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Related Concept Videos

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Decision Making01:20

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Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
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Growth Models with Integration: Problem Solving

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Related Experiment Video

Updated: Jun 27, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Integrating Consensus-Based Group Decision Making into the Graph Model for Conflict Resolution in Complex Conflict

Hengjie Zhang1, Xiaoying Lu1, Fang Wang1

  • 1Business School, Hohai University, Nanjing 211100, China.

Entropy (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

This study enhances conflict analysis by integrating group decision-making into the Graph Model for Conflict Resolution (GMCR). It addresses complex conflicts by reconciling diverse individual preferences for better equilibrium solutions.

Keywords:
consensus-based group decision makingfairness concerngraph model for conflict resolutionoptimization modeloption prioritization

Related Experiment Videos

Last Updated: Jun 27, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Area of Science:

  • Decision Science
  • Game Theory
  • Operations Research

Background:

  • Complex conflict environments present challenges for preference elicitation in the Graph Model for Conflict Resolution (GMCR).
  • Existing GMCR methods struggle with nuanced, heterogeneous preferences and lack mechanisms for reconciling divergent assessments.
  • This limits the ability to construct collective preferences and analyze complex conflicts effectively.

Purpose of the Study:

  • To integrate consensus-based group decision-making into the GMCR framework.
  • To develop a systematic mechanism for reconciling heterogeneous individual assessments and constructing collective preferences.
  • To incorporate fairness concerns into conflict analysis.

Main Methods:

  • Employed pairwise comparisons for statement importance and continuous values for state support.
  • Developed a minimum adjustment-based consensus reaching process to reconcile divergent assessments.
  • Integrated inequity aversion theory to model fairness concerns, proposing two minimum adjustment consensus models with fairness considerations.

Main Results:

  • Successfully integrated consensus-based preferences into GMCR stability analysis.
  • Demonstrated the framework's ability to identify equilibrium solutions in complex conflict scenarios.
  • The proposed models effectively reconcile heterogeneous assessments while considering fairness.

Conclusions:

  • The novel framework enhances GMCR by enabling the reconciliation of diverse preferences through consensus-building.
  • The integration of fairness concerns provides a more realistic approach to modeling individual behavior in conflicts.
  • The approach is applicable to real-world problems, as illustrated by a supply chain carbon reduction case study.