An acyclic outranking model to support group decision making within organizations

A model to support group decision making within the board of any organization to select an alternative from a short list is proposed using a pairwise relation: consensus relation.This relation avoids elementary cyclicity which is a general shortcoming of previous models and satisfies transitivity under special conditions (weak transitivity). This relation is represented by a triangle-free graph and has important implications for Public Choice Theory such as the special relevance of the 2/3 majority rule and for Multicriteria Decision Making (MCDM) to improve outranking models.The proposed model can be easily applied as shown by the example presented.The contributions obtained from this model do not only include the selection of the recommended alternative(s) but also very useful representations and measures of the level of cultural consensus and dissent of the board members which can be used to improve their composition and behavior.     

A quantitative model for manpower decision making

Today's society is continually influenced by various changes, requiring managers to plan for manpower requirements. An approach that can be used by firms to solve one of the most pressing of today's employment problems is examined. In effect, the problem becomes one of determining an optimal work force composition based on both sociological and skill components. The problem is viewed as one of establishing rank ordered priorities among multiple conflicting manpower objectives. This study discusses some of the internal and external constraints faced by the firm and suggests a particular technique, goal programming, to facilitate the manpower decision-making process. The technique is examined under two different circumstances to provide some indication of the model's flexibility.     

群体决策过程中的群体思维研究

综述了群体决策过程中的一类非理性行为--群体思维的研究状况,评述了相关的研究文献.分别从群体思维的本质、前提条件、表现、对群体决策过程及结果的影响以及如何防范几个方面进行了探讨.最后提出一些待研究的方向和建议.     

A statistical framework for strategic decision making with AHP: Probability assessment and Bayesian revision

A probability assessment framework is outlined for an organizational decision involving a conditioning event (CE). The decision may, for example, involve a new-product launch (strategic decision) dependent on the outcome of market research (CE). The framework illustrates how Bayesian revision could be employed as related “news” arrives intermittently to revise current probabilities prior to decision implementation. A unique contribution of this paper is its utilization of the analytic hierarchy process to ascertain a set of consistent and coherent probabilities for the event/sample spaces at all stages of the decision process.     

二分群体决策规则的序性质研究

Karotkin等发现二分群体决策的加权多数决策规则集具有序性质,但未能解释其原因.文章提出了规则链和规则距离函数的概念,指出当一组决策规则构成规则链时这组规则便具有序性质,从而解释了这一现象.而判断一组规则是否构成规则链则可以通过计算各规则间的规则距离来实现.随后通过对具体实例的分析进一步阐述了得到的结论.     

On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective

This paper focuses on qualitative multi-attribute group decision making (MAGDM) with linguistic information in terms of single linguistic terms and/or flexible linguistic expressions. To do so, we propose a new linguistic decision rule based on the concepts of random preference and stochastic dominance, by a probability based interpretation of weight information. The importance weights and the concept of fuzzy majority are incorporated into both the multi-attribute and collective decision rule by the so-called weighted ordered weighted averaging operator with the input parameters expressed as probability distributions over a linguistic term set. Moreover, a probability based method is proposed to measure the consensus degree between individual and collective overall random preferences based on the concept of stochastic dominance, which also takes both the importance weights and the fuzzy majority into account. As such, our proposed approaches are based on the ordinal semantics of linguistic terms and voting statistics. By this, on one hand, the strict constraint of the uniform linguistic term set in linguistic decision making can be released; on the other hand, the difference and variation of individual opinions can be captured. The proposed approaches can deal with qualitative MAGDM with single linguistic terms and flexible linguistic expressions. Two application examples taken from the literature are used to illuminate the proposed techniques by comparisons with existing studies. The results show that our proposed approaches are comparable with existing studies.     

Ethical decision making: A cross-cultural comparison

The purpose of this study is to compare the ethical decision making of respondents from two different cultures. Perceived organizational support for ethical decision making was also compared. The samples include residents of South Florida, United States of America and Jamaica, West Indies. Respondents were employed full time. Results indicate that for the majority of business dilemmas presented, no significant differences were found. Implications for these findings are discussed.     

DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making

This paper develops a comprehensive algorithm for multi-expert multi-criteria decision making problems considering quantitative and qualitative criteria in forms of benefit, cost or target types. We focus on using probabilistic linguistic term sets to express the qualitative evaluations due to their excellence in expressing complex individual and collective linguistic assessments. Firstly, we develop a target-based linear normalization technique and a target-based vector normalization technique. A weight adjustment method is proposed to achieve the tradeoff between criteria after normalization. Given that the two target-based normalization techniques have different advantages, we then propose a ranking method, which consists three subordinate models, based on these two target-based normalization approaches and three aggregation techniques. Reliable results of a multi-expert multi-criteria decision making problem are determined by integrating the subordinate utility values and the ranks of alternatives. The proposed method is implemented to solve the green enterprise ranking problems and the excavation scheme selection problem for shallow buried tunnels, respectively. The advantages of the proposed method are emphasized through comparative analyses with other ranking methods.     

GDSS的基本决策网络模型

为构建 GDSS决策网络引入一个分析模型——决策网络图来研究任务环境和组织设计之间的交互作用 ,提出 GDSS的基本决策网络结构为级联式和二层多分支树型结构 ,借助概率影响图对该决策网络的优化问题进行了形式描述 ,并给出协同工作方式的分类和任务环境的分析步骤 .     

A multicriteria decision making model for reverse logistics using analytical hierarchy process

Product recovery activities such as recycling, refurbishing and direct reuse are becoming integral to manufacturing supply chains. This study presents a multicriteria decision making model for reverse logistics using analytical hierarchy process (AHP). The AHP model evaluates a hierarchy of criteria and subcriteria, including costs and business relations, for critical decisions regarding network design. Using sensitivity analysis with AHP, the work provides insights into the preference ordering among eight alternative network configurations. For instance, the choice of test sites is largely dependent on the potential for cost savings on testing procedures and transportation of scrap, and this decision is not sensitive to the importance of business relations. By contrast, the choice of collection sites is largely determined by the relative importance of business relations considerations vs. cost considerations. As well, the processing location decision favors a third-party reprocessor if there is little need to protect proprietary product knowledge and cost savings is very important. The model is demonstrated using three case studies of real-world applications.     

基于双平台协调的两层群决策方法

为解决现有研究未考虑决策者的认知判断参考点与风险偏好态度对现实决策选择行为影响的问题,首先基于前景理论和T -JM矩阵构建了用于提取主观决策信息的价值平台与风险平台,然后针对上下两层知识在两个平台上的分布性特征给出并分析了两层双平台协调决策结构及运行机理,最后从上下两层满意协调度最优化的视角提出了能够有效提取两层决策信...     

一种基于模糊推理的多目标柔性决策方法

在目前多目标决策研究的基础上 ,提出了基于模糊推理的目标函数集成方法 ,该方法避免了一般的目标函数集成方法特定函数形式的局限性 ,而直接基于决策者对目标偏好的知识结构 ,用模糊规则来表达 .实际上 ,基于模糊推理的目标函数集成方法对应于连续变化权值的算术加权平均集成 .该目标集成方法不仅与决策者的实际决策过程更加接近 ,而且由于模糊推理的通用逼近特性 ,可以表达一般的目标函数集成方法不能表示的决策偏好结构     

Information processing in managerial decision making: A preliminary study

This paper reports the preliminary findings of an exploratory investigation into information processing in a managerial context. The vehicle for testing several research objectives was a laboratory decision-making experiment in which subjects purchased information items and evaluated a set of organizational goals. The methodology included multidimensional statistical methods that hold promise for dealing with the complexity of problems in implementing managerial decision models. Within a specific information-decision scenario, the statistical evidence favorably supports the existence of individual differences in information perception and information selection, and the use of goal preference hierarchies as predictors of information preferences.     

