Integrating SNA and DM technology into HR practice and research: Layoff prediction model

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

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Recent developments in social network analysis (SNA) and data mining (DM) technology have opened up new frontiers for human resource management (HRM). SNA appears to be an effective tool for mapping relationships in an organization. The increased use of information technology provides useful new data about the user behavior automatically stored in database or web log files. Data mining methods were applied in practice to explore information from this huge amount of data. Data mining can be used to gain insight into the usage behavior based on objective data in contrast to subjective data. In this chapter we suggest ways in which combine SNA and DM be analyzed using network software and DM tool. We propose an example used exploratory research design conducting a single case study in Taiwan. This research aims at introducing the importance of the application of DM and SNA to predict layoff through an empirical study.

Original languageEnglish
Title of host publicationMining and Analyzing Social Networks
EditorsI-Hsien Ting, Hui-Ju Wu, Tien-Hwa Ho
Pages53-66
Number of pages14
DOIs
Publication statusPublished - 2010 May 31

Publication series

NameStudies in Computational Intelligence
Volume288
ISSN (Print)1860-949X

Fingerprint

Electric network analysis
Data mining
Human resource management
Information technology

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Wu, H. J., Ting, I. H., & Chang, H-T. (2010). Integrating SNA and DM technology into HR practice and research: Layoff prediction model. In I-H. Ting, H-J. Wu, & T-H. Ho (Eds.), Mining and Analyzing Social Networks (pp. 53-66). (Studies in Computational Intelligence; Vol. 288). https://doi.org/10.1007/978-3-642-13422-7_4
Wu, Hui Ju ; Ting, I. Hsien ; Chang, Huo-Tsan. / Integrating SNA and DM technology into HR practice and research : Layoff prediction model. Mining and Analyzing Social Networks. editor / I-Hsien Ting ; Hui-Ju Wu ; Tien-Hwa Ho. 2010. pp. 53-66 (Studies in Computational Intelligence).
@inbook{5736cc40798b4269b76488fe76f30634,
title = "Integrating SNA and DM technology into HR practice and research: Layoff prediction model",
abstract = "Recent developments in social network analysis (SNA) and data mining (DM) technology have opened up new frontiers for human resource management (HRM). SNA appears to be an effective tool for mapping relationships in an organization. The increased use of information technology provides useful new data about the user behavior automatically stored in database or web log files. Data mining methods were applied in practice to explore information from this huge amount of data. Data mining can be used to gain insight into the usage behavior based on objective data in contrast to subjective data. In this chapter we suggest ways in which combine SNA and DM be analyzed using network software and DM tool. We propose an example used exploratory research design conducting a single case study in Taiwan. This research aims at introducing the importance of the application of DM and SNA to predict layoff through an empirical study.",
author = "Wu, {Hui Ju} and Ting, {I. Hsien} and Huo-Tsan Chang",
year = "2010",
month = "5",
day = "31",
doi = "10.1007/978-3-642-13422-7_4",
language = "English",
isbn = "9783642134210",
series = "Studies in Computational Intelligence",
pages = "53--66",
editor = "I-Hsien Ting and Hui-Ju Wu and Tien-Hwa Ho",
booktitle = "Mining and Analyzing Social Networks",

}

Wu, HJ, Ting, IH & Chang, H-T 2010, Integrating SNA and DM technology into HR practice and research: Layoff prediction model. in I-H Ting, H-J Wu & T-H Ho (eds), Mining and Analyzing Social Networks. Studies in Computational Intelligence, vol. 288, pp. 53-66. https://doi.org/10.1007/978-3-642-13422-7_4

Integrating SNA and DM technology into HR practice and research : Layoff prediction model. / Wu, Hui Ju; Ting, I. Hsien; Chang, Huo-Tsan.

Mining and Analyzing Social Networks. ed. / I-Hsien Ting; Hui-Ju Wu; Tien-Hwa Ho. 2010. p. 53-66 (Studies in Computational Intelligence; Vol. 288).

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Integrating SNA and DM technology into HR practice and research

T2 - Layoff prediction model

AU - Wu, Hui Ju

AU - Ting, I. Hsien

AU - Chang, Huo-Tsan

PY - 2010/5/31

Y1 - 2010/5/31

N2 - Recent developments in social network analysis (SNA) and data mining (DM) technology have opened up new frontiers for human resource management (HRM). SNA appears to be an effective tool for mapping relationships in an organization. The increased use of information technology provides useful new data about the user behavior automatically stored in database or web log files. Data mining methods were applied in practice to explore information from this huge amount of data. Data mining can be used to gain insight into the usage behavior based on objective data in contrast to subjective data. In this chapter we suggest ways in which combine SNA and DM be analyzed using network software and DM tool. We propose an example used exploratory research design conducting a single case study in Taiwan. This research aims at introducing the importance of the application of DM and SNA to predict layoff through an empirical study.

AB - Recent developments in social network analysis (SNA) and data mining (DM) technology have opened up new frontiers for human resource management (HRM). SNA appears to be an effective tool for mapping relationships in an organization. The increased use of information technology provides useful new data about the user behavior automatically stored in database or web log files. Data mining methods were applied in practice to explore information from this huge amount of data. Data mining can be used to gain insight into the usage behavior based on objective data in contrast to subjective data. In this chapter we suggest ways in which combine SNA and DM be analyzed using network software and DM tool. We propose an example used exploratory research design conducting a single case study in Taiwan. This research aims at introducing the importance of the application of DM and SNA to predict layoff through an empirical study.

UR - http://www.scopus.com/inward/record.url?scp=77952716493&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77952716493&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-13422-7_4

DO - 10.1007/978-3-642-13422-7_4

M3 - Chapter

AN - SCOPUS:77952716493

SN - 9783642134210

T3 - Studies in Computational Intelligence

SP - 53

EP - 66

BT - Mining and Analyzing Social Networks

A2 - Ting, I-Hsien

A2 - Wu, Hui-Ju

A2 - Ho, Tien-Hwa

ER -

Wu HJ, Ting IH, Chang H-T. Integrating SNA and DM technology into HR practice and research: Layoff prediction model. In Ting I-H, Wu H-J, Ho T-H, editors, Mining and Analyzing Social Networks. 2010. p. 53-66. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-642-13422-7_4