数据挖掘在劳动力成本估计中的应用  

Application of Data Mining to Labor Cost Estimation

作　　者：彭茜[1] 何淑明[2] 

机构地区：[1]西南大学经济管理学院,重庆400700 [2]重庆工商大学管理学院,重庆400067

出　　处：《重庆工商大学学报（自然科学版）》2012年第6期50-56,共7页Journal of Chongqing Technology and Business University:Natural Science Edition

基　　金：2011年教育部人文社科青年基金项目"模型与实证:新生代农民工择业行为研究"(11XJC630005)

摘　　要：企业家在进行投资前考虑的一个重要方面是企业未来的盈利能力,而最终是否盈利则取决于收入和支出。员工的工资总额(劳动力成本的主要部分)作为企业的一项重要支出自然纳入企业家投资决策的考虑范围,对我国不同地区不同行业劳动力成本的合理估计对决策的制定有着重要意义。通过基于聚类分析的数据挖掘技术,结合实证分析对19个主要行业和31个省市自治区(中国大陆)的薪资水平进行了分析和对比,以更直观的方式揭示内在含义,为企业投资决策提供支撑。An entrepreneur emphatically considers the future profitability of the enterprise before conducting investment ,however, whether the enterprise has the profit depends on earnings and expenditure, the total sum of employees wages （ main part of labor cost）, as an important expenditure of the enterprise, is naturally considered by the entrepreneurs＇ investment decision-making, as a result, the rational estimation on labor cost in different regions and in different industries of China plays an important role in investment decision - making. Based on data mining of clustering analysis, through empirical study, this paper makes analysis and comparison of wages level in 19 industries and 31 provinces and municipalities of China's Mainland and provides support for enterprise investors by more intuitively revealing the inherent meaning of the estimation.

关 键 词：数据挖掘技术 劳动力成本 聚类分析 

分 类 号：C931.1[经济管理—管理学]