Fuzzy Set Based Consensus Schemes for Multicriteria Group Decision making Applied to Strategic Planning

This paper studies three consensus schemes based on fuzzy models for dealing with the input of multiple experts in multicriteria decision making. The consensus schemes are based on different aggregation procedures for constructing a collective decision. In the paper, we propose a methodology that makes use of the three consensus schemes implemented by a coordination mode that creates an efficient manner of exploiting the capabilities of each member of the group in a cooperative work. The applicability and efficiency of the proposed methodology is demonstrated through an application related to strategic planning.     

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.     

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.     

Evaluating a Framework for Multi-Stakeholder Decision Support in Water Resources Management

In this paper we describe a framework for multicriteria modeling and support of multi-stakeholder decision processes. We report on its testing in the development of a new water level management policy for a regulated lake-river system in Finland. In the framework the stakeholders are involved in the decision process from the problem structuring stage to the group consensus seeking stage followed by a stage of seeking public acceptance for the policy. The framework aims at creating an evolutionary learning process. In this paper we also focus on the use of a new interactive method for finding and identifying Pareto-optimal alternatives. Role playing experiments with students are used to test the practical applicability of a negotiation support procedure called the method of improving directions. We also describe the preference programming approach for the aggregation of the stakeholder opinions in the final evaluation of alternatives and consensus seeking.     

A Consensus Based Method for Multi-criteria Group Decision Making Under Uncertain Linguistic Setting

A two-stage (a consensus process and a selection process) approach is proposed to solve multi-criteria group decision making problems under an uncertain linguistic environment. Since achieving general consensus is a desirable goal in group decision making, the proposed method first develops a consensus reaching process in order to reach a satisfactory consensus. Based on the partial order of uncertain linguistic variables, the superiority index of one alternative over another for a given criterion and the overall superiority index of one alternative are defined. Then a procedure based on the superiority indices is described to select the best alternative(s). Given the decision makers’ desire for a consensus solution, a common framework based on the previous consensus model and the selection process is presented. Finally, a practical application is demonstrated to show the effectiveness of the proposed method.     

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.     

一种基于多人决策的供应链协同决策模型

为解决供应链协同决策的有效性问题,本文分析供应链协同决策与群体决策的区别,采用构建决策流程和决策模型、基于集对理论的共识度评价等方法,建立基于模糊多目标多人决策的供应链协同决策建模,并通过算例验证模型的合理性和有效性。     

Enhancing CSCW with Advanced Decision Making Tools for an Agile Manufacturing System Design Application

Computer Supported Collaborative Work (CSCW) can provide an efficient decision-making environment for multi-disciplinary teams faced with the challenge of evaluating agile manufacturing systems. In this paper, the development and evaluation of CSCW prototypes to aid the systematic evaluation of agile manufacturing systems are described. An industrial case study involving the evaluation of alternative design configurations of a cellular manufacturing system (CMS) for agile manufacturing was used for testing with twelve multi-disciplinary teams. The results obtained suggest that engineering design teams can obtain productivity improvements through the use of CSCW tools. The results indicate that CSCW systems can assist decision-makers in reaching consensus especially when advanced decision making tools are incorporated into the problem-solving framework. In this study, we also found that an enhanced CSCW with a neural network module for preference aggregation outperformed a basic CSCW in: (1) decision quality, (2) users' satisfaction and agreement, (3) consensus. These results also have far reaching implications for distributed product development teams that face the problem of reaching consensus on a range of alternative designs with stringent pressures to reduce development time.     

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.     

Internet Multiattribute Group Decision Support in Electronic Commerce

The rapid growth of the Internet has provided the means for distributed organizational decision making for electronic commerce. Members of organizations can jointly investigate products, exchange information, and make decisions on-line from remote sites. Internet-based multiattribute group decision making is characterized by three aspects, (i) individual interactive decision making, (ii) communication means, and (iii) group consensus reaching. The purpose of this research was to study the role of communication and individual decision strategies and their influence on multiattribute group decision making and consensus reaching in organizational electronic commerce settings. The results of this study indicate that analytic decision support is indispensable in collaborative Internet-based decision making, that a perfect match of analytic decision support and communication channels must be achieved, and that efficiency of individual decision support should be compromised for higher confidence in the group's decisions. The results of this study also confirm findings by Häubl and Trifts (2000) that interactive decision analytic support has positive effects on the quality and efficiency of individual decision making, and findings by Limayem and DeSanctis (2000) and Todd and Benbesat (2000), that decision makers will use normative decision models if they require little effort and if decisional guidance is provided. The conclusion drawn from this study is that the continuously evolving Internet technology for collaborative decision making is only one aspect for better organizational decision making – the crucial aspect, however, will be the development and optimal integration of analytic decision models, communication channels, and consensus reaching mechanisms.     

