ANALYTIC-BASED DECISION ANALYSIS TOOL FOR EMPLOYEE-JOB ASSIGNMENTS BASED ON COMPETENCY AND JOB PREFERENCE

Authors

  • Chorkaew Jaturanonda King Mongkut’s University of Technology Thonburi
  • Suebsak Nanthavanij Sirindhorn International Institute of Technology

DOI:

https://doi.org/10.23055/ijietap.2011.18.2.375

Keywords:

Information Systems

Abstract

This paper discusses an analytic-based decision analysis tool called Employee-Job Assignment System (EJAS) for solving the employee-job assignment problem (EJAP).  The EJAS is intended to determine an employee-job assignment (EJA) solution that optimizes the employees’ work efficiency and job satisfaction.  Two person-job (P-J) fit criteria are considered: (1) competency-based P-J fit, and (2) preference-based P-J fit.  Depending on the decision-maker’s selection, the EJAS determines an EJA solution that maximizes the chosen P-J fit.  Additionally, it is capable of generating several near-optimal solutions to assist the decision-maker in selecting a suitable EJA solution.

 

Significance:        Effective management of the human resource is an important issue for every business organization.  Assigning the right employees to the right jobs can help the organization to increase its productivity and/or enhance its service efficiency.  The proposed decision analysis tool enables responsible decision-makers to develop the employee-job assignment solution that considers both competency and job preference; thus, achieving increased productivity and better job satisfaction.

 

Keywords:             Employee-job assignment, workforce management, person-job fit, competency, job satisfaction, decision support system

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Published

2011-02-26

How to Cite

Jaturanonda, C., & Nanthavanij, S. (2011). ANALYTIC-BASED DECISION ANALYSIS TOOL FOR EMPLOYEE-JOB ASSIGNMENTS BASED ON COMPETENCY AND JOB PREFERENCE. International Journal of Industrial Engineering: Theory, Applications and Practice, 18(2). https://doi.org/10.23055/ijietap.2011.18.2.375

Issue

Section

Operations Research

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