Information Technology Reference
In-Depth Information
importance of the application of DM and SNA to predict layoff through an
empirical study.
Global economic recession has been causing the unpaid leave and massive lay-
offs in major high-tech firms of Taiwan, both factors present great potential hard-
ship to many employees according to the reports from industry. Therefore, layoff
prediction and management have become great concerns of employees and man-
agers. 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.
Previous researches on employees' turnover behavior mainly focus on the rea-
soning and affecting for employees' turnover intention. However, the factors for
layoff and the construction of layoff prediction model from real business data still
have not been well examined. Moreover, the application of social network analy-
sis with data mining techniques for layoff prediction model construction is less
addressed as well.
Therefore, layoff prediction and management have become of great concern to
the 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 pre-
diction, this study applies SNA and DM techniques to build a model for layoff
prediction. Social network analysis treats organizations in society as a system of
objects (e.g. people, groups, and organizations) joined by variety of relationships
[11]. A research on social networks indicates that network structure and activities
influence employees and affect individual organizational outcomes [13]. Data
mining is thus emerging as a class of analytical techniques that goes beyond statis-
tics and aims at examining large quantities of data in database.
This chapter aims at introducing the importance of the application of DM and
SNA to predict layoff through an empirical study. It first provides a literature re-
view on the recent research and application of SNA and DM. It is followed by a
discussion of the concepts of DM and SNA. A case study based on an organiza-
tion is then used to illustrate how SNA and DM is applied to develop a model for
predicting the layoff. Future directions in applying SNA and DM in the organiza-
tion networks have also provided in this paper.
2 Literature Review
2.1 Social Network
Social network analysis provides a rich and systematic means of assessing such
network by mapping and analyzing relationships among people, teams, depart-
ments or even the entire organization [10]. Organizations are considered as a
network of individuals and researchers have used network analysis to map infor-
mation flow as well as relational characteristics among strategically important
