商。     

基于图模型理论有序偏好下的冲突反问题研究

在冲突谈判中,能获知对手偏好是掌握谈判主动性的重要条件。本文基于冲突分析图模型理论构建了一种获取对手偏好的方法。该方法通过深入分析冲突分析图模型中Nash、GMR和SEQ三种稳定性定义,利用反向思维,建立求解对手偏好最少约束条件的数学模型。该方法能让决策者在预知冲突结局的前提下,得到对手的全部偏好信息。以“云南曲靖陆良县铬污染”冲突事件为例,通过对该事件引发的冲突进行建模和偏好分析,在已知冲突最终结局的前提下,运用数学模型,省环保厅可以得到陆良化工企业的所有偏好序,使其在冲突谈判中做到知己知彼,同时也验证了该方法的可行性和有效性。案例分析过程可以从战略层面为谈判中的一方提供参考。     

多个过度自信零售商最优订货策略研究

研究在竞争环境下过度自信零售商对市场需求的信念存在偏差时的订货决策问题.在仅知市场需求的均值和支集的情况下,应用最大绝对后悔最小化准则,建立多个过度自信零售商的鲁棒订货模型.证明了具有多个零售商竞争的报童博弈的鲁棒优化Nash均衡解的存在性,并导出了最优决策的封闭表达式.讨论过度自信行为对零售商最优订货量和期望利润的影响.数值分析结果表明:在最小化最大绝对后悔值准则下,过度自信零售商获得的实际期望利润要低于其获得的信念期望利润;在两个零售商的非对称博弈情形,过度自信零售商获得的实际期望利润要高于完全理性零售商获得的期望利润,并且每个零售商获得的实际期望利润还随其竞争对手的过度自信程度的增加而增加.过度自信可以使那些在库存可用性上相互竞争的零售商获益.     

基于零售商过度自信的存货质押博弈决策模型

存货质押是中小企业短期融资的有效手段,而企业对需求的过度自信会影响融资企业和银行的决策,从而影响到企业和银行的预期收益。针对过度自信环境下的存货质押决策问题,建立过度自信零售商和银行的存货质押博弈决策模型,采用Stackelberg博弈分析期望需求和需求波动性两方面过度自信对零售商销售努力、订货量和银行质押率的影响。研究表明:过度自信零售商融资更为激进,过度自信程度越高,对资金需求越大,投入销售努力越高,采购量越大,预期利润与实际利润之间的偏差越大;在低利润市场环境下,质押率随着过度自信的增加而降低,在高利润市场环境下,质押率会随着预测精度过度自信的增加而增加,随着期望需求过度自信的增加而下降。     

Generalized metarationalities in the graph model for conflict resolution

A metarational tree is defined within the graph model for conflict resolution paradigm, providing a general framework within which rational behavior in models with two decision makers (DMs) can be described more comprehensively. A new definition of stability for a DM that depends on the total number, h, of moves and counter-moves allowed is proposed. Moreover, the metarational tree can be refined so that all moves must be unilateral improvements, resulting in a new set of stability definitions for each level of the tree. Relationships among stabilities at various levels of the basic and refined trees are explored, and connections are established to existing stability definitions including Nash stability, general metarationality, symmetric metarationality, sequential and limited-move stability, and policy equilibria.     

A fuzzy multi-criteria decision analysis model for advanced technology assessment at Kennedy Space Center

The rapid development of computer and information technology has made project evaluation and selection a difficult task at the Kennedy Space Center (KSC) Shuttle Project Engineering Office. Decision Makers (DMs) are required to consider a vast amount of intuitive and analytical information in the decision process. Fuzzy Euclid is a Multi-criteria Decision Analysis (MCDA) model that captures the DMs’ beliefs through a series of intuitive and analytical methods such as the analytic hierarchy process (AHP) and subjective probability estimation. A defuzzification method is used to obtain crisp values from the subjective judgments provided by multiple DMs. These crisp values are synthesized with Entropy and the theory of displaced ideal to assist the DMs in their selection process by plotting the alternative projects in a four-zone graph based on their Euclidean distance from the ‘ideal choice’.     

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

The paper develops a new intuitionistic fuzzy (IF) programming method to solve group decision making (GDM) problems with interval-valued fuzzy preference relations (IVFPRs). An IF programming problem is formulated to derive the priority weights of alternatives in the context of additive consistent IVFPR. In this problem, the additive consistent conditions are viewed as the IF constraints. Considering decision makers’ (DMs’) risk attitudes, three approaches, including the optimistic, pessimistic and neutral approaches, are proposed to solve the constructed IF programming problem. Subsequently, a new consensus index is defined to measure the similarity between DMs according to their individual IVFPRs. Thereby, DMs’ weights are objectively determined using the consensus index. Combining DMs’ weights with the IF program, a corresponding IF programming method is proposed for GDM with IVFPRs. An example of E-Commerce platform selection is analyzed to illustrate the feasibility and effectiveness of the proposed method. Finally, the IF programming method is further extended to the multiplicative consistent IVFPR.     

