ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2016, Vol. 48 ›› Issue (8): 1013-1025.doi: 10.3724/SP.J.1041.2016.01013

• 论文 • 上一篇    下一篇

个体自信度对双人决策的影响

余柳涛1; 鲍建樟1; 陈清华1;王大辉1,2   

  1. (1北京师范大学系统科学学院; 2北京师范大学认知神经科学与学习国家重点实验室, 北京 100875)
  • 收稿日期:2015-11-13 出版日期:2016-08-25 发布日期:2016-08-25
  • 通讯作者: 王大辉, E-mail: wangdh@bnu.edu.cn; 陈清华, E-mail: qinghuachen@bnu.edu.cn
  • 基金资助:

    国家自然科学基金项目“风险感知的神经计算机制研究”(31271169)、中央高校基本科研业务费专项资金资助。

The effect of individual confidence on dyadic decision making

YU Liutao1; BAO Jianzhang1; CHEN Qinghua1; WANG Dahui1,2   

  1. (1 School of Systems Science, Beijing Normal University, Beijing 100875, China) (2 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China)
  • Received:2015-11-13 Online:2016-08-25 Published:2016-08-25
  • Contact: WANG Dahui, E-mail: wangdh@bnu.edu.cn; CHEN Qinghua, E-mail: qinghuachen@bnu.edu.cn

摘要:

群体决策是重要的社会现象, 个体自信度在群体决策中发挥了重要作用。本文开展了不同难度和信息交流方式下的双人决策实验, 通过分析自信度和个体决策以及决策调整行为的关系, 研究了个体自信度的交流对双人决策的影响。实验结果表明, 个体的自信度与选择的正确率高度正相关; 双人决策过程是个体根据对方的自信度和选择来不断调整自己的选择最终达成一致的过程, 并通过交互过程提高双人决策的正确率; 实验中双人决策的质量明显优于“自信度分享模型”和“更自信者主导决策模型”的预期结果, 表明群体决策不是通过分享自信度进行的贝叶斯优化整合过程, 也不是由更自信的个体完全主导的过程。

关键词: 双人决策, 动态交互, 自信度, 自信度分享, 虚拟决策

Abstract:

Making a decision as a group of individuals is at the core of any society. Group decision making (GDM) is thus a topic across many research fields. In particular, two questions are crucial to evaluate group decisions: (1) Whether the group performance is better or worse than that of the individuals, and (2) how the individuals’ decisions lead to the group decision. Previous studies have found controversial answers for the first question, indicating that group performance actually depends on the situation. Therefore, to better understand GDM, researchers have looked for the key factors that influence the formation of a group decision. Recently, confidence has been shown to play a pivotal role in this process. Bahrami et al. (2010) proposed a “weighted confidence sharing” (WCS) model to describe the information integration process in GDM. Koriat (2012) investigated the situation when “the more confident member dominates” (MCD) the decision of groups with two members. While explaining the performance of GDM, these studies ignored the dynamic information communication process. How the dynamical interaction between members of the group affects GDM is thus unclear. To explore this question, we designed and carried out a dyadic motion direction discrimination task with a varying communication process. In our three experiments, participants first decide individually in what direction random dots is moving and also report their confidence in a scale from 1 to 6 after making the decision. To study the dynamical process of reaching a consensual decision, we designed the experiments as follows. If the decisions of the two participants in a group are consensual, feedback information on the screen will tell them whether their answers are right or wrong; otherwise, they need to repeat the decision after seeing the identical stimulus again and incorporating information about the behavior of the other participant. In Experiment 1 and 2, each participant is informed about the other’s choice, while in Experiment 3 the other’s confidence is additionally reported. This process is repeated round-by-round until they reach a consensus. The task’s difficulty can be adjusted by varying the coherence level of the dot pattern (the fraction of dots moving towards the same direction) and by varying the number of choice alternatives (two directions for Experiment 1, and four directions for Experiment 2 and 3). By fitting the experimental data using a cumulative Gaussian function, we compared the psychometric sensitivities between individuals, dyad and the WCS and MCD models. Furthermore, we built a model based on Markov process to consider the dynamic change of choice probability due to interaction. We found that in all three experiments, the accuracy of the first-round choice, which was done individually without influence of the other, strongly positively correlates with confidence (Pearson's correlation coefficients approaching 0.99). However, in the following rounds, where the individual decision could be influenced by the other’s choices, the correlation of the accuracy with confidence decreases. This decrease is particularly evident in Experiment 3, where participants can gauge the confidence of each other. We further compared in Experiment 2 and 3 the relationship between the probability of changing one’s choice in the next round and the difference of the individual confidences in the current round. Our results show that the probability of changing the choice positively correlates with confidence difference, and the trend is more prominent for Experiment 3, where the participants can see each other’s confidence. This finding implies that confidence does affect each other’s choice during GDM. Further, the psychometric sensitivities hold the relationship for all three experiments, implicating that neither the WCS nor the MCD model can describe the experimental data integrally. Moreover, SMCD is slightly smaller than SB in Experiment 1 and 2, which is reversed in Experiment 3, indicating confidence’s effect on GDM again. In conclusion, our results show that (1) the decision accuracy is positively correlated with individuals’ confidence; (2) the communication of confidence of the other can influence the tendency to change one’s decision, leading to higher probability to follow the other’s choice given that she/he is more confident; (3) the dyad performance is better than both individuals’ performance and both models’ predictions, indicating that the more confident member does not dominate the group decision and Bayesian integration of shared confidence cannot account for the whole group performance; (4) a Markov model considering the change of choice probability due to dynamic interactions described the experimental data well. However, to better understand the dynamics of GDM, we need to refine the experimental design to extend the interaction rounds in the future.

Key words: dyadic decision making, dynamic interaction, confidence, confidence sharing, virtual decision making