Ordered Weighted Disagreement Functions

In this paper a preference aggregation procedure is proposed for those cases in which decision-makers express their preferences by means of a ranking of alternatives. Among the most commonly applied methods for this purpose are those based on distance measures between individual and collective preferences, which look for the solution that minimizes the disagreement across decision-makers. Some models based on the minimization of the distance between rankings include weights to adjust the relative importance of the agents in the final decision, although in those cases, the weights are related with an a priori evaluation of the individuals and not with the behaviour of the agents in the group decision making process. In the model proposed here, a weighted disagreement function whose emphasis is on the ordered position of the individuals’ disagreement values is developed. In order to solve the problem, a mixed-integer linear programming model is constructed.     

Fuzzy Group Decision Making for the Selection of Facility Location

In this paper, fuzzy group decision making based on extension of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method which was proposed by Chen (Fuzzy Sets Syst, 114:1–9, 2000) is adopted for facility location selection. In this method, the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic variables represented by fuzzy numbers. By fuzzy numbers, it has been tried to resolve the ambiguity of concepts that are associated with human being’s judgments. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). In Chen’s approach, the distance between two fuzzy numbers is calculated with vertex method. But in this study, different distance measurement methods are used and the results are compared. Finally the proposed method has been applied to a facility location selection problem of a textile company in Turkey.     

A Case Study of Group Decision Method for Environmental Foresight and Water Resources Planning Using a Fuzzy Approach

Group decision-making (i.e., multi-expert) is an important subject in planning water resources. The inherent complexity and uncertainty of real world urge many experts to be involved in decision-making processes. This paper presents an application of the linguistic-label aggregation method in a real-life case study. The case was taken from a foresight exercise in Colombia (South America) concerning environmental and water resources planning in a river basin. The group decision-making problem is solved using a four-step approach based on (i) the evaluation of experts’ opinions, (ii) the aggregation of opinions for each alternative, (iii) fuzzy ranking, and (iv) final assessment. Two main issues that are new in our work is that we consider temporal linguistic labels and a fuzzy ranking procedure that is able to include the mean, the standard deviation, the fuzzy membership function and the frequency of experts’ opinions for each alternative. The approach is developed and implemented on a computational tool. Results show an efficient decision-making process, that is, the tool demonstrated to deal with shortest time frames and to increase the efficiency of the planning resources, mainly because allows the decision manager to focus on the establishment of criteria. The latter also leads to objectivity and eases the identification and discussion of elements of consensus in decisions that otherwise may be embedded in individuals’ interests.     

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.     

A Model of Elitist Qualification

This paper deals with the collective qualification of members of society as belonging to a certain category or group based on a fixed attribute. Our model contains three main features: the existence of individual gradual opinions, the notion of elitism (only the opinions of certain individuals are taken into account to delineate the reference group), and the idea of sequentiality (elites are successively created by using the previous elites’ opinions on a social decision scheme). The main results of the paper characterize when this sequential procedure converges for some intuitive ways of aggregating individual opinions. Finally, we analyze the role of convergence for two extra basic properties (symmetry and contractiveness) that elitist rules should possess.     

The Role of Virtues in the Framing of Decisions

This article explores links between the modern theory of rational choice and ethics. Ethics allows us to answer an unsolved question in modern decision theory: the structuring problem in decisions. Such a problem cannot be solved coming from the principle of expected utility. This principle can solve the problem of ‚choosing’ among given alternatives, but does not establish which alternatives should be taken into account in decision. In order to understand the structuring problem, the act of ‚choosing’ has to be completed with three human acts: operating, predicting and evaluating. At the same time, the subjective criteria of rational choice – probability and utility – have to be completed with three objective criteria: efficiency, truth and goodness. Utility is a subjective value of an alternative considered in relation to another. Efficiency, truth and goodness are objective qualities of the joint alternatives in relation to the reality: the real operating possibilities of the agent, the real possibilities of his environment and the true good produced. So, the rule that guarantees a decision to be optimal would be: “do that which most certainly maximises our preferences, according to real operative resources, true knowledge and the right will”. However, this rule cannot be applied without the development of virtues, which could be seen as the main moral competences in decision-making.     

