Using the Analytic Hierarchy Process as a Two-phase Integrated Decision Approach for Large Nominal Groups

When decision makers who comprise a large nominal group face an unstructured decision problem and no simultaneous interactive communications are available, problem identification and consensus building are difficult, if not impossible. Few tools are available to assist decision makers in this situation. The Analytic Hierarchy Process (AHP) has typically been used to evaluate a set of alternatives after a decision problem has been structured as a hierarchy with various levels of criteria above the alternatives. With a group of decision makers, AHP has been used to evaluate those alternatives either by consensus building or by combining judgments or priorities using the geometric mean to aggregate their preferences. In this paper, we extend the use of AHP to a situation involving a large nominal group of dispersed decision makers where the entire hierarchy is not defined at the outset. In particular, we use the AHP as an integrative approach to identify the priorities of the various criteria and then use those priorities to screen and consolidate a large set of potential alternatives. This results in considering a reduced set of alternatives that will be affected by the more important criteria. The consolidated set of alternatives is evaluated by each individual in the group using AHP, combined using the geometric mean, and the results are synthesized to obtain the overall priorities of the alternatives. The approach is demonstrated and evaluated in a case study to select an alunmi anniversary gift to the U.S. Coast Guard Academy with a large nominal group of decision-makers dispersed throughout the United States.     

A Study on Aggregation of TOPSIS Ideal Solutions for Group Decision-Making

The technique for order preference by similarity to ideal solution (TOPSIS) has become a popular multi-criteria decision making (MCDM) technique, since it has a comprehensible theoretical structure and is able to provide an exact model for decision making. For the use of TOPSIS in group decisions, the common approaches in aggregating individual decision makers’ judgments are the geometric and the arithmetic mean methods, although these are too intuitive and do not consider either preference levels or preference priorities among alternatives for individual decision makers. In this paper, a TOPSIS group decision aggregation model is proposed in which the construction consists of three stages: (1) The weight differences are calculated first as the degrees of preferences among different alternatives for each decision maker; (2) The alternative priorities are then derived, and the highest one can be denoted as the degree to which a decision maker wants his most favorite alternative to be chosen; (3) The group ideal solutions approach in TOPSIS is used for the aggregation of similarities obtained from different decision makers. A comparative analysis is performed, and the proposed aggregation model seems to be more satisfactory than the traditional aggregation model for solving compromise-oriented decision problems.     

Group Aggregation Techniques for Analytic Hierarchy Process and Analytic Network Process: A Comparative Analysis

The analytic hierarchy process (AHP) and the analytic network process are important multiple criteria decision making methods for supporting complex, discrete strategic management decision problems. In order to exploit a broader information basis as well as to achieve a sufficient degree of objectivity strategic decision settings are mostly embedded into a multi-personal decision context to which different individuals with expert status contribute. Owing to the fact that there is a vast number of different methods and further internal possibilities (derivation of means) to aggregate the individual expert preferences to a group consensus, the first aim of this paper is to present a comprehensive literature review on various aggregation possibilities. The second aim is the conduction of a transparent comparative analysis of selected approaches and methods (geometric/arithmetic aggregation of individual judgments, geometric/arithmetic aggregation of individual priorities, geometric/arithmetic loss function approach and Group AHP model). Therefore, we use four different evaluation scenarios and point out under which assumptions which solution is suitable. Starting from these results, the aggregation techniques adequate to a specific decision context are provided.     

A Calibrated Group Decision Process

In practice most organisational decisions are made by groups that bring into the problem multiple perspectives, both complementary and contradictory. When having a group of decision makers, usually individuals’ preferences are either led to consensus or are aggregated with the use of some function like the median, the arithmetic or geometric mean. We focus in the second case, where individual’s preferences need to be aggregated. Our approach is based on the fact that when two decision makers are asked to give their preference between a pair of criteria using a specific scale, it is possible that they will give slightly different answers, even when they actually have the same opinion. This difference will not affect the case of a single decision maker, as it will be consistent throughout the whole process. However, it can affect a group decision when the values will be used as an input for the aggregation function. A novel approach is presented that enhances group decision making through a group calibration process. The proposed process adjusts individuals’ preferences based on their answers on a set of standardized questions prior to the aggregation phase. The method focuses The whole concept is applied to the group analytical network process method and it is illustrated through a telecommunications project case. The decision under examination concerns the selection of the right place for deploying a new telecom service of a multinational-based telecommunications company where a group of geographically dispersed decision makers form an ad-hoc virtual team in order to select the location for a new technical support centre.     

