基于指标优先度的多属性群决策方法研究

在研究互反矩阵的基础上给出了指标优先度的定义,并且在理想点,相对贴近度的角度给出了模糊群决策的方法,此方法简单实用。最后给出了一个实例论证了它的可行性和实用性。     

模糊多属性决策法在配送中心选址中的应用

依据配送中心选址的主要因素,从基础设施、自然环境、社会效益、费用以及服务水平等几个方面建立多级评判指标体系,并提供两种模糊多属性决策法对备选配送中心进行优选和排序。最后一个算例方法客观反映实际情况,具有可行性。     

多属性决策方法研究综述

在理论研究方面,多属性决策自从其诞生以来就一直是学术界关注的研究课题.本文总结了多属性决策方法的国内外研究现状,分析了多属性决策方法的研究热点,并对多属性决策方法的未来研究提出展望.     

关于“基于可能度的区间数排序的一种新方法”的注记

首先纠正了有关错误，在此基础上对区间数简易排序方法进行了讨论，给出区间数排序的一些更简易新方法，并以简单例子对方法的使用进行了注记。     

权重与属性值均为区间数的多属性VIKOR决策方法分析

针对决策者给出的权重值和属性值均为区间数的多属性决策问题,提出VIKOR决策方法,该方法运用线性规划确定群体效益值与个别遗憾度区间,然后得到备选方案的折衷值也用区间数表达,基于折衷值的分布函数对折衷值进行两两比较,建立了可能度矩阵-模糊互补判断矩阵,据此对方案进行排序。最后以一个算例说明该方法的可操作性。     

关于“基于可能度的区间数排序的一种新方法”的注记

首先纠正了有关错误,在此基础上对区间数简易排序方法进行了讨论,给出区间数排序的一些更简易新方法,并以简单例子对方法的使用进行了注记。     

基于模糊决策的多属性在线拍卖决策算法

通过对现有应用模糊数学的方法来解决多属性在线拍卖中决定胜出者的方法进行分析后,发现其存在两个问题,一是原计算方法存在简化空间,二是方法本身涉及到模糊指标值和模糊权重的直接加权,导致了模糊元素的非线性化和计算的复杂化。本文针对第一个问题提出计算步骤简化意见,进而又针对第二个问题提出一种新的模糊决策算法。新算法避免了直接对模糊指标值进行加权,从而保持了模糊元素的线性性质,简化了模糊决策计算过程,优化了现有多属性拍卖中用到的模糊决策算法,丰富和完善了拍卖问题涉及模糊环境时采用模糊数学求解的算法。     

基于联系数的三角模糊数多属性决策新模型

针对属性值和属性权重都用三角模糊数表示的多属性决策问题,提出了一种基于联系数的三角模糊数多属性决策评价模型.通过运用集对分析的不确定性系统理论,利用三角模糊数的中值及上下确界所限定的取值区间,将三角模糊数转化为联系数,建立了联系数决策模型,并给出决策步骤,基于此可以对多属性决策评价问题进行排序.该模型的建立既考虑了三角模糊数的中值,又兼顾了三角模糊数的上下确界,即联系数的差异度,更具有客观性.通过对实例的运用和分析表明,该方法算理清晰,计算简便,结论合理.     

基于信息熵多属性决策的投资评价研究

随着社会经济的发展,投资商有越来越多的机会进行投资,但如果对投资目标评价不准确,盲目投资,会造成投资利润无法收回,因此投资商在选择企业进行投资时,应该对企业进行正确的评价,本文研究了基于信息熵的多属性决策方法,将其应用于选择企业进行投资的评价中,实验证明,该方法是切实有效的。     

权重未知的直觉区间模糊多准则决策方法

从两个方面推导准则权重的求解方法,用多目标的思想处理准则权重赋值问题,以估计缺失权重。同时给出直觉区间数的运算规则和记分函数,提出准则权重未知的直觉区间模糊多准则决策方法。     

模糊群决策方法在中间商选择中的应用研究

企业在选择中间商时往往面临着候选伙伴评价指标信息获取的困难,为了使决策科学合理,采用群决策方法集成各领域不同专家的信息,通过语言变量把专家的主观判断转化为对应模糊数,建立相应的数学模型,并计算出用模糊数表示的候选者综合评价值。     

Information Collection Strategic Design in Experts-assisted Decision Making Paradigm

In an experts-assisted decision making paradigm, the information collection design becomes a strategic variable under a weak assumption that the final decision is dependent on the design used to collect information as well. As a result, the same information of the experts and the decision maker about the problem can potentially produce different final decisions for different information collection designs. The implication is that a decision maker can strategically select a design which serves his/her objective. This paper uses a Bayesian estimation methodology for combining experts' information with the decision maker's prior. An information collection process is designed by setting constraints on this model. Several designs are developed here using such controlled factors as a one-stage versus a two-stage decision process, experts' rank ordering, and group versus individual lobbying/consultation. An example is provided to illustrate the applicability of the concept. It is shown that the information produced in the process of producing a decision can also give insights into the impacts of the decision maker and the experts on the decision.     