Multiple Attribute Group Decision Making Method Based on Utility Theory Under Interval-Valued Intuitionistic Fuzzy Environment

In this paper, a kind of multiple attribute group decision making problem is studied, where there is no original information about the weights of importance of the attributes and the decision makers (DMs), and the attribute values are given in the form of interval-valued intuitionistic fuzzy numbers (IVIFNs). To solve this problem, a new method is proposed based on utility theory. In the proposed method, the weights of importance of the DMs and the attributes are all determined by using the intuitionistic indexes of related IVIFNs. And then, the alternatives are compared by using their composite interval indexes which are generated based on utility theory. Finally, two numerical examples are proposed to demonstrate the effectiveness of the proposed method.     

Cultural Differentiation of Negotiating Agents

Negotiations proceed differently across cultures. For realistic modeling of agents in multicultural negotiations, the agents must display culturally differentiated behavior. This paper presents an agent-based simulation model that tackles these challenges, based on Hofstede’s model of national cultures. The context is a trade network for goods with a hidden quality attribute. The negotiation model is based on the ABMP negotiation architecture and applies a utility function that includes market value, quality preference and risk attitude. The five dimensions of Hofstede’s model are the basis for the modification of ABMP parameters and weight factors in the utility function. The agents can observe each other’s group membership and status. This information is used, along with the indices of Hofstede’s dimensions, to differentiate behavior in different cultural settings. The paper presents results of test runs that verify the implementation of the model. The model helps to explain behaviors of actors in international trade networks. It proves that Hofstede’s dimensions can be used to generate culturally differentiated agents. Further validations of the model with case studies from literature and experiments have yet to be conducted. Extensions can make this model a useful tool for training traders who engage in cross-cultural negotiation and for implementation in negotiation support systems.     

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.     

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 Distance-Based Collective Weak Ordering

A group decision-making approach can be seen as a two stage process. The first stage allows for multi-cirteria evaluation of the alternatives and the second aims at deriving a collective weak ordering from the partial orderings supplied by the members after the first stage. The problem of combining the weak orderings to form a collective ranking is investigated. An axiomatic structure relating to the concept of distance between binary relations is developed. An algorithm for deriving the collective weak ordering is proposed, based on the idea of ranking first the least dominated alternatives.     

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).     

Multicriteria Group Decision-Making Method Using Vector Similarity Measures For Trapezoidal Intuitionistic Fuzzy Numbers

Based on the extension of the Jaccard, Dice, and cosine similarity measures, three vector similarity measures between trapezoidal intuitionistic fuzzy numbers (TIFNs) are proposed in the vector space and are applied to the fuzzy multicriteria group decision-making problem, in which the criteria weights and the evaluated values in decision matrix are expressed by TIFNs. Through the weighted similarity measures between each alternative and the ideal alternative, the ranking order of all the alternatives can be determined and the best one(s) can be easily identified as well. A practical example of the developed approaches is given to select the investment alternatives. The decision results of different similarity measures demonstrate that the three similarity measures have better similarity identification. The illustrative example shows that the proposed methods are applicable.     

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.     

A Progressive Search for a Group Ranking with Robust Conclusions on Prudent Orders

We consider the problem where rankings, provided for instance by a group of evaluators, have to be combined into a common group ranking. In such a context, Arrow and Raynaud suggested that the compromise ranking should be a prudent order. In general, a prudent order is not unique. That is why, we propose to manage this possible multiplicity of compromise solutions by computing robust conclusions. This allows for a progressive refinement of the decision model and supports the group to eventually select one group ranking. The approach is illustrated on a problem where a group of junior researchers has to agree on a ranking of research domains.     

