Title :
Mining Organizational Networks for Layoff Prediction Model Construction
Author :
Chang, Huo-Tsan ; Wu, Hui-Ju ; Ting, I-Hsien
Author_Institution :
Grad. Inst. of Human Resource Manage., Nat. Changhua Univ. of Educ., Changhua, Taiwan
Abstract :
Global economic recession has been causing the unpaid leave and massive layoffs in major high-tech firms of Taiwan, both factors present great potential hardship to many employees according to the reports from industry. Therefore, layoff prediction and management have become great concerns of employees and managers. Employees wish to retain their jobs and keep their work for a long time. Hence, they need to predict the possible layoff and then utilize their resources to retain their job. In response to the difficulty of layoff prediction, this study applies social networks and data mining techniques to build a model for layoff prediction. This study compares various techniques to propose a better approach to generate a possible layoff list for employees. Through an empirical study, the results indicate that the proposed approach has pretty good prediction accuracy by using organizational networks, employee databases and layoff records to build the layoff prediction model.
Keywords :
data mining; organisational aspects; personnel; social sciences computing; termination of employment; Taiwan; data mining technique; employee database; global economic recession; high-tech firms; layoff prediction model construction; layoff records; organizational network mining; social networks; Data analysis; Data mining; Databases; Delta modulation; Economic forecasting; Human resource management; Information analysis; Information management; Predictive models; Social network services; Data Mining; Human Resource Management; Layoff; Social Network Analysis;
Conference_Titel :
Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
Conference_Location :
Athens
Print_ISBN :
978-0-7695-3689-7
DOI :
10.1109/ASONAM.2009.52