Consensus Building Process in Group Decision Making—An Adaptive Procedure Based on Group Dynamics

2018 ◽  
Vol 26 (4) ◽  
pp. 1923-1933 ◽  
Author(s):  
Mahima Gupta
Keyword(s):  
Decision Making ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Group Decision ◽  
Consensus Building ◽  
Adaptive Procedure ◽  
Building Process

scholarly journals Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

2015 ◽  
Vol 15 (4) ◽  
pp. 863-874 ◽  
Author(s):  
G. Lee ◽  
K. S. Jun ◽  
E.-S. Chung
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Consensus Building ◽  
Vikor Method ◽  
Flood Vulnerability ◽  
Fuzzy Vikor ◽  
Risk Vulnerability

Abstract. This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Leaderless Group Decisions

2019 ◽  
Author(s):  
Seong-Jae Min
Keyword(s):  
Decision Making ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Direct Democracy ◽  
Participatory Democracy ◽  
Group Decision ◽  
Group Discussion ◽  
The United States ◽  
Conclusive Evidence ◽  
Leaderless Group

Leaderless group decision-making denotes the idea that political decisions from a non-hierarchical discussion structure can be more legitimate and effective than those from a hierarchical structure. Since the latter half of the 20th century, such decision-making has been practiced widely in community groups, non-governmental organizations (NGOs), “deliberation” forums, as well as in the business and management settings. While one may argue its origins go back to Athenian direct democracy, it was the zeal of the 1960s participatory democracy movement in the United States that produced the more sophisticated principles, philosophies, and mechanics of leaderless group decision-making. The progressive social movement activists at that time considered non-hierarchical groups as ethically appropriate to their causes. Since then, this tradition of leaderless group decision-making processes has been adopted in many grassroots social movements. Debates and controversies abound concerning leaderless group decision-making. It has been a normative imperative for many social activists to adopt decision-making in a leaderless manner. Research to date, however, has produced no conclusive evidence that leaderless group discussion results in better or more effective decisions. Proponents argue that members of a leaderless group would develop greater capacities for self-governance because in such a setting they can take more personal and egalitarian initiatives to organize activities of the group. This, in turn, would lead to better group dynamics and discussion, and, eventually, better decisions. Critics suggest that leaderless groups are slow and inflexible in decision-making and that the supposedly leaderless groups usually end up with leaders because of the social dynamics and human nature present in group interactions. Regardless of its potential benefits and problems, the ideals of deliberative and participatory democracy are strongly propelling this egalitarian, discourse-based form of group decision-making. Researchers will gain a great deal of insight from literature in deliberation concerning the functions, problems, and future directions of leaderless groups. In addition, there is a need to study leaderless groups in a more multi-faceted way, as research to date has been dominated by psychology-based quantitative assessment of groups. Qualitative and ethnographic approaches will be helpful to further assess the dynamics of leaderless group decision-making.

scholarly journals Intra-group decision-making in agent-based models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Allegra A. Beal Cohen ◽  
Rachata Muneepeerakul ◽  
Gregory Kiker
Keyword(s):  
Decision Making ◽  
Functional Groups ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Local Governments ◽  
Large Scale ◽  
Group Decision ◽  
Social Systems ◽  
Agent Based Models ◽  
Agent Based

AbstractMany agent-based models (ABMs) try to explain large-scale phenomena by reducing them to behaviors at lower scales. At these scales in social systems are functional groups such as households, religious congregations, coops and local governments. The intra-group dynamics of functional groups often generate inefficient or unexpected behavior that cannot be predicted by modeling groups as basic units. We introduce a framework for modeling intra-group decision-making and its interaction with social norms, using the household as our focus. We select phenomena related to women’s empowerment in agriculture as examples influenced by both intra-household dynamics and gender norms. Our framework proves more capable of replicating these phenomena than two common types of ABMs. We conclude that it is not enough to build multi-scale models; explaining social behaviors entails modeling intra-scale dynamics.

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