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Fraud Transmission Mechanisms within Community: Peer Concealing and Hinting among Chinese Listed Corporations

Published online by Cambridge University Press:  05 September 2023

Jing Zhang Open the ORCID record for Jing Zhang [Opens in a new window] ,
Yuan Feng ,
Yuntao Bai  and
Yongjian Lin
Jing Zhang
Affiliation:
Business School, Southwest University of Political Science & Law, Chongqing 401120, China
Yuan Feng*
Affiliation:
School of Management, Xiamen University, Xiamen 361005, FJ, China
Yuntao Bai
Affiliation:
School of Management, Xiamen University, Xiamen 361005, FJ, China
Yongjian Lin
Affiliation:
School of Economics and Management, Xiamen University of Technology, Xiamen 361024, FJ, China
*
Corresponding author: Yuan Feng (17620190153972@stu.xmu.edu.cn)
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Abstract

We explored the transmission mechanisms of corporate fraud and its punishments within social network communities. Using fraud triangle theory and trust triangle theory, we hypothesize four transmitting channels of how fraud commission and detection are affected by peers’ fraud and punishment. Based on Chinese listed corporations from 2008 to 2018, we first construct and detect interlocked social network communities with a community-detecting algorithm, and then examine hypotheses using a bivariate probit model with partial observability. Our findings indicate that peer-concealing and -hinting effects exist within social network communities. The peer-concealing effect decreases the likelihood of being detected when committing fraud, for those with more and closer fraudulent peers. The peer-hinting effect increases the likelihood of being detected when committing fraud, for those with more and closer punished peers. There is no evidence to support peer-contagion and vicarious-punishment effects. Thus, an improved understanding of the transmission mechanism of corporate fraud commission and detection within communities is provided to prevent and detect corporate fraud. In addition, stakeholders and regulators should be aware of the deviant subculture and social distancing in social network communities.

摘要

摘要

本文 探究了公司违法违规行为及其惩处在社会关系社群中的传播机制。基于舞弊三角理论和信任三角理论，本文假设了同伴的违法违规行为及其惩处如何影响目标公司违法违规行为的实施和检举。基于中国上市公司在 2008–2018 年的数据，本文利用社群发现算法在连锁董事网络中构造了上市公司社会关系社群，并利用部分可观测的二值选择模型进行了实证检验。实证检验结果表明，在上市公司社会关系社群中，违法违规行为具有同伴遮掩效应、惩处具有同伴揭示效应，但未发现违法违规行为的同伴学习效应或惩处的替代惩罚效应：同伴遮掩效应意味着，对于拥有更多且更亲密的违法违规同伴时，目标公司实施违法违规行为后被检举的概率较低；同伴揭示效应意味着，对于拥有更多且更亲密的被惩处的同伴时，目标公司在实施违法违规行为后被检举的概率较高。因此，本文深化了对公司违法违规行为如何在社会网络社群中传播的理解，为利益相关者及监管部门提供了参考。

Keywords

bivariate probit model with partial observabilitycommunity detectioncorporate fraudinterlock networksocial network community公司违法违规行为社会关系社群社群发现连锁董事部分可观测的二值选择模型
Type
Article
Information
Management and Organization Review , Volume 19 , Issue 5 , October 2023 , pp. 1005 - 1038
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The International Association for Chinese Management Research

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