The Role of the DS/AHP in Identifying Inter-Group Alliances and Majority Rule Within Group Decision Making

DS/AHP is a nascent method of multi-criteria decision-making, based on the Dempster-Shafer theory of evidence and indirectly the Analytic Hierarchy Process. It is concerned with the identification of the levels of preference that decision makers have towards certain decision alternatives (DAs), through preference judgements made over a number of different criteria. The working result from a DS/AHP analysis is the body of evidence (BOE), which includes a series of mass values that represent the exact beliefs in the best DA(s) existing within certain subsets of DAs. This paper considers the role of DS/AHP as an aid to group decision-making, through the utilisation of a distance measure (between BOEs). Here, the distance measure enables the identification of the members of the decision-making group who are in most agreement, with respect to the judgements they have individually made. The utilisation of a single linkage dendrite approach to clustering elucidates an appropriate order to the aggregation of the judgements of the group members. This develops the DS/AHP method as a tool to identify inter-group alliances, as well as introduce a ‘majority rule’ approach to decision-making through consensus building.     

An Integrated Group Decision-Making Method Dealing with Fuzzy Preferences for Alternatives and Individual Judgments for Selection Criteria

Organizations often require decisions to be made by a group, and decision makers often have fuzzy preferences for alternatives and individual judgments when attempting to reach an optimal solution. In order to deal with the fuzziness of preference of decision makers, this paper proposes an integrated fuzzy group decision-making method. This method allows group members to express fuzzy preferences for alternatives and individual judgments for solution selection criteria. It also allowed for the weighting of group members. The method then aggregates these elements into a compromise group decision which is the most acceptable for the group as a whole. This method has been implemented and tested. An example is presented to illustrate the method.     

Multi-criteria Group Decision-Making Method Based on Intuitionistic Interval Fuzzy Information

For problems in multi-criteria group decision-making (MCGDM), this paper defines intuitionistic interval numbers, and the operational laws and comparison method of it. Some intuitionistic interval information aggregation operators are proposed, such as intuitionistic interval weighted arithmetic averaging operator, intuitionistic interval weighted geometric averaging operator, intuitionistic interval ordered weighted averaging operator, intuitionistic interval heavy averaging operator and intuitionistic interval aggregating operator. Then, based on intuitionistic interval fuzzy information, a method is developed to handle the problems in MCGDM. In this method, by applying the knowledge level of the experts to the decision making problem, the model of maximizing comprehensive membership coefficient is constructed to determine the weights of decision makers. By calculating the distances to the ideal and negative ideal solutions, the comprehensive attribute values and the rank of the alternatives can be obtained. Finally, an example is provided to demonstrate the feasibility and effectiveness of the proposed method.     

Characterization of the Row Geometric Mean Ranking with a Group Consensus Axiom

An axiomatic approach is applied to the problem of extracting a ranking of the alternatives from a pairwise comparison ratio matrix. The ordering induced by row geometric mean method is proved to be uniquely determined by three independent axioms, anonymity (independence of the labelling of alternatives), responsiveness (a kind of monotonicity property) and aggregation invariance, which requires the preservation of group consensus, that is, the pairwise ranking between two alternatives should remain unchanged if unanimous individual preferences are combined by geometric mean.     

