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公共物品博弈中的沟通的共鸣效应。

Reverberation effect of communication in a public goods game.

机构信息

Department of Management and Economics, Otto-von-Guericke University, Magdeburg, Germany.

出版信息

PLoS One. 2023 Feb 27;18(2):e0281633. doi: 10.1371/journal.pone.0281633. eCollection 2023.

DOI:10.1371/journal.pone.0281633
PMID:36848359
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9970058/
Abstract

Using a public goods laboratory experiment, this paper analyzes the extent to which face-to-face communication keeps its efficiency gains even after its removal. This is important as communication in real world is costly (e.g. time). If the effect of communication is long-lasting, the number of communication periods could be minimized. This paper provides evidence that there is a lasting positive effect on contributions even after communication was removed. Yet, after the removal, the contributions are lower and abate over time to the previous magnitude. This is referred to as the reverberation effect of communication. As we do not observe an effect of endogenizing communication, the strongest driver of the size of the contributions is the existence of communication or its reverberation. Eventually, the experiment provides evidence for a strong end-game effect after communication was removed, insinuating communication does not protect from the end-game behavior. In total, the results of the paper imply, that the effects of communication are not permanent but communication should be repeated. Simultaneously, results indicate no need for permanent communication. Since communication is conducted using video-conference tools, we present results from a machine learning based analysis of facial expressions to predict contribution behavior on group level.

摘要

本文通过公共物品实验室实验,分析了面对面沟通在取消后仍能在多大程度上保持其效率增益。这一点很重要,因为现实世界中的沟通是有成本的(例如时间)。如果沟通的效果具有持久性,那么沟通的次数就可以最小化。本文提供的证据表明,即使在取消沟通后,对贡献的积极影响仍然存在。然而,在取消沟通后,贡献会降低,并随着时间的推移恢复到之前的水平,这被称为沟通的回响效应。由于我们没有观察到沟通的内生性效应,因此贡献大小的最强驱动因素是沟通的存在或其回响。最终,实验结果表明,在取消沟通后存在强烈的终局效应,暗示沟通并不能防止终局行为。总的来说,本文的结果表明,沟通的效果不是永久性的,而是应该重复沟通。同时,结果表明不需要永久性的沟通。由于沟通是通过视频会议工具进行的,我们还展示了基于机器学习的面部表情分析结果,以预测群体层面的贡献行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/85e69d220754/pone.0281633.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/ceb131d8c436/pone.0281633.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/9e912e9bc870/pone.0281633.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/85e69d220754/pone.0281633.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/ceb131d8c436/pone.0281633.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/9e912e9bc870/pone.0281633.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f3/9970058/85e69d220754/pone.0281633.g003.jpg

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本文引用的文献

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Sensors (Basel). 2019 Jun 21;19(12):2786. doi: 10.3390/s19122786.
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