A Trust Incentive Driven Feedback Mechanism With Risk Attitude for Group Consensus in Social Networks

激励 机制(生物学) 群(周期表) 社会心理学 心理学 微观经济学 业务 经济 认识论 哲学 有机化学 化学
作者
Feixia Ji,Jian Wu,Francisco Chiclana,Qi Sun,Enrique Herrera‐Viedma
出处
期刊:IEEE transactions on systems, man, and cybernetics [Institute of Electrical and Electronics Engineers]
卷期号:55 (3): 2133-2146 被引量:14
标识
DOI:10.1109/tsmc.2024.3519510
摘要

Trust relationships can facilitate cooperation in collective decisions. Using behavioral incentives via trust to encourage voluntary preference adjustments improves consensus through mutual agreement. This article aims to establish a trust incentive-driven framework for enabling consensus in social network group decision making (SN-GDM). First, a trust incentive mechanism is modeled via interactive trust functions that integrate risk attitude. The inclusion of risk attitude is crucial as it reflects the diverse ways decision makers (DMs) respond to uncertainty in trusting others' judgments, capturing the varied behaviors of risky, neutral, and insurance DMs in the consensus process. Inconsistent DMs then adjust opinions in exchange for heightened trust. This mechanism enhances the importance degrees via a new weight assignment method, serving as a reward to motivate DMs to further align with the majority. Subsequently, a trust incentive-driven bounded maximum consensus model is proposed to optimize cooperation dynamics while preventing over-compensation of adjustments. Simulations and comparative analysis demonstrate the model's efficacy in facilitating cooperation through tailored trust incentive mechanisms that account for these diverse risk preferences. Finally, the approach is applied to evaluate candidates for the Norden Shipping Scholarship, providing a cooperation-focused SN-GDM framework for achieving mutually agreeable solutions while acknowledging the impact of individual risk attitude on trust-based interactions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
bigboss发布了新的文献求助10
2秒前
2秒前
武林小鸟发布了新的文献求助10
3秒前
3秒前
曾浩完成签到 ,获得积分20
3秒前
3秒前
小蘑菇应助超帅寄真采纳,获得10
4秒前
4秒前
平淡晓凡完成签到,获得积分10
5秒前
7秒前
Gzl完成签到 ,获得积分10
7秒前
孟超发布了新的文献求助10
8秒前
绮罗完成签到 ,获得积分10
9秒前
吴家豪发布了新的文献求助20
9秒前
青天鸟1989发布了新的文献求助10
9秒前
lixiao完成签到,获得积分10
11秒前
11秒前
12秒前
万能图书馆应助accerue采纳,获得10
13秒前
嘻嘻发布了新的文献求助30
14秒前
明理的夜玉完成签到,获得积分10
15秒前
15秒前
rrjl完成签到,获得积分10
16秒前
勤劳白翠完成签到,获得积分10
16秒前
红泥小火炉完成签到,获得积分10
16秒前
gyh应助滕皓轩采纳,获得10
16秒前
16秒前
17秒前
搜集达人应助满满采纳,获得10
18秒前
JoshuaChen发布了新的文献求助10
18秒前
20秒前
20秒前
CodeCraft应助愉快乐瑶采纳,获得10
22秒前
22秒前
隐形曼青应助小花采纳,获得30
23秒前
24秒前
蓝莓橘子酱应助小猫钓鱼采纳,获得10
25秒前
ding应助acadedog采纳,获得10
25秒前
Frankll发布了新的文献求助10
26秒前
火星上文轩关注了科研通微信公众号
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Social Cognition: Understanding People and Events 1000
Polymorphism and polytypism in crystals 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6029047
求助须知:如何正确求助?哪些是违规求助? 7697131
关于积分的说明 16188872
捐赠科研通 5176194
什么是DOI,文献DOI怎么找? 2769978
邀请新用户注册赠送积分活动 1753333
关于科研通互助平台的介绍 1639052