金融发展与企业家创业决策

分析金融机构监督成本与企业家创业之间的联系。在各企业家具备同样的融资能力的情况下,由于全融机构的监督成本不同,将出现不同的决策。在高监督成本下,只有一部分潜在企业家选择创业,全融机构为这些企业家提供较少的融资;在低监督成本下,将有更多的潜在企业家选择创业,并能获得较多的融资。     

High Stakes Decision Making: Normative,Descriptive and Prescriptive Considerations

This paper reviews the state of the art of research on individual decision-making in high-stakes, low-probability settings. A central theme is that resolving high-stakes decisions optimally poses a formidable challenge not only to naïve decision makers, but also to users of more sophisticated tools, such as decision analysis. Such decisions are difficult to make because precise information about probabilities is not available, and the dynamics of the decision are complex. When faced with such problems, naïve decision-makers fall prey to a wide range of potentially harmful biases, such as failing to recognize a high-stakes problem, ignoring the information about probabilities that does exist, and responding to complexity by accepting the status quo. A proposed agenda for future research focuses on how the process and outcomes of high-stakes decision making might be improved.     

Applying Multiattribute-Based Group Decision Making Techniques in Complex Equipment Selection Tasks

A practicing industrial engineer, even an experienced decision maker, needs help in the sense that there is a necessity to use more logical or analytical decision support tools, especially when dealing with control and instrumentation projects which are often worth millions of dollars. In this article we propose an algorithm which can support the process of group decision making relating to industrial automation, especially involving the selection of control and instrumentation equipment. The aim of this article is to look only at the algorithm's application and how it is applied. To this end, two test cases are used as examples: (1) selecting a local area network for installation in an academic environment; and (2) selecting an integrated control system for a real-world pulp and paper mill. Obtained results show that the algorithm leads to a satisfactory solution. A software form of the algorithm is being programmed for use as a decision support tool.     

Challenging Group Support Systems Research: The Case for Strategic Decision Making

Strategic decision making (SDM) often occurs in groups that can benefit from the use of group support systems (GSS). However, no comprehensive review of this logical intersection has been made. We explore this intersection by viewing GSS research through the lens of SDM. First, SDM is broadly characterized and a model of GSS-mediated SDM is produced. Second, we review empirical GSS research linking these findings to the characteristics of SDM. We conclude that GSS research has not produced sufficient knowledge about group history, heterogeneity, member experience, task type, time pressure, technology or tool effects, and decision consensus for a favorable evaluation of SDM in GSS groups. SDM in GSS groups challenges researchers to study the effects of group processes such as those just mentioned in a context that involves ongoing and established groups, political activity, and a multiplicity of tasks.     

Simple Decision Aids and Consumer Decision Making

To help consumers deal with increasing amounts of information, many online retailers offer simple decision aids, such as the ability to sort on a particular attribute or eliminate undesired alternatives. The authors propose that consumers use simple decision aids as substitutes for cognitive effort, potentially with adverse consequences for decision making. An experimental study shows that providing unrestricted sorting increases decision quality only when choice conflict is low; beyond a certain point, greater use of the decision aid is associated with declines in decision quality. A second study shows that that allowing consumers to sort alternatives only one time enhances decision quality and, when choice conflict is high, reduces decision effort. A third study shows that providing elimination as well as sorting tools helps mitigate the negative effects of simple decision aids. Although the availability of sorting alone hurts decision quality when choice conflict is high, decision quality under choice conflict is improved when both sorting and elimination tools are provided. Implications for retail practice are discussed.     