Technology and Group Decision Process in Going-Concern Judgements

Accounting and auditing practices are continually being affected by advances in technology. This study empirically examined the effect of group decision processes and technological advances on group going-concern decision making. Groups with access to group decision support systems (GDSS) were compared to groups without access to GDSS for their going-concern judgments. The results show group discussion induced auditors to be more conservative and to consider factors which may have overlooked at the individual level, though neither structure significantly reduced the considerable variance in the individual going-concern judgments. Further, as compared to their counterparts in the face-to-face discussion groups, GDSS groups indicated much higher confidence in their group's final assessment of the client's going-concern status and a higher level of satisfaction and agreement with the group decision processes. The findings suggest that while group discussions did not significantly reduce auditors' considerable variance in going-concern judgments, future research should investigate which explicit models would improve the consensus on going-concern evaluations.     

Aggregation of Individual Preference Structures in Ahp-Group Decision Making

This paper presents a new procedure, to which we have given the name Aggregation of Individual Preference Structures (AIPS), whose objective is to deal with multiactor decision making when using Analytic Hierarchy Process (AHP) as the methodological support. This procedure incorporates ideas similar to Borda count methods and transfers to the case of preference structures the principle of aggregation employed in the two approaches traditionally followed in AHP-group decision making (aggregation of individual judgments and aggregation of individual priorities). The new aggregation method allows us to capture: (i) the richness of uncertainty inherent to human beings; (ii) the vision of each decision maker within the context of the problem; (iii) the interdependencies between the alternatives being compared and (iv) the intensities of the preferences that each decision maker gives to these interdependencies. From the preference structure distribution associated to each decision maker, this new approach (AIPS) provides the holistic importance of each alternative and ranking, as well as the most representative preference structure distribution for the group. The knowledge derived from these could be employed as an initial step in the search for consensus, which characterises the negotiation processes followed by the actors involved in the resolution of decisional problems. An earlier version of this paper was presented at the GDN2005 Conference held at Vienna. The work has been partially funded under Research Projects “Electronic Government. Internet-based Complex Decision Making: e-democracy and e-cognocracy” (Ref. PM2004-052) and “Internet-based Complex Decision Making. Decisional Tools for e-cognocracy” (Ref. TSI2005-02511).     

伦理问题、道德强度与供应商伦理管理

供应商的伦理问题涉及人权、环境、多样化、慈善与安全等方面,不同伦理问题的道德强度不同,企业决策者对供应商不同伦理问题的重视程度也不同。运用层次分析法,给出道德强度的结果严重度、社会共识、结果发生可能性、时间急迫性、接近性、结果集中度等六个维度的相对权重,根据道德强度各维度的相对重要性,对供应商不同的伦理权重进行排序。     

渠道成员选择评价体系及其优化方法研究

渠道成员选择是一个多目标决策问题,选择过程中由于评价指标包含了大量的不确定性和模糊性,若仅凭决策者的主观经验对此类问题评价则缺乏科学性。基于此,把层次分析法应用于营销渠道中的渠道成员选择上,从而为决策者正确地选择合适的渠道成员提供定量的技术分析依据,有着较好的科学性和合理性。     

Issue-Contingent Effects on Ethical Decision Making: A Cross-Cultural Comparison

This experiment examined the effects of three elements comprising Jones' (1991) moral intensity construct, (social consensus, personal proximity, and magnitude of consequences) in a cross-cultural comparison of ethical decision making within a human resource management (HRM) context. Results indicated social consensus had the most potent effect on judgments of moral concern and judgments of immorality. An analysis of American, Eastern European, and Indonesian responses also indicted socio-cultural differences were moderated by the type of HRM ethical issue. In addition, individual differences in personal ethical ideology (relativism and idealism) varied reliably with moral judgments after controlling for issue characteristics and socio-cultural background.     

利益相关者财务治理的一致性聚类分析

本文利用聚类分析方法研究利益相关者参与企业财务治理的决策机制,以融资决策为例,将内部融资、债务融资、股权融资三种不同的融资类型作为决策者判断的方案,不同类型融资的具体数值作为三角模糊数,考虑决策者的权重对决策者一致度计算的影响,计算不同决策者之间的一致度距离,进行决策者聚类,依据聚类的结果,计算一致性相同的决策者集合的最终方案集,最后通过实例演示了上述的计算过程。     

Deriving Weights from Interval Multiplicative Preference Relations in Group Decision Making

