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.     

Group Decision and Negotiation in Strategy Making

For a large number of organisations effective delivery of strategy depends upon the psychological and emotional commitment of the Top Management Team (TMT) thus involving group negotiation and decision making. Computer based group support promoting open debate and developing commitment is therefore important and illustrated through examples from the presenter's large number of strategic interventions.     

Ethical Decision Making: A Comparison of Computer- Supported and Face-to-face Group

This study compares computer-supported groups, i.e., groups using group support systems (GSS), and face-to-face groups using ethical decision-making tasks. A laboratory experiment was conducted using five-person groups of information systems professionals. Face-to-face (FTF) and GSS groups were compared in terms of their decision outcomes and group members' reactions. The results revealed that computer-supported and face-to-face groups showed no significant difference in terms of the decision outcomes of choice shift and decision polarity. However, FTF groups reached their decisions more quickly and they were more successful in attaining group consensus than GSS groups. Subjects evaluated face-to-face communication more favorably than GSS interaction on most post-group measures related to perceived group processes and satisfaction. Despite these outcomes, some possibilities for using GSS technology in an ethical decision making context are examined.     

Menu Dependence and Group Decision Making

This paper is concerned with the problem of group decision making. We introduce the notion of a collective system rule. A collective system rule maps each preference profile to a group-preference system, which is a collection of social preferences on the subsets of the alternatives. By formulating the Arrovian conditions, we show the Arrow-type impossibility theorems. We also discuss how our approach is related to the standard group decision-making process.     

A Sorting Model for Group Decision Making: A Case Study of Water Losses in Brazil

Many water supply systems in Brazil have serious problems related to the high index of water losses, which provokes financial and environmental impacts. This is an immediate consequence of an inadequate maintenance plan, allied to natural and budgetary constraints. In addition, in these types of problems it is commonplace to consider the opinions of many managers, such as those from the operational, environmental and financial sectors of Water Companies. In view of this, a sorting multicriteria model to support group decision making is developed. We proposed an approach which sorts the areas of the system which are located in critical zones of water losses into categories, and which takes into account different points of view and considers uncertainty in criteria weights by using only ordinal information, so as to make it viable to manage the maintenance plan and to use the scant financial resources more efficiently. The SMAA-TRI method is used to tackle the group sorting problematic by categorizing the network into zones where losses are intense and thus to focus the managers’ effort on the most critical regions. A case study in Brazil is presented to demonstrate the efficiency of the approach proposed.     

A Deviation-Based Approach to Intuitionistic Fuzzy Multiple Attribute Group Decision Making

The aim of this article is to investigate the approach to multiple attribute group decision making (MAGDM) with intuitionistic fuzzy information. We first introduce a deviation measure between two intuitionistic fuzzy numbers, and then utilize the intuitionistic fuzzy hybrid aggregation operator to aggregate all individual intuitionistic fuzzy decision matrices into a collective intuitionistic fuzzy decision matrix. Based on the deviation measure, we develop an optimization model by which a straightforward formula for deriving attribute weights can be obtained. Furthermore, based on the intuitionistic fuzzy weighted averaging operator and information theory, we utilize the score function and accuracy function to give an approach to ranking the given alternatives and then selecting the most desirable one(s). In addition, we extend the above results to MAGDM with interval-valued intuitionistic fuzzy information.     

AHP-Group Decision Making: A Bayesian Approach Based on Mixtures for Group Pattern Identification

This paper proposes a Bayesian estimation procedure to determine the priorities of the Analytic Hierarchy Process (AHP) in group decision making when there are a large number of actors and a prior consensus among them is not required. Using a hierarchical Bayesian approach based on mixtures to describe the prior distribution of the priorities in the multiplicative model traditionally used in the stochastic AHP, this methodology allows us to identify homogeneous groups of actors with different patterns of behaviour for the rankings of priorities. The proposed procedure consists of a two-step estimation algorithm: the first step carries out a global exploration of the model space by using birth and death processes, the second concerns a local exploration by means of Gibbs sampling. The methodology has been illustrated by the analysis of a case study adapted from a real experiment on e-democracy developed for the City Council of Zaragoza (Spain). Partially funded under the research project Electronic Government. Internet-based Complex Decision Making: e-democracy and e-cognocracy (Ref. PM2004-052) approved by the Regional Government of Aragon (Spain) as part of the multi-disciplinary projects programme.     

Multi-criteria Group Decision Making with Various Ordinal Assessments

Group Decision and Negotiation - This paper proposes a method for addressing multi-criteria group decision making (MCGDM) problems with various types of ordinal assessments. In addition to two...     

Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making

This paper describes a group decision support system based on an additive multi-attribute utility model for identifying a consensus strategy in group decision-making problems where several decision-makers or groups of decision-makers elicit their own preferences separately. On the one hand, the system provides procedures to quantify the DMs or group of DMs preferences separately. This involves assessing the DMs or group of DMs component utilities that represent their preferences regarding the respective possible attribute values and objective weights that represent the relative importance of the criteria. On the other hand, we propose Monte Carlo simulation techniques for identifying a consensus strategy. An iterative process will be carried out, where, after the simulations have been performed, the imprecise component utilities and weights corresponding to the different DMs or groups of DMs are tightened to output more meaningful information in the next simulations to achieve a consensus strategy. Finally, an application to the evaluation of remedial strategies for restoring contaminated aquatic ecosystems illustrates the usefulness and flexibility of this decision support tool.     

