Sustainable human resource management: Improving employee satisfaction with a nonlinear assignment program involving uncertain utility functions

Abstract

It is no doubt that the most significant resource for organizations is human capital and the optimal utilization of human capital enables them to make savings both from time and money. One of the most critical phases of human resource management is the job-personnel assignment process. For success in this process, it is necessary to consider a job candidate's satisfaction and expectations with regard to the job that he/she will be assigned, in addition to his/her technical competencies. Considering this fact, in the context of sustainable human resource management which is a topic highligted in the extant literature, this research aims to develop a job-personnel assignment decision support model that can be used to improve employee satisfaction. While the model developed makes use of the utility theory and its functions in measuring employee satisfaction, it employs a nonlinear assignment program with uncertain utility functions to determine the optimal jobpersonnel match. By taking into account both nonlinearities and uncertainties in employee satisfaction changing with respect to economic, social and environmental factors, the model developed provides a more realistic approach than the provious models do. An illustration of the model is presented with a hypothetical example where the results obtained through Monte Carlo simulation are statistically interpreted. To elaborate the contribution further, a sensitivity analysis is conducted, and the results are analyzed under both statistical independence and dependence assumptions.