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.     

Multi-criteria Remote Asynchronous Group Decision Screening: An Experimental Study

A new visualization-based multi-criteria procedure for group decision screening is presented. The procedure supports a group in selecting a small number of alternatives from an initial list described by a collection of attributes which are used as screening criteria. We propose and experimentally study the Group Remote Asynchronous Screening Support (GRASS) procedure that can be used by a large number of participants who are not able to meet face to face. GRASS does not use any interaction between the participants and the group screening is based on the individual preferences expressed by them independently from each other. GRASS uses the concepts of Borda count, by applying the visualization of information to simplify the analysis of large lists of multi-criteria alternatives. Visualization is used to support the individual analysis of the variety of alternatives and the individual selecting of a small number of alternatives from the list for the subsequent scoring through Borda count. Visualization is carried via the Interactive Decision Maps / Reasonable Goals Method (IDM/RGM) technique. We first check a speculative supposition that participants are able to find a single best alternative by using the GRASS procedure. As it is not the case, we re-formulate our hypothesis and check whether the most preferred alternative is part of a short list of alternatives returned through GRASS. The experiment was carried out with senior applied mathematics students who managed to apply GRASS without any problem.     

A Distance-Based Collective Preorder Integrating the Relative Importance of the Group's Members

In this paper, we propose an aggregation procedure, which includes two steps. In the first one, the group's members elaborate individually a preorder (total or partial) on the alternatives set. These preorders can be obtained, for example, by applying a multicriterion aggregation procedure such as ELECTRE III, PROMETHEE I or II. In the second step, these individual preorders (total or partial) are aggregated into a collective preorder (total or partial). For this purpose, we first built a distance measure between pairs of binary relations in order to quantify the divergence between two preorders. Then we determine, for each pair of alternatives, the relative importance coefficients of the group's members by using a method based on subjective and objective components. These coefficients and the distance measure are finally exploited by an iterative algorithm in order to elaborate a collective preorder synthesizing the individual preorders.     

A purchase decision support model considering consumer personalization about aspirations and risk attitudes

Ranking alternative products to help consumers make better purchase choices is a valuable research topic. Most previous decision support models cannot be well applied to heterogeneous consumers. This paper focuses on establishing a personalized interactive model to assist consumers make better buying decisions with less effort. For the alternative products provided by consumers, we collect online reviews and parameter configurations of alternative products and then obtain the fusing evaluative information. As consumers are dominated by bounded rationality, they only provide partially key attribute weights, based on which, we construct an optimizing model to obtain the optimal attribute weights of customers for products. Then, a satisfaction function is proposed by uniting aspiration levels and risk attitudes of consumers and a compensatory decision rules is established to rank and recommend the brands to consumers. Finally, practicability of this study is illustrated with a real car purchase case. Through the case study, it can be seen that the proposed decision support model generates a personalized list of alternatives based on consumer's own utility function about risk attitudes, aspiration levels, and preferences for product attributes, which further confirms that the proposed model can capture the personalized needs of consumers. Theoretical and managerial implications of this model as well as advantages are further illustrated.     

A linguistic decision process in group decision making

Assuming a set of linguistic preferences representing the preferences of the individuals, a linguistic choice process is presented. This is developed using the concept of fuzzy majority for deriving a collective linguistic preference, and the concept of nondominated alternatives for deriving the selected alternatives in the linguistic choice process. The fuzzy majorities are equated with fuzzy linguistic quantifiers. The collective linguistic preference is derived by means of a linguistic ordered weighted averaging operator whose weights are defined using a fuzzy linguistic quantifier. In order to obtain the nondominated alternatives, we present a novel reformulation of Orlovski's nondominance degree under linguistic information.     

A Relative Entropy Approach to Group Decision Making with Interval Reciprocal Relations Based on COWA Operator

A new approach has been presented based on relative entropy to rank all the alternatives in the group decision making with interval reciprocal relations. First we introduced the continuous ordered weighted averaging operator and used it to aggregate all individual interval reciprocal relations to derive the priority vector. Then we define the consensus indicator of the interval reciprocal relations to determine the weights of experts in the group decision making. Based on the conception of relative entropy, we construct an optimization model to minimize the difference between the group priority vector and all individual priority vectors. We also give the solution to the optimal model, in which we obtain the formula to rank the given alternatives in the group decision making for the collective reciprocal relations and select the most desirable one. Finally, a numerical example shows that the developed approach is feasible and the result is credible.     

