Transitivity of Social Decisions under Some More General Group Decision Rules than the Method of Majority Decision

1971 ◽  
Vol 38 (3) ◽  
pp. 295 ◽  
Author(s):  
R. N. Batra ◽  
P. K. Pattanaik
Keyword(s):  
Group Decision ◽  
Decision Rules ◽  
General Group ◽  
Majority Decision ◽  
Social Decisions

Decision rules, escalation of commitment and sensitivity to framing in group decision-making

2016 ◽  
Vol 54 (7) ◽  
pp. 1649-1668 ◽  
Author(s):  
Petru Lucian Curseu ◽  
Sandra G. L. Schruijer ◽  
Oana Catalina Fodor
Keyword(s):  
Decision Making ◽  
Decision Rule ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Rules ◽  
Escalation Of Commitment ◽  
Group Level ◽  
Content Type ◽  
The Impact ◽  
Collaborative Decision

Purpose – The purpose of this paper is to test the influence of collaborative and consultative decision rules on groups’ sensitivity to framing effect (FE) and escalation of commitment (EOC). Design/methodology/approach – In an experimental study (using a sample of 233 professionals with project management experience), the authors test the effects of collaborative and consultative decision rules on groups’ sensitivity to EOC and FE. The authors use four group decision-making tasks to evaluate decision consistency across gain/loss framed decision situations and six decision tasks to evaluate EOC for money as well as time as resources previously invested in the initial decisions. Findings – The results show that the collaborative decision rule increases sensitivity to EOC when financial resources are involved and decreases sensitivity to EOC when time is of essence. Moreover, the authors show that the collaborative decision rule decreases sensitivity to FE in group decision making. Research limitations/implications – The results have important implications for group rationality as an emergent group level competence by extending the insights concerning the impact of decision rules on emergent group level cognitive competencies. Due to the experimental nature of the design, the authors can probe the causal relations between the investigated variables, yet the authors cannot generalize the results to other settings. Practical implications – Managers can use the insights of this study in order to optimize the functioning of decision-making groups and to reduce their sensitivity to FEs and EOC. Originality/value – The study extends the research on group rationality and it is one of the few experimental attempts used to understand the role of decision rules on emergent group level rationality.

Group Decision Model Based on Ordered Weighted Distance to Aid Decisions on Logistics

2018 ◽  
Vol 26 (02) ◽  
pp. 233-254 ◽  
Author(s):  
Jose Leao E Silva Filho ◽  
Danielle Costa Morais
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Decision Model ◽  
Group Decision ◽  
Decision Rules ◽  
Decision Makers ◽  
Weighted Distance ◽  
Model Based ◽  
Decision Making Model

This paper presents a group decision-making model using a distance aggregator based on Ordered Weighted Distance (OWD) which offers a solution that can reduce disagreement between decision makers (DMs). This paper discusses decision rules and sets out measures to evaluate compensatory effects that have a bearing on DMs’ opinions. The model uses formulations of distances to reveal the differences in opinion among DMs and discusses the meanings of distance and the information presented by each DM. Finally, a case study of a logistics problem is used to illustrate how the model is applied.

The structure of coalitional power under probabilistic group decision rules

1982 ◽  
Vol 27 (2) ◽  
pp. 366-375 ◽  
Author(s):  
Taradas Bandyopadhyay ◽  
Rajat Deb ◽  
Prasanta K Pattanaik
Keyword(s):  
Group Decision ◽  
Decision Rules

CLUSTERING OF DECISION TABLES TOWARD ROUGH SET-BASED GROUP DECISION AID

2011 ◽  
Vol 19 (supp01) ◽  
pp. 17-32 ◽  
Author(s):  
MASAHIRO INUIGUCHI ◽  
RYUTA ENOMOTO
Keyword(s):  
Hierarchical Clustering ◽  
Rough Set ◽  
Real World ◽  
Decision Aid ◽  
Group Decision ◽  
Decision Rules ◽  
Agglomerative Hierarchical Clustering ◽  
Clustering Techniques ◽  
Fuzzy C Means ◽  
Decision Tables

In order to analyze the distribution of individual opinions (decision rules) in a group, clustering of decision tables is proposed. An agglomerative hierarchical clustering (AHC) of decision tables has been examined. The result of AHC does not always optimize some criterion. We develop non-hierarchical clustering techniques for decision tables. In order to treat positive and negative evaluations to a common profile, we use a vector of rough membership values to represent individual opinion to a profile. Using rough membership values, we develop a K -means method as well as fuzzy c-means methods for clustering decision tables. We examined the proposed methods in clustering real world decision tables obtained by a questionnaire investigation.

The Transmission of Norms Regarding Group Decision Rules

1997 ◽  
Vol 23 (5) ◽  
pp. 516-525 ◽  
Author(s):  
Michael E. Nielsen ◽  
Charles E. Miller
Keyword(s):  
Group Decision ◽  
Decision Rules

scholarly journals Group decision rules and group rationality under risk

2016 ◽  
Vol 52 (2) ◽  
pp. 99-116 ◽  
Author(s):  
Aurélien Baillon ◽  
Han Bleichrodt ◽  
Ning Liu ◽  
Peter P. Wakker
Keyword(s):  
Group Decision ◽  
Decision Rules
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