腐败行为的发展轨迹：一项潜变量混合增长模型研究

The Development of Corruption: Using Latent Growth Mixture Modeling

通过在实验室中模拟一个常见的贿赂情境,并操纵感知的腐败风险概率和腐败风险可控感,让被试进行连续10轮的腐败决策,观察腐败行为的发展趋势。本研究探讨(1)腐败行为如何发展;(2)感知的风险概率和风险可控感如何影响腐败的发展趋势。利用潜变量混合增长模型对腐败行为的发展趋势进行分析,发现腐败行为发展趋势有3种不同的类型:(1)腐败程度始终稳定在中等水平的"一般腐败者";(2)腐败程度较高,并呈逐渐增长趋势的"腐败沦陷者";(3)始终都少有腐败行为的"清廉者"。同时还发现,感知的风险概率影响初始的腐败程度,感知的风险可控感则既影响初始腐败程度,又影响腐败发展速度。

How corruption behavior develops？The theoretical derivation implies that corruption should decrease as time pass by. Because if the probability of being caught is p every time, then after n times of corruption, the probability of being caught is increasing exponentially to 1-（1-p）n . Contradictorily, the practical experience indicates that people often increase corruption. There could be two explanations to such contradiction. Firstly it may because of the ignorance of the real corruption development trends for those corruptors who didn’t get caught nor exposed. Secondly, it may because of the negligence of some key subjective factors in theoretical derivation, like perceived probability and controllability of risk. Therefore, the study simulated a corruption situation in laboratory to （1） Explore how corruption behavior develops with time passing by, （2） Explore the effects of perceived probability and controllability of the risk on people’s corruption behavior. Participants were 155 college students in Beijing （37% males）. We simulated a common bribery situation in our laboratory, and observed how people behave in 10 rounds corruption simulated situations. The participants played as government officials, and faced with bribe from faked businessman. They needed to decide whether to accept it or not. And if they accepted the bribe, based on the amounts of bribe, there was a certain probability they would get punished. However participants could avoid the punishment by finishing a task. We manipulated the level of risk probability and risk controllability in the corruption situations. Using latent growth mixture modeling, three distinct linear growth patterns of corruption behavior were identified. First class （39.36%）, with a middle initial status of corruption, demonstrated a slow non-significant linear decrease in the following times. We call this class “normal-corruptors”. The second class （30.97%）, with a higher initial status of corruption, demonstrated a slowly non-significant linear increase in the following times. We call this class “slowly-falling-corruptors”. The last class （29.68%） remained a very low degree of corruption, or no corruption at all. We call this class of people “non-corruptors”. Analyses also showed that the probability and controllability of risk have different effects on corruption development. The probability of risk only has effect on the initial status of corruption. However the controllability of risk has effect not only on the initial status but also on the slope of the developmental trends. In the condition of a low-level risk probability, people intended to have a higher initial status of corruption compared to the condition of a high probability. And in the condition of a high-level controllability, people intended to have a higher initial status of corruption and also they tended to have a more rapid development in the following times. The results suggested that the corruption trajectory is heterogeneous and there are three different classes of corruption development trajectories. The research also suggested that increasing the risk probability of corruption is not as effective as we thought before. And in order to keep corruption within limits, we need to pay more attention to reduce the people’s controllability.