Sürdürülebilir insan kaynağı yönetimi: Belirsiz fayda fonksiyonlu doğrusal-olmayan atama programı ile çalışan memnuniyetinin arttırılması

Abstract

 Maximizing employee satisfaction through automation and interview robots in human resource management  Uncertainty in employee expectation and satisfaction levels due to measurement error or changes through time and by experience  The presence of statistical dependency among employees' expectation and satisfaction levelsIt 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. Figure A. Histogram and box-whisker plots of the illustrative case results for scenario 6 under statistical dependency assumption Purpose: 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.Theory and Methods: 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 job-personnel 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.Results: 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 as presented in Figure A as an example. Conclusion:Although this research provides a theoretical basis for the development of an interview robot which can be used in managing human resource sustainably, further research is needed for such applications in order to protect individual rights and privacy within the framework of relevant laws and ethical values.