Framing Effects in Group Investment Decision Making: Role of Group Polarization

2008 ◽  
Vol 102 (1) ◽  
pp. 283-292 ◽  
Author(s):  
Pi-Yueh Cheng ◽  
Wen-Bin Chiou
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Investment Decision ◽  
Framing Effects ◽  
Risk Averse ◽  
Group Decisions ◽  
Group Polarization ◽  
Relative Preference ◽  
Individual Decisions

Prospect theory proposes that framing effects result in a preference for risk-averse choices in gain situations and risk-seeking choices in loss situations. However, in group polarization situations, groups show a pronounced tendency to shift toward more extreme positions than those they initially held. Whether framing effects in group decision making are more prominent as a result of the group-polarization effect was examined. Purposive sampling of 120 college students (57 men, 63 women; M age = 20.1 yr., SD = 0.9) allowed assessment of relative preference between cautious and risky choices in individual and group decisions. Findings indicated that both group polarization and framing effects occur in investment decisions. More importantly, group decisions in a gain situation appear to be more cautious, i.e., risk averse, than individual decisions, whereas group decisions in the loss situation appear to be more risky than individual decisions. Thus, group decision making may expand framing effects when it comes to investment choices through group polarization.

scholarly journals A new measure of group decision-making efficiency

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Cheng-Ju Hsieh ◽  
Mario Fifić ◽  
Cheng-Ta Yang
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Group Decision Making ◽  
Group Decision ◽  
Detection Task ◽  
Detection Sensitivity ◽  
System Level ◽  
Workload Capacity ◽  
Individual Decisions ◽  
Collective Benefit

Abstract It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems’ factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321–359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacity CAND(t), which only considers the correct responses, and the assessment function of capacity AAND(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, CAND(t) and AAND(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to the AAND(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that AAND(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.

scholarly journals Groups Make Better Self-Interested Decisions

2012 ◽  
Vol 26 (3) ◽  
pp. 157-176 ◽  
Author(s):  
Gary Charness ◽  
Matthias Sutter
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Economic Behavior ◽  
Economic Research ◽  
Individual Decision ◽  
Bottom Line ◽  
Individual Decision Making ◽  
Cognitive Limitations ◽  
Individual Decisions

In this paper, we describe what economists have learned about differences between group and individual decision-making. This literature is still young, and in this paper, we will mostly draw on experimental work (mainly in the laboratory) that has compared individual decision-making to group decision-making, and to individual decision-making in situations with salient group membership. The bottom line emerging from economic research on group decision-making is that groups are more likely to make choices that follow standard game-theoretic predictions, while individuals are more likely to be influenced by biases, cognitive limitations, and social considerations. In this sense, groups are generally less “behavioral” than individuals. An immediate implication of this result is that individual decisions in isolation cannot necessarily be assumed to be good predictors of the decisions made by groups. More broadly, the evidence casts doubts on traditional approaches that model economic behavior as if individuals were making decisions in isolation.

Probabilistic Interval Reference Ordering Sets in Multi-Criteria Group Decision Making

2017 ◽  
Vol 25 (02) ◽  
pp. 189-212 ◽  
Author(s):  
Yue He ◽  
Zeshui Xu ◽  
Weiling Jiang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Investment Decision ◽  
Silk Road ◽  
Decision Makers ◽  
Distance Measures ◽  
Basic Operation ◽  
Preference Ordering ◽  
Inaccurate Information

Uncertain preference orderings have been widely applied in real world decision making problems as a useful and convenient tool to express preference information. When the number of decision makers is great, the importance degrees of preference interval orderings provided by the decision makers are usually difficult to be determined and may be ignored, which probably lead to the erroneous decision results when the weight information is missing. In order to make full use of information, we define the concepts of probabilistic interval preference ordering set (PIPOS) and probabilistic interval preference ordering element (PIPOE). Then, we give the score and the basic operation laws of PIPOEs, based on which we develop some aggregation operators and the distance measures for PIPOEs. After that, due to the limited cognitions and knowledge of the decision makers, we propose an algorithm to remove the inaccurate information and adjust the probabilities. Furthermore, we put forward the aggregation-based approach and the TOPSIS approach with probabilistic interval preference orderings for multi-criteria group decision making. Finally, in order to illustrate our approaches, we make a detailed case study concerning the infrastructure investment decision making problem on “the Silk Road Economic Belt and the 21st-Century Maritime Silk Road” (B&R) strategy.

Three-way group decisions under hesitant fuzzy linguistic environment for green supplier selection

Kybernetes ◽  
2020 ◽  
Vol 49 (12) ◽  
pp. 2919-2945 ◽  
Author(s):  
Weimin Ma ◽  
Wenjing Lei ◽  
Bingzhen Sun
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Group Decisions ◽  
Content Type ◽  
Green Supplier Selection ◽  
Strategic Role ◽  
Fuzzy Linguistic ◽  
Selection Of

Purpose The purpose of this paper is to propose a three-way group decision-making approach to address the selection of green supplier, by extending decision-theoretic rough set (DTRS) into hesitant fuzzy linguistic (HFL) environment, considering the flexible evaluation expression format of HFL term set (HFLTS) and the idea of minimum expected risk in DTRS. Design/methodology/approach Specifically, the authors first present the calculation method of the conditional probability and discuss the loss functions of DTRS with HFL element (HFLE), along with some associated properties being investigated in detail. Further, three-way group decisions rules can be deduced, followed by the cost of every green supplier candidate. Thus, based on these discussions, a novel green supplier selection DTRS model that combines multi-criteria group decision-making (MCGDM) and HFLTS is designed. Findings A numerical example of green supplier selection, the comparative analysis and associated discussions are conducted to illustrate the applicability and novelty of the presented model. Practical implications The selection of green supplier has played a critically strategic role in sustainable enterprise development due to continuous environmental concerns. This paper offers an insight for companies to select green supplier selection from the perspective of three-way group decisions. Originality/value This paper uses three-way decisions to address green supplier selection in the HFL context, which is considered as a MCGDM issue.

