scholarly journals How collective reward structure impedes group decision making: An experimental study using the HoneyComb paradigm

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259963
Author(s):  
Marie Ritter ◽  
Meng Wang ◽  
Johannes Pritz ◽  
Olaf Menssen ◽  
Margarete Boos
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Detrimental Effect ◽  
Group Decision ◽  
Reward Structure ◽  
Repeated Interaction ◽  
Computer Controlled ◽  
Exploration Exploitation ◽  
Experimental Group ◽  
The Ideal

This study investigates if and under which conditions humans are able to identify and follow the most advantageous leader who will them provide with the most resources. In an iterated economic game with the aim of earning monetary reward, 150 participants were asked to repeatedly choose one out of four leaders. Unbeknownst to participants, the leaders were computer-controlled and programmed to yield different expected payout values that participants had to infer from repeated interaction over 30 rounds. Additionally, participants were randomly assigned to one of three conditions: single, independent, or cohesion. The conditions were designed to investigate the ideal circumstances that lead to identifying the most advantageous leader: when participants are alone (single condition), in a group that lets individuals sample information about leaders independently (independent condition), or in a group that is rewarded for cohesive behavior (cohesion condition). Our results show that participants are generally able to identify the most advantageous leader. However, participants who were incentivized to act cohesively in a group were more likely to settle on a less advantageous leader. This suggests that cohesion might have a detrimental effect on group decision making. To test the validity of this finding, we explore possible explanations for this pattern, such as the length of exploration and exploitation phases, and present techniques to check for confounding factors in group experiments in order to identify or exclude them as alternative explanations. Finally, we show that the chosen reward structure of the game strongly affects the observed following behavior in the group and possibly occludes other effects. We conclude with a recommendation to carefully choose reward structures and evaluate possible alternative explanations in experimental group research that should further pursue the study of exploration/exploitation phases and the influence of group cohesion on group decision making as promising topics for further research.

Reducing the Risk of Wrong Choice in Group Decision Making by Optimal Weight Allocating to Decision Makers

2018 ◽  
Vol 7 (2) ◽  
pp. 1-23 ◽  
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Potential Risk ◽  
Group Decision ◽  
Decision Makers ◽  
Topsis Method ◽  
Numerical Examples ◽  
Multiple Attribute ◽  
Key Issues ◽  
The Ideal

How to determine a weight for decision makers (DMs) is one of the key issues in Multiple Attribute Group Decision Making (MAGDM). While, some experts (or DMs) clearly wiser and more powerful in such matters than others, it has often seen that experts play their roles with same weights of importance. Meanwhile, it will lead to the wrong choice (or decision risk) and loss of values. Since, in the absence of any other standards about how to reduce this potential risk for bias, in this article, based on judgment matrices and error analysis, the author presents two new algorithm taken from crisp (the correlation-based approach) and interval (the ideal-based approach) TOPSIS method, respectively. Finally, two numerical examples are given to demonstrate the feasibility of the developed method.

FUZZY POWER AGGREGATION OPERATORS AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2013 ◽  
Vol 19 (3) ◽  
pp. 377-396 ◽  
Author(s):  
Guiwu Wei ◽  
Xiaofei Zhao ◽  
Hongjun Wang ◽  
Rui Lin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Magdm Problems ◽  
The Ideal

The article investigates the multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of triangular fuzzy information. Motivated by the ideal of power aggregation, in this paper some power aggregation operators for aggregating triangular fuzzy information are developed and then applied in order to develop some models for multiple attribute group decision making with triangular fuzzy information. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.

A Novel Method for Fuzzy Multi-Criteria Decision Making

2014 ◽  
Vol 13 (03) ◽  
pp. 497-519 ◽  
Author(s):  
Meimei Xia ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weight Vector ◽  
Decision Makers ◽  
Decision Matrix ◽  
Novel Method ◽  
The Individual ◽  
Ideal Group ◽  
The Ideal

To determine the weight vector and to aggregate the individual opinions are necessary steps in the classical methods for multi-criteria group decision-making problems in which the weight vectors of the decision makers and the criteria are incompletely known. In this paper, we propose a simple but efficient approach which can avoid these steps by establishing some optimal models. To get the optimal group decision matrix, we first propose two kinds of models among which the former focuses on minimizing the deviations between individual decision matrix and the ideal group one, while the latter aims at minimizing the deviations between the estimated group opinion and the ideal group one. To get the overall performances of alternatives, another two types of models are further established, one of which is to minimize the distance between the evaluation value under each criterion and the ideal overall value for each alternative, and the other is to minimize the distance between the estimated overall value and the ideal overall one. The proposed models can be used to deal with group decision-making under intuitionistic fuzzy, interval-valued fuzzy or other fuzzy environments, and can also provide the decision makers more choices by containing the parameter which can be assigned different values according to different actual situations. Several examples illustrate the practicability of the proposed methods.

scholarly journals NS-Cross Entropy Based MAGDM under Single Valued Neutrosophic Set Environment

2018 ◽  
Author(s):  
Surapati Pramanik ◽  
Shyamal Dalapati ◽  
Shariful Alam ◽  
F. Smarandache ◽  
Tapan Kumar Roy
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Cross Entropy ◽  
Neutrosophic Set ◽  
Entropy Measure ◽  
Numerical Example ◽  
Basic Properties ◽  
Solution Strategies ◽  
The Ideal

Single valued neutrosophic set has king power to express uncertainty characterized by indeterminacy, inconsistency and incompleteness. Most of the existing single valued neutrosophic cross entropy bears an asymmetrical behavior and produce an undefined phenomenon in some situations. In order to deal with these disadvantages, we propose a new cross entropy measure under single valued neutrosophic set (SVNS) environment namely SN- cross entropy and prove its basic properties. Also we define weighted SN-cross entropy measure and investigate its basic properties. We develop a new multi attribute group decision making (MAGDM) strategy for ranking of the alternatives based on the proposed weighted SN-cross entropy measure between each alternative and the ideal alternative. Finally, a numerical example of MAGDM problem of investment potential is solved to show the validity and efficiency of proposed decision making strategy. We also present comparative anslysis of the obtained result with the results obtained form the existing solution strategies in the solution.

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