TOPSIS Based Approach to Scoring Negotiating Offers in Negotiation Support Systems

In this paper we analyze the possibility of applying the technique for order preferences by similarity to ideal solution (TOPSIS) to building the scoring system for negotiating offers. TOPSIS is a multiple criteria decision making method that is based on measuring distances between alternatives under consideration and two bipolar reference alternatives, a positive and negative ideal. Thus the criteria used for the evaluation of alternatives should be described using strong scales. However, in the negotiation, the issues are very often described qualitatively, which results in ordinal or even nominal variables that must be taken into consideration in offers’ evaluation process. What is more, TOPSIS may be applied to solving the discrete decision problems while the negotiation space may be defined by the means of continuous variables too. In this paper we try to modify the TOPSIS algorithm to make it applicable to negotiation support and, moreover, discuss the following methodological issues: using TOPSIS for a negotiation problem with continuous negotiation space; selecting the distance measure for adequate representation of negotiator’s preferences and measuring distances for qualitative issues. Finally, we propose a simple additional mechanism that allows for building the TOPSIS-based scoring system for negotiating offers and does not involve negotiators in time consuming and tiresome preference elicitation process. This mechanism requires from negotiators to construct examples of offers that represent some categories of quality and then by using a goal programming approach it infers all the parameters required by the TOPSIS algorithm. We also show a simple prototype software tool that applies the TOPSIS modified algorithm and may be used in electronic negotiation support.     

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.     

Investigating brand preferences across social groups and consumption contexts

Using a unique dataset on U.S. beer consumption, we investigate brand preferences of consumers across various social group and context related consumption scenarios (??scenarios??). As sufficient data are not available for each scenario, understanding these preferences requires us to share information across scenarios. Our proposed modeling framework has two main building blocks. The first is a standard continuous random coefficients logit model that the framework reduces to in the absence of information on social groups and consumption contexts. The second component captures variations in mean preferences across scenarios in a parsimonious fashion by decomposing the deviations in preferences from a base scenario into a low dimensional brand map in which the brand locations are fixed across scenarios but the importance weights vary by scenario. In addition to heterogeneity in brand preferences that is reflected in the random coefficients, heterogeneity in preferences across scenarios is accounted for by allowing the brand map itself to have a discrete heterogeneity distribution across consumers. Finally, heterogeneity in preferences within a scenario is accounted for by allowing the importance weights to vary across consumers. Together, these factors allow us to parsimoniously account for preference heterogeneity across brands, consumers and scenarios. We conduct a simulation study to reassure ourselves that using the kind of data that is available to us, our proposed estimator can recover the true model parameters from those data. We find that brand preferences vary considerably across the different social groups and consumption contexts as well as across different consumer segments. Despite the sparse data on specific brand-scenario combinations, our approach facilitates such an analysis and assessment of the relative strengths of brands in each of these scenarios. This could provide useful guidance to the brand managers of the smaller brands whose overall preference level might be low but which enjoy a customer franchise in a particular segment or in a particular context or a social group setting.     

An Extended PROMETHE II Multi-Criteria Group Decision Making Technique Based on Intuitionistic Fuzzy Logic for Sustainable Energy Planning

The implementations of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) category to complex multi-criteria group decision making (MCGDM) scenarios have been included in thousands areas. Outranking methods such as PROMETHEE II are also greatly employed in energy planning application. In MCGDM methods if decision makers (DMs) are not able to treat precise data in order to define their preferences, the intuitionistic fuzzy set (IFS) theory enables them. IFS attributes are connected with the degree of membership and non-membership, and can be used to draw uncertainty in group decision-making situations. In this paper, a new version of the PROMETHEE II method is proposed, aiming at solving MCGDM problems. Linguistic variables are expressed in the membership function and non-membership function of IFS which are used to assess the weights of all criteria and the ratings of each alternative with respect to each criteria. Conditional normalized Euclidean distance measure is adopted to measure deviations between alternatives on intuitionistic fuzzy set. Then, a ranking algorithm is applied to indicate the order of superiority of alternatives. Finally, a practical example is given to an application of sustainable energy planning to verify our proposed method. Additionally, a comparative analysis is done among the proposed PROMETHEE II method and the intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method and elimination and choice translating reality method (IF-ELECTRE).     

