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On Modeling Work Experiences and Their Influencing Factors among Employees in a University

Authors: Emily L. Casinillo; Leomarich F. Casinillo; Angelita L. Paradero;

On Modeling Work Experiences and Their Influencing Factors among Employees in a University

Abstract

Favorable work experiences are vital in becoming efficient in functioning at a University. Henceforth, it is crucial to determine some factors that might improve the employees' work experiences. This study aims to develop statistical models to elucidate the various determinants of work experiences among employees at Visayas State University, Philippines. Secondary data were utilized consisting of the different work experiences and their possible determinants. Descriptive statistics and regression analysis were employed to summarize and predict influencing determinants of work experiences. Results revealed that working at a University is challenging. Regression models have shown that teaching is more logical compared to administrative work and male workers are more likely to enjoy their job compared to female employees. Moreover, income, fair administration, opportunities for promotion, and awards are positively influencing the employees' work experiences at the university. Furthermore, results revealed that overtime pay is a good remuneration that makes employees feel that their work is rewarding. Hence, to increase employees' satisfaction and improve their well-being, the university may provide incentives or benefits for their extra service. Recognition or awards may also be provided for the meritorious performance of employees to motivate them in doing their best.

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Keywords

HB1-3840, state university, Commercial geography. Economic geography, Philippines, Economic theory. Demography, HF1021-1027, determinants, multiple regression models, philippines, work experiences

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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