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首页> 外文会议>7th World Multiconference on Systemics, Cybernetics and Informatics(SCI 2003) vol.6: Information Systems, Technologies and Applications: I >Aggregation of Individual Preferences in GDSS: An Empirical Study on the Consensus of Group Decisions Using Social Welfare Vs. Social Choice Functions
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Aggregation of Individual Preferences in GDSS: An Empirical Study on the Consensus of Group Decisions Using Social Welfare Vs. Social Choice Functions

机译：GDSS中个人偏好的聚集：基于社会福利Vs的群体决策共识的实证研究。社会选择功能

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摘要

In any Group Decision Support System (GDSS), there exists a "social judgment model" for calculation of weights for decision alternatives, and tabulation of votes toward a consensus. To arrive at a group decision on a set of alternatives, one can assess a social welfare function to aggregate individual cardinal preferences or utilities into a group preference. One can also use social choice functions, such as Condorcet, Borda, Copeland, and Eigenvector, to aggregate individual ordinal preferences or rankings into a group ranking. This study empirically investigates the consensus between individual preferences and the group preference derived from various aggregation methods. It proposes to use the Copeland function as a simple rule for the aggregation of individual preferences into a high group consensus.
机译：在任何团体决策支持系统（GDSS）中，都存在一个“社会判断模型”，用于计算决策备选方案的权重以及将选票汇总成共识。为了就一组备选方案达成集体决策，可以评估一种社会福利功能，以将个人基本偏好或效用汇总到集体偏好中。人们还可以使用诸如Condorcet，Borda，Copeland和Eigenvector之类的社会选择功能，将个人有序的偏好或排名汇总到组排名中。这项研究从经验上调查了个人偏好与从各种聚合方法得出的群体偏好之间的共识。它建议使用Copeland函数作为将个人偏好聚合为高群体共识的简单规则。

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