International Journal of Knowledge Processing Studies
Online ISSN: 2783-4611

The Application of Knowledge Extraction in Business Classification to Identify Key Players

Document Type : Original Research Manuscripts

Authors

Ali Zare Abarghouei 1
Mohammad Reza Dalvi 2
Zahra Dashtlaali 2

1 Adaptive Management, Department of Management,Dehaghan Branch,Islamic Azad University ,Dehaghan, Isfahan, Iran.

2 Department of Management,Dehaghan Branch,Islamic Azad University ,Dehaghan, Iran

https://doi.org/10.22034/kps.2023.388868.1112
Abstract
The current research was conducted to apply knowledge extraction in the classification of jobs to identify the key role players using a mixed method (qualitative and sufficient data). The application of expert systems or decision support systems based on organizational data is increasing in the selection and hiring of personnel. The data was derived from in-depth and semi-structured interviews with 17 subject experts in bank human resources, who were selected based on purposeful sampling.
Data analysis was done based on the Strauss and Corbin model in the form of open, axial, and selective coding in the Atlas TI8 software. The results showed that the classification of jobs for the key role players in public and private banks includes causal conditions (requirement of talent substitution, human resource management developments, and organizational challenges), intervening conditions  (organizational limitations and fear and resistance), and contextual conditions (strengthens and drivers) strategies (developmental, supportive and creating) and short-term and long-term consequences are among the components of the job classification model for the key role players in public and private banks. Next, based on the database with the CART method, the data mining of job classification was done. Regarding the performance of the model, it showed variance values of 311.92 and a risk value of 288.19. The predictions in the model explained 28.9% of the differences observed in the variable "employment status of A employees' category".

Keywords

Job classification
leading players
CART method
Knowledge Extraction
Data Mining
Subjects
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International Journal of Knowledge Processing Studies
Volume 4, Issue 2
Spring 2024
Pages 65-78

  • Receive Date 07 March 2023
  • Revise Date 27 August 2023
  • Accept Date 27 December 2023

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