On Consensus of Group Decision Making with Interval Utility Values and Interval Preference Orderings

Uncertainty is a common phenomenon in our real world. Interval utility values and interval preference orderings are two of the simplest and most convenient tools to describe uncertain preferences in decision making. In this paper, we investigate consensus problems in group decision making with interval utility values and interval preference orderings. We first establish their transformation relations, and give a formula for calculating the association coefficients of individual uncertain preferences and group ones. We then develop a consensus procedure for group decision making with interval utility values and interval preference orderings, which takes interval utility values as the uniform preference representation. This procedure can be reduced to a series of processes for dealing with some special group decision making situations, such as: group decision making with utility values and preference orderings, group decision making with interval utility values, group decision making with interval preference orderings, etc. Finally, we illustrate the applications of the developed procedures with two practical examples.     

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.     

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.     

The Core of Consistency in AHP-Group Decision Making

This paper presents a new tool, the Consistency Consensus Matrix, designed to encourage the search for consensus in group decision making when using the Analytic Hierarchy Process (AHP). The procedure exploits one of the characteristics of AHP: the possibility of measuring consistency in judgement elicitation. Using two other tools, Preference Structures and Stability Intervals, we derive the Consistency Consensus Matrix that corresponds to the actor’s core of consistency. The performance analysis of the preference structure obtained from this matrix provides us with valuable information in search for knowledge. The new tool is illustrated by means of a case study adapted from a real-life experiment in e-democracy developed for the City Council of Zaragoza (Spain).     

Hierarchical Punishment-Driven Consensus Model for Probabilistic Linguistic Large-Group Decision Making with Application to Global Supplier Selection

Group Decision and Negotiation - Large-group decision making (LGDM) has attracted extensive attention and has been used to model complex decision problems. It is necessary to implement a consensus...     

Ethical Decision Making in a Peer-to-Peer File Sharing Situation: The Role of Moral Absolutes and Social Consensus

Individuals are downloading copyrighted materials at escalating rates (Hill 2007; Siwek 2007). Since most materials shared within these networks are copyrighted works, providing, exchanging, or downloading files is considered to be piracy and a violation of intellectual property rights (Shang et al. 2008). Previous research indicates that personal moral philosophies rooted in moral absolutism together with social context may impact decision making in ethical dilemmas; however, it is yet unclear which motivations and norms contextually impact moral awareness in a peer-to-peer (P2P) file sharing context (Shang et al. 2008). In sum, factors affecting the decision to share copyrighted material require further clarification and investigation (Shang et al. 2008). The purpose of this study was to use a consumer-based scenario and multiple ethics measures to explore how idealism, formalism, and perceived social consensus impact users’ propensity to recognize that the sharing of copyrighted media through P2P networks was an ethical issue and their subsequent ethical intentions. Results showed that high levels of idealism and formalism were associated with an increased recognition that file sharing was an ethical issue, but neither construct had a direct effect on ethical intention. Strong social consensus among respondents that other people consider file sharing to be unethical was also positively related to the recognition that file sharing was an ethical issue, and ethical recognition was a moderate predictor of intention not to engage in file sharing. Finally, a post hoc mediation analysis indicated that idealism, formalism, and social consensus operated through recognition of an ethical issue to impact ethical intention (indirect-only mediation).     

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.     

A Spreadsheet Module for Consistent Consensus Building in AHP-Group Decision Making

This paper presents a spreadsheet module developed with Microsoft Excel and Visual Basic to search for consensus when dealing with AHP in group decision making. On the basis of the theoretical results included in the paper Moreno-Jiménez et al. (2003), this spreadsheet module allows us to construct, in a local context (one criterion), the Consistent Consensus Matrix (CCM) corresponding to the core of consistency associated with the actors involved in the decision making process. By means of simulation techniques, this module provides, for each of the different values of the inconsistency thresholds considered, the preference structures derived from the interval incomplete matrix (CCM) that represents the groups core of consistency. This information will be used to establish consensus paths between the actors involved in the resolution process, one of the most important goals in distributed and participatory decision making.This paper has received partial financial support from the Research Project of the University of Zaragoza (2002): Herramientas decisionales para el constructivismo cognitivo (ref. 228-056). A previous version of this paper has been presented at the Group Decision and Negotiation session of the EURO-INFORMS Congress in Istanbul, 2003.     

Some Intuitionistic Fuzzy Weighted Distance Measures and Their Application to Group Decision Making

Xu and Chen (J Syst Sci Syst Eng 17:432–445, 2008) introduced a new decision-making technique called the ordered weighted distance (OWD) measure, having been proved useful for the treatment of situation where the available information is represented in exact numerical values. In this paper, we consider the situations with intuitionistic fuzzy and interval-valued intuitionistic information, and develop some intuitionistic fuzzy weighted distance measures such as intuitionistic fuzzy ordered weighted distance (IFOWD) measure, interval-valued intuitionistic fuzzy ordered weighted distance (IVIFOWD) measure, intuitionistic fuzzy hybrid weighted distance (IFHWD) measure and interval-valued intuitionistic fuzzy hybrid weighted distance (IVIFHWD) measure. These developed weighted distance measures are very suitable to deal with the situation where the input data are represented in intuitionistic fuzzy numbers or interval-lvalued intuitionistic fuzzy numbers. Then we present a consensus reaching process for group decision making with intuitionistic fuzzy preference information based on the developed distance measures. Finally, a practical application of he developed approach to the problem of evaluating university faculty for tenure and promotion is given.     

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.