Mining organizational networks for layoff prediction model construction

Huo-Tsan Chang; Hui Ju Wu; I. Hsien Ting

doi:10.1109/ASONAM.2009.52

Mining organizational networks for layoff prediction model construction

Huo-Tsan Chang, Hui Ju Wu, I. Hsien Ting

Graduate Institute of Human Resource Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
Pages	411-416
Number of pages	6
DOIs	https://doi.org/10.1109/ASONAM.2009.52
Publication status	Published - 2009 Oct 15
Event	2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009 - Athens, Greece Duration: 2009 Jul 20 → 2009 Jul 22

Publication series

Name	Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009

Other

Other	2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
Country	Greece
City	Athens
Period	09-07-20 → 09-07-22

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Software
Social Sciences(all)

Access to Document

10.1109/ASONAM.2009.52

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Chang, H-T., Wu, H. J., & Ting, I. H. (2009). Mining organizational networks for layoff prediction model construction. In Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009 (pp. 411-416). (Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009). https://doi.org/10.1109/ASONAM.2009.52

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author = "Huo-Tsan Chang and Wu, {Hui Ju} and Ting, {I. Hsien}",

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Chang, H-T, Wu, HJ & Ting, IH 2009, Mining organizational networks for layoff prediction model construction. in Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009. Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009, pp. 411-416, 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009, Athens, Greece, 09-07-20. https://doi.org/10.1109/ASONAM.2009.52

Mining organizational networks for layoff prediction model construction. / Chang, Huo-Tsan; Wu, Hui Ju; Ting, I. Hsien.

Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009. 2009. p. 411-416 (Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Chang H-T, Wu HJ, Ting IH. Mining organizational networks for layoff prediction model construction. In Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009. 2009. p. 411-416. (Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009). https://doi.org/10.1109/ASONAM.2009.52