Group Decision and Negotiation最新文献

Scoring rules are a popular method for aggregating rankings; they are frequently used in many settings, including social choice, information retrieval and sports. Scoring rules are parametrized by a vector of weights (the scoring vectors), one for each position, and declare as winner the candidate that maximizes the score obtained when summing up the weights corresponding to the position of each voter. It is well known that properly setting the weights is a crucial task, as different candidates can win with different scoring vectors. In this paper, we provide several methods to identify the winner considering all possible weights. We first propose VolumetricTop, a rule that ranks alternatives based on the hyper-polytope representing the set of weights that give the alternative the highest score, and provide a detailed analysis of the rule from the point-of-view of social choice theory. In order to overcome some of its limitations, we then propose two other methods: Volumetric-runoff, a rule that iteratively eliminates the alternative associated with the smallest region until a winner is found, and Volumetric-tournament, where alternatives are matched in pairwise comparisons; we provide several insights about these rules. Finally we provide some test cases of rank aggregation using the proposed methods.

The product–service system (PSS) is a strategic design approach proposed to address sustainability in socio-economic systems amidst rapid industrialization and transition. Evaluating the concept design of a PSS is a crucial and initial step prior to implementation. This study presents an innovative framework for evaluating concept designs of sustainable PSS based on a well-defined evaluation index system via integrating quality function deployment (QFD) and the technique for order preference by similarity to ideal solution (TOPSIS) while accommodating extended basic uncertain linguistic information (EBULI). Specifically, a QFD-based framework is first developed to identify the requirements of various stakeholders and then to establish the multi-dimensional criteria for evaluating sustainable PSS. Then, a House of Quality-based relationship matrix is introduced to determine the weights of criteria more accurately. Further, an adaptive consensus-reaching process method based on an expert weighting optimization model is proposed to ensure a collective outputs recognized by multiple involved stakeholders. Finally, an improved EBULI-based TOPSIS method is presented to determine the priority ranking of alternative sustainable PSS concepts. A case study on a car-sharing PSS project demonstrates the viability and effectiveness of the proposed QFD–TOPSIS integrated approach under EBULI settings. The alternative PSS concept design, which demonstrates relatively good performance in criteria of high importance, is selected as the most suitable option. Moreover, relevant comparative and sensitivity analyses reveal that the proposed approach exhibits superiorities in appropriate criteria elicitation, accurate weights determination, and high consensus ranking outputs.

In the consensus reaching process of group decision making (GDM), consensus measures do not require the consensus opinions of all decision makers. Meanwhile, unit adjustment cost is one of the important and often uncertain factors that affect consensus in GDM. Due to the uncertainty of unit adjustment costs, the moderator may not be able to provide each decision maker with an accurate unit adjustment cost. To overcome these problems, a novel class of group consensus decision models is proposed in this paper. First, fuzzy consensus measures are defined to make the consensus flexible using the specificity and coverage of the consensus granule. Secondly, to describe the uncertainty of the cost of unit adjustment, three uncertainty scenarios are created by the robust optimization approach is introduced. In the end, the feasibility and applicability of the method are verified by taking the classical GDM problem as an example, and sensitivity and comparative analyses are also performed.

Interventions involving simulated interactions aimed at mimicking real situations must be engaging to maximize their effectiveness. This study aimed to assess how a sample of middle school girls displayed behavioral and cognitive indicators of engagement when interacting with avatars representing game characters that were controlled by a human digital puppeteer. The simulation game, DRAMA-RAMA, is a component of an intervention intended to reduce at-risk girls' sexual and other risky behaviors. We used verbal/nonverbal behaviors and surveys to assess the game players' cognitive and behavioral involvement (N = 131). Participants perceived the game scenarios and interactions as realistic and the characters as similar to people in real life. Participants' behavior indicated their involvement and interest in interacting with the game characters. Finally, participants tended to be appropriate but not effective when attempting to advise/support the characters. These findings have implications for assessing successful operationalization of communication designs in interactive virtual learning environments.

Consistency and consensus are two key challenges under uncertain circumstances in pairwise comparison-based group decision-making (GDM), especially in a distributed preference relation (DPR) environment. In this paper, a comprehensive framework designed to tackle GDM problems evaluated by DPR is developed. First, after discussing two types of inconsistency in a complete DPR matrix: uncertainty-caused inconsistency and preference-caused inconsistency, two targeted optimization models to generate a consistent certain DPR matrix are proposed based on the definitions of stochastic additive strong/weak consistency and the similarity measure between DPRs. These models can effectively derive a DPR matrix closest to the original certain judgment by stochastic optimal allocation of uncertainties. Second, a new group consensus degree is introduced to measure the consensus in the group. Then a consensus improving model is given to reach an acceptable consensus by adjusting the DPR matrix of the decision maker (DM) with the least consensus degree. Third, the DMs’ weights are determined based on the expected consistency of the original DPR matrix by stochastic simulation instead of subjective judgment, and then the aggregated DPR matrix is obtained to derive a final solution using the weighted averaging operator. Finally, an automobile selection example is given to verify the validity and rationality of the proposed models.

The risk evaluation of liquefied natural gas (LNG) carriers has been the focus of research due to the special characteristics of the goods carried. Therefore, firstly, this article systematically summarizes sixteen failure modes through literature analysis and constructs a risk evaluation system for LNG carriers based on group Failure Modes and Effects Analysis (FMEA) technique. Secondly, this article introduces the personalized individual semantic (PIS) model into the risk evaluation information of LNG carriers by experts to avoid the problem of inconsistent linguistic scales among different experts. Further, this article combines the PIS model with the group consensus technique to ease the contradiction among different experts and to obtain the weights of different failure modes. Finally, the risk ranking of LNG carriers which combines objective environmental data with subjective expert evaluations is obtained, some comparative analysis and sensitivity analysis are conducted to further demonstrate the essential characteristics of the proposed method.

We study cooperative games in which some of the coalitions are not viable and in addition, there are externalities among the feasible coalitions. These games are called here restricted partition function form games. For this class of games, two extensions of the Shapley value are proposed and characterized.

Abstract

To mitigate the unfavorable effects of excessive water resources consumption, mainly induced by poor performance of irrigation practices, efficient water resource management strategies are required. In response to this need, we have, in an innovative way, enhanced the water resources management (WRM) strategies by both considering the regional conditions with the graph model for a conflict resolution (GMCR) decision support system, and linking the irrigation concept and water resources allocation theory to develop a coupled WRM simulation–optimization model. Typically, implementation of the modified WRM strategies may cause local conflicts because of losing the original water rights. To improve the current irrigation water allocation system with the minimum objections, the hypergame theory was utilized to enhance the capabilities of traditional GMCR models by including the parties’ misunderstandings in the negotiation process and assessing the partial perceptions rather than crisp options. Moreover, by dynamic monitoring of available water resources and water consumption patterns, a WRM simulation model was developed, which is applicable in real agricultural conditions of multi-agricultural zones with multi-crop and intercropping systems and variable water supply sources. The genetic algorithm was utilized to allocate the water resources and determine optimal WRM strategies with the lowest irrigation water shortage. The efficiency of the proposed framework was assessed in conventional agricultural zones in Oman. The recommended strategies not only address local conflicts during the implementation of optimal WRM strategies, but also demonstrate significant potential to reduce the water shortage as a serious environmental concern.