A Framework for Adopting Collaboration 2.0 Tools for Virtual Group Decision Making

Decision making in virtual teams is gaining momentum due to globalization, mobility of employees, and the need for collective and rapid decision making by members who are in different locations. These factors resulted in a proliferation of virtual team software support tools for decision making, the latest of which is social software (also known as collaboration 2.0), which includes tools such as wikis, blogs, microblogs, discussion forums, and social networking platforms. This paper describes the potential use of collaboration 2.0 software for improving the process and the specific tasks in virtual group decision making. The paper proposes a framework for exploring the fitness between social software and the major activities in the group decision making process and how such tools can be successfully adopted. Specifically, we use a fit-viability model to help assessing whether social software fit a decision task and what organizational factors are important for such tools to be effective. Representative research issues related to the use of such tools are also presented.     

A Fuzzy Multi-Criteria Decision Making Model for IS Student Group Project Assessment

To accommodate the criterion-referenced student group project assessment approach, this paper proposes a fuzzy group Multi-Criteria Decision Making (MCDM) model. The proposed model can be used to solve student group project assessment problem in particular and generic MCDM problems in general, where the criteria used are often different and can be scored with multiple preference formats. The proposed fuzzy group MCDM model supports seven different preference formats, including preference ordering, utility vector, linguistic term vector, selected subset, fuzzy selected subset, fuzzy preference relation, and normal preference relation. It has been firstly used in the context of Information Systems (IS) student group project assessment.     

Group Decision Making with Dispersion in the Analytic Hierarchy Process

With group judgments in the context of the Analytic Hierarchy Process (AHP) one would hope for broad consensus among the decision makers. However, in practice this will not always be the case, and significant dispersion may exist among the judgments. Too much dispersion violates the principle of Pareto Optimality at the comparison level and/or matrix level, and if this happens, then the group may be homogenous in some comparisons and heterogeneous in others. The question then arises as to what would be an appropriate aggregation scheme when a consensus cannot be reached and the decision makers are either unwilling or unable to revise their judgments. In particular, the traditional aggregation via the geometric mean has been shown to be inappropriate in such situations. In this paper, we propose a new method for aggregating judgments when the raw geometric mean cannot be used. Our work is motivated by a supply chain problem of managing spare parts in the nuclear power generation sector and can be applied whenever the AHP is used with judgments from multiple decision makers. The method makes use of principal components analysis (PCA) to combine the judgments into one aggregated value for each pairwise comparison. We show that this approach is equivalent to using a weighted geometric mean with the weights obtained from the PCA.     

Compatibility Analysis of Intuitionistic Fuzzy Preference Relations in Group Decision Making

Compatibility analysis is an efficient and important tool used to measure the consensus of opinions within a given group of individuals. In this paper, we give a compatibility measure between intuitionistic preference values and a compatibility measure between intuitionistic preference relations, respectively, and study their properties. It is shown that each individual intuitionistic preference relation and the collective intuitionistic preference relation is perfectly compatible if and only if all the individual intuitionistic preference relations are perfectly compatible. Based on the compatibility measures, a consensus reaching procedure in group decision making with intuitionistic preference relations is developed, and a method for comparing intuitionistic fuzzy values is pointed out, by which the considered objects are ranked and selected. In addition, we extend the developed measures, procedure and method to accommodate group decision making situations with interval-valued intuitionistic preference relations. Numerical analysis on our results through an illustrative example is also carried out.     

Decisional Power in Group Decision Making: A Note on the Allocation of Group Members' Weights in the Multiplicative AHP and SMART

Many complex decisions are made in a group environment, where the decision is made jointly by a committee or group structure. The individual group members are often not equally qualified to contribute equitably to the decision process, or may have different saliences (desires) to influence the decision. A quantitative knowledge of the players' decisional power is useful for better understanding of the group decision process, and could even be used in weighted voting within the group structure. We adapt the REMBRANDT suite of decision models (multiplicative AHP and SMART) to measure decisional power in groups, and we generalise this to cater for the case where power itself is deemed to be multidimensional in nature, and the case of uncertain subjective judgements of power amongst group members.     

Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making

Group Decision and Negotiation - In group decision making, it is sensible to achive minimum consensus cost (MCC) because the consensus reaching process resources are often limited. In this...     

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.     

A Practical Procedure for Group Decision Making under Incomplete Multiplicative Linguistic Preference Relations

The aim of this paper is to investigate a group decision making problem with incomplete multiplicative linguistic preference relations. We first define the concept of an incomplete multiplicative linguistic preference relation, and then develop a simple algorithm to extend each incomplete multiplicative linguistic preference relation to a complete multiplicative linguistic preference relation. Finally, we develop a practical procedure for group decision making under incomplete multiplicative linguistic preference relations, and give a numerical example to illustrate the developed procedure.