Linkage between satisfaction with colleagues, promotion, nature of work, and three-dimensional organizational commitment
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DOIhttp://dx.doi.org/10.21511/ppm.19(1).2021.11
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Article InfoVolume 19 2021, Issue #1, pp. 127-136
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Employees’ job satisfaction is a leading factor in determining their organizational commitment. The organizational commitment level affects the employees’ decision to leave or remain in their organization. The banking sector of Nepal has been facing a problem of high employee mobility from one bank to another. In the backdrop of this context, this survey intends to examine the effect of satisfaction with colleagues, promotion, and the nature of work on the three dimensions of organizational commitment using the Ordinary Least Squares model in the context of private bank employees in Nepal. This study used a survey method to collect data from 199 employees working in private banks in Nepal, using a standardized questionnaire. The collected data were coded, entered, and processed in Statistical Package for Social Sciences version 25. The outcomes of the study – satisfaction with the colleagues, promotion, and the nature of the work – had a significant positive impact on the affective and normative commitment of the employees, but the regressors had an insignificant effect on continuance commitment. The employees’ satisfaction from their colleagues, promotion, and the nature of work positively improves their affective and normative commitment. Nevertheless, this study found the predictor variables as irrelevant factors for explaining the continuance commitment of the employees in the context of the study. This study’s contribution is the idea of how satisfaction with colleagues, promotion, and work nature contribute to the three dimensions of organizational commitment among Nepalese private bank employees.
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JEL Classification (Paper profile tab)G41, M54
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References46
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Tables4
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Figures0
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- Table 1. Summary statistics
- Table 2. Correlation matrix of response and predictor variables N = 199
- Table 3. Multiple regression equation of AC on all predictor variables
- Table 4. Multiple regression equation of NC on all predictors
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