Beyond Pay: How Compensation and Work Motivation Shape Employee Performance in an Indonesian Distribution Center

Yuaniko Paramitra; Amanda Deswita Safitri

doi:10.58777/hco.v4i1.689

Authors

Yuaniko Paramitra Faculty of Economics, Management Study Program, Krisnadwipayana University, Jakarta
Amanda Deswita Safitri Faculty of Economics, Management Study Program, Krisnadwipayana University, Jakarta

DOI:

https://doi.org/10.58777/hco.v4i1.689

Keywords:

Compensation, Work Motivation, Employee Performance, Human Resource Management, PT Tirta Investama

Abstract

This study examines the relationship between compensation, work motivation, and employee performance at PT Tirta Investama Distribution Center Jatiasih. It addresses concerns about declining employee performance classifications and growing development needs. Drawing on Equity Theory and Self-Determination Theory, the study considers organizational rewards and employee motivation in a distribution-center setting. A quantitative cross-sectional survey was conducted with 64 purposively selected employees from a population of 104. Data were collected through structured questionnaires and analyzed using multiple linear regression. Compensation and work motivation were each positively associated with performance and jointly helped explain differences in performance within the sample. These findings support considering financial and non-financial rewards alongside motivational conditions in human resource management. The results do not establish causality, and questionnaire findings should be distinguished from historical company performance assessments. Declining performance classifications suggest that compensation and motivation may not fully explain operational outcomes, which may also reflect competencies, training, workload, supervision, and working conditions. The study recommends reviewing compensation fairness and transparency while strengthening employee development, recognition, and supervisory support. Its single-site, purposive, cross-sectional design limits generalizability; future research could use longitudinal methods and objective performance data.

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