A new decision support model in multi-criteria decision making with intuitionistic fuzzy sets based on risk preferences and criteria reduction

In this paper, we propose a new model for decision support to address the ‘large decision table’ (eg, many criteria) challenge in intuitionistic fuzzy sets (IFSs) multi-criteria decision-making (MCDM) problems. This new model involves risk preferences of decision makers (DMs) based on the prospect theory and criteria reduction. First, we build three relationship models based on different types of DMs’ risk preferences. By building different discernibility matrices according to relationship models, we find useful criteria for IFS MCDM problems. Second, we propose a technique to obtain weights through discernibility matrix. Third, we also propose a new method to rank and select the most desirable choice(s) according to weighted combinatorial advantage values of alternatives. Finally, we use a realistic voting example to demonstrate the practicality and effectiveness of the proposed method and construct a new decision support model for IFS MCDM problems.     

Developing a straightforward approach for group decision making based on determining weights of decision makers

Group decision making is an active area of research within multiple attribute decision making. This paper assumes that all the decision makers (DMs) are not equally qualified to contribute equitably to the decision process. The aim of this paper is to develop an approach to determine weights of DMs, in which the decision information on alternatives with respect to attributes, provided by each DM, is represented in the form of interval data. We define the average of all individual decisions as the positive ideal decision (PID), and the maximum separation from PID as the negative ideal decision, which are characterized by a matrix, respectively. The weight of each DM is determined according to the Euclidean distances between the individual decision and ideal decisions. By using the obtained weights of DMs, all individual decisions are aggregated into a collective decision. Then the alternatives is ranked based on the collective decision. Meanwhile, this paper also gives a humanized decision method by using an optimistic coefficient, which is used in adjusting the relative importance between profit and risk. Finally, we give an example to illustrate the developed approach.     

An interactive method for the optimal selection problem with two decision makers

We develop in this paper an interactive approach for the bilateral optimal selection problem. The decision model involves two decision makers (DMs) observing a sequence of n offers, sequentially, one at a time, in order to choose a compromise offer. Our method is based on an aggregation of the individual expected utilities of the two DMs whenever a conflict occurs. A conflicting situation arises when the two DMs do not agree to choose the same decision. We develop and simulate our approach on different forms of utilities.     

An interactive sorting approach based on the assignment examples of multiple decision makers with different priorities

Although group decision-making is often adopted by many organizations in today??s highly complicated business environment, the multiple criteria sorting (MCS) problem in the context of group decision-making has not been studied sufficiently. To this end, we propose a new interactive method to assist a group of decision makers (DMs) with different priorities. With the goal of relieving the cognitive effort exerted by DMs, this method uses the assignment examples provided by the DMs to draw the parameters for the group preference model. In the iterative MCS process that we employ, the DMs are supported from two perspectives. When the assignment examples provided by the DMs are inconsistent, a RINCON algorithm is developed to identify all the possible solutions that the DMs can use to resolve the conflicts. When the examples are consistent, the potential and the fittest assignments of each alternative are deduced using linear programming techniques. These are then presented to the DMs to help them provide more information for the decision-making process. Furthermore, the priority of each DM is objectively and subjectively evaluated, and then progressively updated to reflect the decision-making performance of a DM at each iteration. Meanwhile, the priorities are integrated into the linear programming model to deduce the fittest assignment, as well as into the RINCON algorithm. Hence, the assignment examples of the DMs with higher priorities are emphasized in the fittest assignment, and are less likely to be revised for inconsistency. A practical example featuring MBA programs is also presented to demonstrate the proposed method.     

A soft multi-criteria decision analysis model with application to the European Union enlargement

This paper proposes a new multi-criteria decision analysis (MCDA) model that uses a series of existing intuitive and analytical methods to systematically capture both objective and subjective beliefs and preferences from a group of decision makers (DMs). A defuzzification method that combines entropy and the theory of displaced ideal synthesizes crisp values from the DMs’ subjective judgments. This approach assists the DMs in their selection process by plotting alternatives in a four quadrant graph and considering their Euclidean distance from the “ideal” choice. A pilot study illustrates the details of the proposed method. The DMs were a group of graduate students from the University of Paderborn in Germany. The pilot study concerned the addition of new members into the European Union (EU), a decision that has profound economic and political effects on both the entering and existing members of the Union. The DMs were required to consider a large number of internal strengths and weaknesses and external opportunities and threats in assessing the decision to enlarge the EU. Although the pilot study was not performed by actual DMs from the EU, it was an excellent platform for testing the proposed model.