Measuring Investors’ Socially Responsible Preferences in Mutual Funds

The aim of this study is to analyze investor behavior towards socially responsible mutual funds. The analysis is based on an experimental study where a sample of individuals takes investment decisions under different parameters of information about the investment alternatives and expected returns. In the experiment, each participant decides how to distribute an investment budget between two funds, returns on which are uncertain and change over time. Two treatments are conducted, each providing a different degree of information on the socially responsible (SR) character of one of the two investment alternatives. The results obtained suggest that although individuals’ criteria for investment are essentially guided by returns and diversification, participants invest significantly more in a fund when they are explicitly informed about its SR nature. In particular, participants who declare being concerned about SR actually invest significantly more in the SR alternative. Furthermore, the level of SR faithfulness among a small group of investors is such that they invest the main share of their budget in the SR fund, even when the return differential is highly unfavorable. Providing clear information about the SR characteristics of an investment is crucial to help investors express their preferences.     

A logistic regression-based pairwise comparison method to aggregate preferences

In a group decision making process, several individuals or a committee have the responsibility to choose the best alternative from a set. The problem addressed in this paper is how to aggregate personal preferences to arrive at an optimal group decision. New technologies allow individuals that may seldom or never meet to make group decisions. This paper proposes a methodology to obtain the group preference ordering in two steps. Firstly, each individual studies the problem isolated, and then, in a possibly virtual meeting, the group must agree on the preferences on some pairs of alternatives. Then, the group criterion is achieved by using a logistic regression model within the pairwise comparison framework proposed here. Properties of the procedure are studied and two illustrative examples are presented.     

Compromising the compromise effect: Brands matter

Consumer behavior research has a long history indicating that preferences are influenced by the relative positions of members of a choice set. The realism of this work, however, is somewhat limited because alternatives are typically labeled with letters rather than with real brand names. We investigate the boundaries of prior research by testing whether preferences for alternatives in compromise and superior positions generalize to a more realistic market scenario that includes choices between real brands. In particular, we conduct two studies that examine if preferences for brands in a choice set are moderated by the inclusion of more or less familiar brand names. We find that consumers prefer extreme brands when compromise brands are relatively less familiar and compromise brands when they are relatively more familiar. In this scenario brand familiarity and not the position of the alternatives determine choice. In situations where a choice alternative is superior, we find no moderation due to brand familiarity.

Consumer response to and choice of customized versus standardized systems

Recent research on customization suggests that a need exists to examine conditions under which selling customized versus non-customized offerings will be more beneficial to vendors. To this end, this paper empirically evaluates consumer response to and choice of customized systems (offerings that are integrated and customized) in relation to standardized systems (offerings that feature integration but not customization). Through a series of studies, we demonstrate that the relationship between a buyer's systems purchase strategy and their future repurchase intentions toward the seller is moderated by a buyer characteristic (that is, a consumer's insight into his/her own preferences, or the degree to which a consumer can confidently and consistently express his or her true preferences) as well as a seller characteristic (retailer reputation). Given that consumers who are experts have greater insight into their own preferences than novices, our work also suggests that this greater insight into one's own preferences is a plausible explanation for why experts are more likely to choose a customized system. The main practical implication of our research is that it prompts managers to challenge the contention in some mass customization writings that customized offerings have universal appeal. Although the participants in our studies also tended to be more attracted to customized systems in general, this proclivity was lower for consumers with less product category expertise. This is important because our results convey that repurchase intentions towards a vendor will be higher after the purchase of a non-customized system by those consumers who lack insight into their preferences. As such, firms should try to propose customized systems only to those prospective buyers who possess strong preference insight, and propose standardized systems to those buyers who do not.     

The MARS Approach in the Verbal and Holistic Evaluation of the Negotiation Template

The negotiation template, which defines a set of potential negotiation offers, is traditionally evaluated by means of the simple additive weighting method (SAW). However, some recent research reports on the potential problems and inconsistencies in using and interpreting SAW-based scores. Thus, in this paper we consider the issue of evaluating negotiation offers when the negotiator’s preferences are expressed verbally. We present a new approach called Measuring Attractiveness near Reference Situations (MARS), which combines the algorithms of two multiple criteria decision making methods: ZAPROS and MACBETH. Applying the elements of ZAPROS allows identifying a small set of reference alternatives that consists of the best resolution levels for all the negotiation issues but one. In pair-wise comparisons of these alternatives negotiators need to evaluate trade-offs only, which means deciding which concessions are better to be made. Using the elements of MACBETH allows determining the strong interval scale based on verbal judgments defined by negotiators at the beginning of the preference elicitation process. We study in detail the legitimacy of hybridizing ZAPROS and MACBETH that differ in their philosophies of decision support as well as discuss the drawbacks of these two MCDM methods and propose some alternative solutions that make this approach applicable to supporting negotiators in the evaluation of negotiation offers. Finally, we present an example in which we indicate the differences in the negotiation offers’ scoring process conducted by means of MARS and the traditional ZAPROS and MACBETH procedures.     