scholarly journals Collective intelligence or groupthink? Group decision making under the Japanese Companies Act

2018 ◽  
Vol 14 (2) ◽  
pp. 27-37 ◽  
Author(s):  
Daisuke Asaoka
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Boards Of Directors ◽  
Organizational Design ◽  
Group Decision ◽  
Collective Intelligence ◽  
Behavioural Science ◽  
Individual Decisions ◽  
Japanese Companies ◽  
Start Ups

Japanese corporate law (the Companies Act) requires that boards have three or more directors, and thus makes group decision making obligatory within firms. But according to some observers, boards of directors are often a mere formality in Japan, especially for non-public and small-to-medium-sized firms. The literature of behavioural science shows that group decision making does not necessarily produce better outcomes than individual decisions. In fact, a model of a group decision making shows that it can cause underinvestment at firms. The three-or-more requirement was formed with path dependency dating back to the late 19th century when Japan transplanted legal systems from overseas, but it was by no means the standard. Giving managers flexibility in organizational design is desirable in that it can accommodate firms’ internal characteristics and tendencies and facilitate the establishment of start-ups, new subsidiaries and joint ventures.

scholarly journals Anytime Collaborative Brain-Computer Interfaces for Enhancing Group Decision-Making in Realistic Environments

2020 ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Computer Interfaces ◽  
Related Potentials ◽  
Individual Decisions

Abstract In this paper we present and test collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of group decision-making in realistic situations. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

APPROACHES TO MULTI-STAGE MULTI-ATTRIBUTE GROUP DECISION MAKING

2011 ◽  
Vol 10 (01) ◽  
pp. 121-146 ◽  
Author(s):  
ZESHUI XU
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Investment Decision ◽  
Weight Vector ◽  
Interval Uncertainty ◽  
Weighted Averaging ◽  
Multi Stage ◽  
Investment Decision Making ◽  
Magdm Problems

Multi-stage multi-attribute group decision making (MS-MAGDM) as a familiar decision activity that usually occurs in our daily life, such as multi-stage investment decision making, medical diagnosis, personnel dynamic examination, military system efficiency dynamic evaluation, etc. The aim of this paper is to investigate MS-MAGDM problems in which both the weight information on a collection of predefined attributes and the decision information on a finite set of alternatives with respect to the attributes are collected at different stages. We first propose a Poisson distribution based method to determine the weight vector associated with a time-weighted averaging (TWA) operator. Furthermore, we use a hybrid weighted aggregation (HWA) operator to fuse all individual decision information into group opinions at different stages, and then utilize the TWA operator to aggregate the derived group opinions at different stages into the complex group ones so as to rank the given alternatives. After that, we further investigate MS-MAGDM problems where all decision information at different stages cannot be given in exact numerical values, but value ranges can be obtained. An approach based on the uncertain time-weighted averaging (UTWA) operator and the uncertain hybrid weighted aggregation (UHWA) operator is developed for solving MS-MAGDM problems under interval uncertainty. Finally, a practical example is provided to illustrate the developed approaches.

An Innovative Fuzzy-Neural Decision Analyzer for Qualitative Group Decision Making

2015 ◽  
Vol 14 (03) ◽  
pp. 659-696 ◽  
Author(s):  
Ki-Young Song ◽  
Gerald T. G. Seniuk ◽  
Janusz A. Kozinski ◽  
Wen-Jun Zhang ◽  
Madan M. Gupta
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Theory ◽  
Human Cognition ◽  
Group Decisions ◽  
Uncertain Environments ◽  
Fuzzy Neural ◽  
Professional Fields

Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper, we introduce an innovative approach to group decision making in uncertain situations by using fuzzy theory and a mean-variance neural approach. The key idea of this proposed approach is to defuzzify the fuzziness of the evaluation values from a group, compute the excluded-mean of individual evaluations and weight it by applying a variance influence function (VIF); this process of weighting the excluded-mean by VIF provides an improved result in the group decision making. In this paper, a case study with the proposed fuzzy-neural approach is also presented. The results of this case study indicate that this proposed approach can improve the effectiveness of qualitative decision making by providing the decision maker with a new cognitive tool to assist in the reasoning process.

Framing Effects and Choice Shifts in Group Decision Making

1993 ◽  
Vol 56 (1) ◽  
pp. 149-165 ◽  
Author(s):  
Paul W. Paese ◽  
Mary Bieser ◽  
Mark E. Tubbs
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Framing Effects

scholarly journals So how to make group decisions? Arrow's impossibility theorem 70 years after

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hung T. Nguyen ◽  
Olga Kosheleva ◽  
Vladik Kreinovich
Keyword(s):  
Decision Making ◽  
Decision Theory ◽  
Group Decision Making ◽  
First Principles ◽  
Group Decision ◽  
Impossibility Theorem ◽  
Group Decisions ◽  
Content Type ◽  
Kenneth Arrow ◽  
Practical Recommendations

PurposeIn 1951, Kenneth Arrow proved that it is not possible to have a group decision-making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result – well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains – so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision – this is known, e.g. for different voting schemes.Design/methodology/approachIn this paper we analyze this problem from the viewpoint of decision theory, the basic theory underlying all our activities – including economic ones.FindingsWe show how from the first-principles decision theory, we can extract explicit recommendations for group decision making.Originality/valueMost of the resulting recommendations have been proposed earlier. The main novelty of this paper is that it provides a unified coherent narrative that leads from the fundamental first principles to practical recommendations.

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