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Research Of Human Resource Planning On Copper Mt.Copper Mine

Posted on:2015-07-04Degree:MasterType:Thesis
Country:ChinaCandidate:Z B ZhangFull Text:PDF
GTID:2309330428981708Subject:Business administration
Abstract/Summary:PDF Full Text Request
The object of research in this paper is the Tongshankou Copper,which is one of the main production subsidiary of Daye company.at present, the overall level of human resources planning of Copper Mt. copper mine is still in its infancy, with no guarantee of mining enterprises have the reasonable personnel structure. The mine has many problems:widespread human resources quantity in excess, the phenomenon of low quality. Key personnel job structure and quality is low, core management, technical staff has been unable to meet the Copper Mt. mine needs of the rapid development of modern mining enterprises, in order to adapt to the enterprise environment change and constantly updated technology, ensure the realization of the goal of enterprise development, the application of perfect human resource must be planning in the enterprise, this is particularly important to Daye nonferrous metals that move towards the international market and Copper Mt. copper mine.Therefore, through field research, and at the same time, by strong management database,which is belonged to the consulting company alliance PKU that is a leading enterprises in domestic management consulting industry, provide great help for personnel quantity, quality, structure, hierarchical dynamic prediction of Tongshankou Copper mine in the next five years. In this paper, a comprehensive inventory and Analysis on the current personnel situation of Tongshankou Copper Mine, using dynamic prediction mechanism, demand forecasting model to predict the mine personnel in future five years.Hope this paper can make a contribution for human resources planning of mining industry,and play the role of human resource planning for other mines, become an useful reference of other mines.
Keywords/Search Tags:human resources planning, model of demand forecast, dynamic prediction
PDF Full Text Request
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