基于二元语义信息处理的一种语言群决策方法

针对解决具有语言评价信息的多指标群决策问题,提出了一种基于二元语义信息处理的 群决策方法. 该方法是采用近年来最新发展的二元语义概念对语言评价信息进行处理和运算, 它是依据传统理想点法的基本思想,通过计算每个方案与正、负理想点间的语义距离,最终确 定最优方案,使该方案最贴近正理想点和最远离负理想点. 该方法具有对语言信息处理较为精 确的特点,避免了以往采用的语言信息处理方法所带来的信息扭曲和损失. 最后给出了一个 算例.     

Multi-attribute utility methods in group decision making: Past applications and potential for inclusion in GDSS

This paper reviews a variety of studies in which multi-attribute utility theory (MAU) has been used successfully to aid group decision processes and discusses the incorporation of MAU in Group Decision Support Systems (GDSS). GDSS of various levels of automation have been proposed to aid group decision making. A number of commercial GDSSs are available which are capable of aiding generation of alternatives, their evaluation, and selection. Many authors have promoted the incorporation of quantitative decision making models in GDSS. The most appropriate quantitative tool for GDSS is MAU, but MAU has rarely been utilized. The cases reviewed illustrate that the use of MAU techniques is not prohibitively difficult or complex.     

Computing an effective decision making group of a society using social network analysis

Recent years have witnessed how much a decision making group can be dysfunctional due to the extreme hyperpartisanship. While partisanship is crucial for the representatives to pursue the wishes of those whom they represent for, such an extremism results in a severe gridlock in the decision making progress, and makes themselves highly inefficient. It is known that such a problem can be mitigated by having negotiators in the group. This paper investigates the potential of social network analysis techniques to choose an effective leadership group of a society such that it suffers less from the extreme hyperpartisanship. We establish three essential requirements for an effective representative group, namely Influenceability, Partisanship, and Bipartisanship. Then, we formulate the problem of finding a minimum size representative group satisfying the three requirements as the minimum connected \(k\) -core dominating set problem (MC \(k\) CDSP), and show its NP-hardness. We introduce an extension of MC \(k\) CDSP, namely MC \(k\) CDSP-C, which assumes the society has a number of sub-communities and requires at least one representative from each sub-community should be in the leadership. We also propose an approximation algorithm for a subclass of MC \(k\) CDSP with \(k=2\) , and show an \(\alpha \) -approximation algorithm of MC \(k\) CDSP can be used to obtain an \(\alpha \) -approximation algorithm of MC \(k\) CDSP-SC.     

Informed decision making: the new paradigm

Health care cannot survive in its present form. It is becoming unaffordable for a large share of the country's population. Its quality and effectiveness inexplicably vary between communities and across time. With all these problems, the process of health care can be understood. All that are needed are good, basic data; its access, management, and analysis; and then presentation of facts and observations. Together, these functions describe the translation of data into information--the field of medical informatics. Information about such management concerns as clinical efficiency (which largely is related to appropriateness and cost-effectiveness) and about the realities of day-to-day medical practice can be used to improve the value of health care. Informed decision making is based solely on confidence that, given the right information and understanding, we can all make the right decisions. The right decisions mean better patient acceptance and satisfaction, a sense of value enhancement by payers, and support of the Hippocratic tradition.     

A framework of decision making for technological change

The first article in this series2 drew a distinction between the costs of line operations- or current outputs—and those costs devoted to investment, or future outputs. As investment encompasses technological change—in practice it is dominated by it—this article examines some of the broader issues underlying decisions to invest and describes in outline a study being made of the economic criteria that are relevant to such decisions. In the longer term the objective is to develop a procedure or framework of criteria to assist the process of decision making; and this would include a frame of reference—a set of statistical time-series and analyses designed for the purpose.     

复杂决策问题的多元化模型体系研究

鉴于复杂决策问题的特点,仅仅依靠定量模型难以描述和求解复杂决策问题. 从定性到 定量综合集成角度出发,认为复杂决策问题的求解过程需要多元化模型支持. 依据复杂决策问 题的认知层次,提出复杂决策问题的多元化模型体系中包含概念模型、结构模型和数学模型, 并对这三类模型进行了论述.