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Demographic Variables of Corruption in the Chinese Construction Industry: Association Rule Analysis of Conviction Records

机译:中国建筑业腐败人口变量:定罪记录关联规则分析

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摘要

Corruption in the construction industry is a serious problem in China. As such, fighting this corruption has become a priority target of the Chinese government, with the main effort being to discover and prosecute its perpetrators. This study profiles the demographic characteristics of major incidences of corruption in construction. It draws on the database of the 83 complete recorded cases of construction related corruption held by the Chinese National Bureau of Corruption Prevention. Categorical variables were drawn from the database, and association rule mining analysis' was used to identify associations between variables as a means of profiling perpetrators. Such profiling may be used as predictors of future incidences of corruption, and consequently to inform policy makers in their fight against corruption. The results signal corruption within the Chinese construction industry to be correlated with age, with incidences rising as managers' approach retirement age. Moreover, a majority of perpetrators operate within government agencies, are department deputies in direct contact with projects, and extort the greatest amounts per case from second tier cities. The relatively lengthy average 6.4-year period before cases come to public attention corroborates the view that current efforts at fighting corruption remain inadequate.
机译:建筑业的腐败是中国的严重问题。因此,战斗这一腐败已成为中国政府的优先目标,主要努力发现和起诉其肇事者。本研究概况了腐败主要事件的人口特征。它借鉴了中国国家腐败预防局持有的83个完整录制腐败案件的数据库。从数据库中汲取的分类变量,并且关联规则挖掘分析“用于将变量与分析肇事者手段的关联识别。这种分析可能被用作未来腐败事件的预测因素,从而为政策制定者提供反对腐败的斗争。结果在中国建筑行业内腐败与年龄相关联,因为管理者的方法退休年龄为发病率。此外,大多数肇事者在政府机构内运作,是与项目直接接触的部门代表,并勒索了来自第二层城市的每个案例的最大金额。案件前持续的平均6.4年期间相对较长,以证明对抗腐败时期的努力仍然不充分。

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