Consistency in MCGDM Problems with Intuitionistic Fuzzy Preference Relations Based on an Exponential Score Function

This paper investigates an approach for multiple criteria decision making problems with intuitionistic fuzzy preference relations (IFPRs). An exponential score function for intuitionistic fuzzy numbers is developed. Its novelty is that it can convert an IFPR into a multiplicative preference relation. Then, the exponential score preference relation is introduced and its associated optimal transfer matrix is proposed. The optimal transfer matrix can guarantee the consistency via the additive transitivity property. Furthermore, an optimal model for aggregating group IFPRs to reach consistency is proposed. Finally, a group decision making approach and a multi-criteria decision making approach with IFPRs are presented.     

Ethical Decisions About Sharing Music Files in the P2P Environment

Digitized information and network have made an enormous impact on the music and movie industries. Internet piracy is popular and has greatly threatened the companies in these industries. This study tests Hunt-Vitell’s ethical decision model and attempts to understand why and how people share unauthorized music files with others in the peer-to-peer (P2P) network. The norm of anti-piracy, the ideology of free software, the norm of reciprocity, and the ideology of consumer rights are proposed as four deontological norms related to using P2P systems. The model is tested using a scenario survey with four alternatives; the results indicate that the deontological norm of anti-piracy is not a main factor in affecting P2P users’ ethical considerations regarding sharing files with others. This finding suggests that to protect their property rights, record companies should try to realize the consumer benefits brought via new digital and network technology, instead of simply declaring their intellectual property and resisting the innovations resulting from new technologies.     

Reaching informed agreement in multispecialist cooperation

Very often, complex decisions must be made by a group of specialists rather than a single decision maker. To make an effective decision, the combination of the group's expertise must be brought to bear on the situation. Fusing expertise where individuals have very detailed knowledge in their own areas and much weaker understanding of others is characterized by many difficulties: (1) agents cannot communicate their expertise in an intelligible way to nonexperts because of differences in vocabulary and conceptual content; (2) the process allows for incorrect inferences; and (3) no one knows what anyone else needs to know. This impasse cannot be broken until shared mental models are developed to provide a level of agreement in evaluating alternatives needed to focus the activity of the group. This article presents a model of decision making by teams of specialists in which agents' evaluations confound expert and naive inferences in judging alternatives. A partitioning of agent knowledge into expert and naive models is proposed. The naive portion of agents' models provides both a common language and the inferential skeleton needed for the development of shared models. Communications are categorized into types of evaluation or justification based on their form and the entities they involve within the agent models. A process of model refinement is outlined, linking communications among agents to modifications of the naive/ shared portions of their models. The process of cooperative problem solving by a team of specialists is characterized as a search among alternatives in which model refinement continually alters the agents' evaluations, leading to progressively greater accuracy and more precisely directed search. The model is intended as a research tool for investigating multiagent problem solving among people and machines.     

Staging of venture capital investment: a real options analysis

This paper uses contingent claims analysis to investigate the staging decision of venture capitalist (VC) in a principal-agent framework. Venture capital investment opportunities are modeled as real options with multiple volatilities, and the entrepreneur’s incentive is assumed to maximize the probability of getting funded in the next financing round. Two celebrated formulae in the option pricing literature are generalized to evaluate these real options. We find that staging not only gives the VC a waiting option but also mitigates the agency problem of the entrepreneur undertaking too conservative activities. Moreover, we find that the VC tends to stage her investment when the expected growth rate of the venture’s market value is lower. However, the risk-free interest rate is not an important factor in the staging decision. Our model also provides a good explanation for existing empirical evidence on the staging of venture capital investment.     

Development of a media selection model using the analytic network process

The authors develop and test a comprehensive model for media selection utilising the Analytic Network Process (ANP). ANP is a flexible and powerful multi-attribute decision aid developed by Saaty (1996) for solving complex decision-making problems. It is aimed at integrating different measures (both qualitative/intangible and quantitative/tangible) into a single overall score for ranking decision alternatives. In applying the ANP method, the authors specifically incorporate web/internet media advertising into their list of media alternatives, using many of the same standard media attributes that have typically been employed in comparing more traditional media. The result is a model that may be utilised by expert and/or novice media planners with equal effectiveness.