The Influence of the Physical Work Environment and Employee Motivation on Job Satisfaction among Administrative Staff at PT XYZ
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Abstract
Although employee job satisfaction has received considerable scholarly attention, research examining the combined effects of the physical work environment and work motivation on administrative employees in the cash management service industry remains limited. This study aims to analyze the effects of the physical work environment and work motivation on the job satisfaction of administrative employees at PT XYZ. A quantitative approach with a cross-sectional survey design was employed, involving 40 administrative employees selected through census sampling. Data were collected using structured questionnaires based on a five-point semantic differential scale, supported by preliminary interviews and organizational documentation, and analyzed using descriptive statistics and multiple linear regression with IBM SPSS Statistics version 26. The findings indicate that the physical work environment and work motivation have positive and statistically significant effects on employee job satisfaction, both partially and simultaneously. The physical work environment emerged as the strongest predictor, while the regression model explained 79.8% of the variance in job satisfaction. These findings support the applicability of Herzberg’s Two-Factor Theory by demonstrating that hygiene and motivational factors jointly contribute to employee job satisfaction within the cash management service industry. This study extends the human resource management literature by providing empirical evidence from administrative employees in a specialized financial service organization. The findings further emphasize the importance of integrating improvements in the physical workplace with organizational motivational practices to enhance employee satisfaction, well-being, and organizational effectiveness. Future research may examine additional determinants of job satisfaction across broader organizational contexts using larger samples and more advanced analytical approaches.

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