Computer-Assisted Negotiations of Water Resources Conflicts

This paper describes the algorithms within and results obtained using an interactive computer program developed to assist those involved in negotiating agreements among parties having conflicting objectives. This Interactive Computer-Assisted Negotiation Support system (ICANS) can be used during the negotiation process by opposing parties or by a professional mediator. On the basis of information provided to the program, in confidence, by each party, it can help all parties identify feasible alternatives, if any exist, that should be preferred to each party's proposal. If such alternatives do not exist, the program can help parties develop counter proposals. Through a series of iterations in which each party's input data, assumptions, and preferences may change, ICANS can aid each party in their search for a mutually acceptable and preferred agreement. This paper describes the algorithms used for analyzing preferences and for generating alternative feasible agreements. Also presented a re the results of some limited experiments involving water resource system development and use conflicts that illustrate the potential of programs such as ICANS.     

Multiple Criteria Assessment of Insulating Materials with a Group Decision Framework Incorporating Outranking Preference Model and Characteristic Class Profiles

We present a group decision making framework for evaluating sustainability of the insulating materials. We tested thirteen materials on a model that was applied to retrofit a traditional rural building through roof’s insulation. To evaluate the materials from the socio-economic and environmental viewpoints, we combined life cycle costing and assessment with an adaptive comfort evaluation. In this way, the performances of each coating material were measured in terms of an incurred reduction of costs and consumption of resources, maintenance of the cultural and historic significance of buildings, and a guaranteed indoor thermal comfort. The comprehensive assessment of the materials involved their assignment to one of the three preference-ordered sustainability classes. For this purpose, we used a multiple criteria decision analysis approach that accounted for preferences of a few tens of rural buildings’ owners. The proposed methodological framework incorporated an outranking-based preference model to compare the insulating materials with the characteristic class profiles while using the weights derived from the revised Simos procedure. The initial sorting recommendation for each material was validated against the outcomes of robustness analysis that combined the preferences of individual stakeholders either at the output or at the input level. The analysis revealed that the most favorable materials in terms of their overall sustainability were glass wool, hemp fibres, kenaf fibres, polystyrene foam, polyurethane, and rock wool.     

Shopping Style Segmentation of Consumers

The World Wide Web has rapidly become an alternative means to reach customers and has attracted the attention of many businesses. Unfortunately, however, despite its growth, there is little knowledge of which consumers would be willing to switch to the new format and to what extent. Our paper is aimed at providing some insights into these questions. Specifically, we propose a model to identify segments that differ in their shopping style, i.e., in their preference for which format, or bundle of formats, they like to shop in.Our research question, and model, is similar in spirit to prior research in marketing on how consumers choose assortments. Despite this similarity, our research makes some substantive and methodological contributions to the literature. Substantively, we examine the issue of the choice of channel assortments by consumers across a variety of product categories. We believe this is an important question and one that has not been examined earlier. From a methodological point of view, our model adds to earlier work by specifying the utility of an assortment as a sum of the deterministic and stochastic components of the utilities of its members. This contrasts with previous research where only the deterministic components of the utilities of the component brands of an assortment are added and the relationships between their random components are not accounted for.We calibrate the model on data regarding the format choices of households. In order to control for potentially similar format preferences across purchases of different categories we specify the model to allow for correlation between format preferences over the choice history of each household. Our results suggest that there are four segments of consumers that differ in their preference for different types of formats.     

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).     

For the Greater Good? A Test for Strategic Bias in Group Environmental Decisions

This paper presents a study which tests for strategic bias in group decision support models. Strategic bias occurs when individuals provide preference information to a group decision model which, they perceive, will improve their own outcomes and not necessarily those of the group. A test is made for strategic bias in a decision model used to allocate funds amongst 14 natural resource management regions in Queensland. The funds are a crucial source of revenue for the regions to achieve environmental objectives. In this real decision problem representatives from each region supplied criteria weights for a multiple criteria analysis model. Results reveal moderate to weak presence of strategic bias. Regions mostly selected weights that would improve their outcome relative to the weights of other regions. But this was not overly pronounced and there were exceptions. Whilst some degree of strategic bias existed these results show a willingness to separate individual and group preferences when interacting with formal decision procedures. Further research is required to see how this changes under unstructured negotiation and arbitration as opposed to a formal model.