A hierarchical consensus reaching process for group decision making with noncooperative behaviors

Ming Tang, Huchang Liao, Xiaomei Mi, Benjamin Lev and Witold Pedrycz

European Journal of Operational Research, 2021, vol. 293, issue 2, 632-642

Abstract: With the development of technological and societal paradigms, we witness a trend where a large number of experts participate in decision-making processes, and large-scale group decision making has become a much researched topic. A large-scale group decision-making problem usually involves many experts with various backgrounds and experiences. In these cases, an effective consensus reaching process is essential to guarantee the support of all experts, especially in large-scale group decision-making settings. This study proposes a hierarchical consensus model that allows the number of adjusted opinions to vary depending on the specific level of consensus in each iterative round. Furthermore, this study also introduces a method to detect and manage noncooperative behaviors by means of the hierarchical consensus model. The minimum spanning tree clustering algorithm is used to classify experts. A weight determination method combining the size of the subgroup and the sum of squared errors is developed for subgroups. Finally, an illustrative example is provided to demonstrate the practicality of the proposed model.

Keywords: Decision support systems; Group decision making; Hierarchical consensus; Noncooperative behaviors; Minimum spanning tree (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221720310717
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:293:y:2021:i:2:p:632-642

DOI: 10.1016/j.ejor.2020.12.028

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().