appropriate choice for building a relation with other variables.
Also, it was concluded that, out of 26 effective variables only
five variables, such as province of employment; education
level; exam score; interview score and work experience had
the most effect on the ‘promotion score’ target.
It is of great importance that an extensive use of data mining
techniques can be made in other management areas. Whilst
this is a low-cost technique, it can help managers to discover
covert knowledge in their organisations.
Limitations of the study
The limitations of the study can be classified in two separate
groups as follow:
• Lack of access to data mining software in Iran.
• Lack of access to personnel data bases.
Recommendation for future research
In order to complement and enhance the results of this
study in human resource management, the following
recommendations can be considered for future research:
• Designing a model for recruitment of entrance exam
volunteers by means of a fuzzy data mining approach.
• Investigating the difference between the result of data
mining for the recruitment model of entrance exam’s
volunteers by means of a decision tree and neural
network technique.
• Investigating the relationship between the evaluation
scores of interviewees with the future performance of
employed people by means of the data mining approach.
• Applying data mining techniques in other areas of
management.
• Investigating the relationship of banks’ employee
performance in provincial branches with the index of
deposits absorption.
Acknowledgements
Competing interests
The authors declare that they have no financial or personal
relationship(s) which may have inappropriately influenced
them in writing this article.
Authors’ contributions
A.A. (TarbiatModares University) was the supervisor of
the dissertation. M.V.S. (TarbiatModares University) was
the main provider of dissertation and was responsible for
experimental and project design and wrote the manuscript.