In this article, we investigate group decision making problems with interval multiplicative preference relations (including complete interval multiplicative preference relations and incomplete interval multiplicative preference relations). On the basis of the number of judgments and the consistency degree of each interval multiplicative preference relation, we first give a combined weighting method to derive the weights of decision makers. Then, we establish two linear programming models to derive the weight intervals of alternatives from all individual consistent interval multiplicative preference relations and utilize the continuous ordered weighted averaging operator or the continuous ordered weighted geometric operator to aggregate all the values in each weight interval. In addition, we establish a more general model to check the consistency of all individual interval multiplicative preference relations. In the cases where the optimal objective value of the model is not zero, we can get the optimal weights of alternatives directly, and then utilize these optimal weights and the optimal deviation values derived from the model to construct consistent interval multiplicative preference relations. Furthermore, we discuss some special cases of the established models and illustrate our models with a practical example.     

Geldpolitik aus Sicht der Bundesbank: auf dem Weg zu einem neuen Paradigma?

The ECB decision to cut its benchmark interest rate in November 2013 has been severely criticised in Germany. Against this background, the President of the Bundesbank justified the ECB’s monetary policy stance in recent speeches. At the same time, however, he argued that this stance carries risks and has adverse effects. By noting this, he leaves it open to interpretation whether a more restrictive stance would be appropriate even if inflation is well within the target range. If this interpretation were to be correct, it would indicate a deviation from elements of the pre-crisis consensus, namely that policy makers should aim at a clear target and should justify their measures in a consistent way.     

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.     

The Emergence of Individual Knowledge in a Group Setting: Mitigating Cognitive Fallacies

Research in psychology has found that subjects regularly exhibit a conjunction fallacy in probability judgments. Additional research has led to the finding of other fallacies in probability judgment, including disjunction and conditional fallacies. Such analyses of judgments are critical because of the substantial amount of probability judgment done in accounting, business and organizational settings. However, most previous research has been conducted in the environment of a single decision maker. Since business and other organizational environments also employ groups, it is important to determine the impact of groups on such cognitive fallacies. This paper finds that groups substantially mitigate the impact of probability judgment fallacies among the sample of subjects investigated. The key finding of this paper is the analysis of the apparent manner in which groups make such decisions. A statistical analysis, based on a binomial distribution, suggests that groups investigated here did not use consensus. Instead, if any one member of the group has correct knowledge about the probability relationships, then the group uses that knowledge and does not exhibit fallacy in probability judgment. Having a computational model of the group decision making process provides a basis for developing computational models that can be used to simulate “mirror worlds” of reality or model decision making in real world settings.     

Some Hesitant Fuzzy Aggregation Operators with Their Application in Group Decision Making

Hesitancy is the most common problem in decision making, for which hesitant fuzzy set can be considered as a suitable means allowing several possible degrees for an element to a set. In this paper, we study the aggregation of the hesitancy fuzzy information. Several series of aggregation operators are proposed and the connections of them are discussed. To reflect the correlation of the aggregation arguments, two methods are proposed to determine the aggregation weight vectors. Based on the support degrees among aggregation arguments, the weight vector of decision makers are obtained more objectively. To deal with the correlation of criteria, we apply the Choquet integral to get the weights of criteria. A method is also proposed for group decision making under hesitant fuzzy environment.     

Consensus Measure with Multi-stage Fluctuation Utility Based on China’s Urban Demolition Negotiation

Utility functions are often used to reflect decision makers’ (DMs’) preferences. They have the following two merits: one refers to the representation of the DM’s utility (satisfaction) level, the other one to the measuring of the consensus level in a negotiation process. Taking the background of China’s urban house demolition, a new kind of consensus model is established by using different types of multi-stage fluctuation utility functions, such as concave, convex, S-shaped, reversed S-shaped, reversed U-shaped as well as their combinations, to reveal negotiators’ dynamic physiological preferences and consensus level. Moreover, the effects of the decision-making budget and the individual compensation tolerance on the consensus level are also discussed in this paper. Compared with previous research, the proposed model takes both the negotiation cost and DM’s preference structure into consideration, and most importantly, it is computational less complex.