Multiple Criteria Decision Making Models in Group Decision Support

Use of multiple criteria decision making (MCDM) models to aid the group decision process was tested. Two multiple criteria group decision support systems (MCGDSS) were studied, one using the AHP/Tchebycheff method of Iz and the other using Kersten's NEGO system. These systems were compared with a commercial GDSS, VisionQuest. VisionQuest does not include multiple criteria tools. To make the study comparable, VisionQuest was augmented with an ad hoc linear programming model that could generate solutions with specified characteristics requested by the using group. The three systems were compared on the dimensions of solution quality and decision support effectiveness.One of the hypotheses was that MCDM models would force participants to examine criteria, preferences, and aspirations more thoroughly, thus leading to decisions of better quality. Subjects using the MCGDSSs were expected to have higher mean quality and effectiveness values. However, the quality and effectiveness values of the VisionQuest/ad hoc system were found to be better on the dimension of effectiveness. Explanations for this result are included in the paper.Another hypothesis was that the AHP/Tchebycheff method of Iz, a value-oriented system, would yield more effective group support than the goal-oriented NEGO system. However, the NEGO system was found to yield solutions with better quality measures than the solutions obtained with the AHP/Tchebycheff system.Observation of the groups using the MCDM systems indicate that both the AHP/Tchebycheff and NEGO methods can be revised to enhance their effectiveness. The primary difficulty encountered with the AHP/Tchebycheff method was in the large number of pairwise comparisons required by AHP. The NEGO method can be enhanced by including specification of desired attainment levels in the first stage of the method. Both MCDM techniques have potential to benefit group decision support by giving using groups a means to design better solutions.     

Personal Values’ Influence on the Ethical Dimension of Decision Making

Personal values have long been associated with individual decision behavior. The role played by personal values in decision making within an organization is less clear. Past research has found that managers tend to respond to ethical dilemmas situationally. This study examines the relationship between personal values and the ethical dimension of decision making using Partial Least Squares (PLS) analysis. The study examines personal values as they relate to five types of ethical dilemmas. We found a significant positive contribution of altruistic values to ethical decision making and a significant negative contribution of self-enhancement values to ethical decision making. Dr. David J. Fritzsche is a retired Professor of Management and Organization at The Pennsylvania State University, Great Valley. Among the numerous journals in which he published are Journal of Business Ethics, Academy of Management Journal, Journal of Macromarketing, and Simulation & Games. He is the co-author of the Business Policy Game: A Strategic Management Simulation. He authoured the book Business Ethics: A Global and Managerial Perspective (McGraw-Hill, 1997). Dr. Effy Oz is a Professor of Management Science and Information Systems at The Pennsylvania State University, Great Valley, where he teaches courses on IT management, ethical issues in IT, and business-stakeholder relations. He has authored several textbooks including five editions of Management Information Systems (Course Technology Inc., 1998–2006), Foundations of E-Commerce (Prentice-Hall, 2002) and, Ethics for the Information Age (McGraw-Hill, 1994), and a practitioner’s book (The Manager’s Bible, Ivy League Publishing, 1998). He has also published research articles in academic and professional journals, among which are MIS Quarterly, Communications of the ACM, Information & Management, Decisions Sciences, OMEGA, Journal of Business Ethics, and Journal of Computer Information Systems. Dr. Oz is a member of the editorial boards of Encyclopaedia of Information Systems, Information & Management, and Journal of Global Information Technology Management. He is a frequent speaker at IT conferences, has conducted research on a number of IT topics, and has been quoted in numerous media including Computerworld, MSNBC, and the Los Angeles Times. He was awarded the 1997 Notable Contribution to the Information Systems Literature Award by the Information Systems Section of the American Accounting Association, the 1999-2000 Distinguished Faculty Research Award at Penn State Great Valley, and Best Paper Award at the Annual Global Information Technology Conference of 2004.     

An Interactive Approach to Multiple Attribute Group Decision Making with Multigranular Uncertain Linguistic Information

The multiple attribute group decision making (MAGDM) problems having multiple sources of uncertain linguistic information assessed in different linguistic label sets are investigated. The existing linguistic labels in a linguistic label set are uniformly and symmetrically distributed, but in many real-life situations, the unbalanced linguistic information appears due to the nature of the linguistic variables used in the problems (Herrera and Herrera-Viedma, Proceedings of 4th international workshop on preferences and decisions, Trento, Italy, 2003). In this paper, we first define some unbalanced linguistic label sets, and then develop some transformation functions to unify the given multigranular linguistic labels in a unique linguistic label set without loss of information. Moreover, we utilize the uncertain linguistic weighted averaging operator to aggregate all individual uncertain linguistic decision matrices into a collective one, and define two similarity measures, one for measuring the similarity degree between each pair of uncertain linguistic variables, and the other for checking the consensus degrees among the individual uncertain linguistic decision matrices and the collective uncertain linguistic decision matrix. Finally, we develop an interactive approach to MAGDM with multigranular uncertain linguistic information and illustrate the developed approach with an application example.