Antecedents of Port Employees’ Intention to Stay: A Binary Logistics Analysis
DOI:
https://doi.org/10.7719/jpair.v63i1.973Keywords:
Employee retention, work-life balance, supervisor support, job security, descriptive-correlational, PhilippinesDisciplines:
Human Resource Management, Public AdministrationAbstract
Employee retention is a critical concern for public sector organizations like the Philippine Ports Authority (PPA), which plays a strategic role in the country’s logistics and economic infrastructure. This study investigated how work-life balance, organizational support, and job security influence employees’ intention to stay. Data were gathered from 173 regular and contract employees working at a government port in Northern Mindanao through a validated and reliable survey questionnaire that measured perceptions of the three independent variables and retention intentions. Descriptive statistics, including means and standard deviations, were used to assess the participants’ ratings across variables, all of which were rated as high in work-life balance, supervisor support, and job security. Binary logistic regression analysis was employed to determine the predictive strength of each factor, revealing that supervisor support was a significant predictor of employees' intention to stay. Neither work-life balance nor job security had a statistically significant influence on retention. These findings highlight the pivotal role of immediate supervisors in shaping employee decisions to remain, emphasizing that leadership support can outweigh even broader structural factors in employee retention. This study contributes to the understanding of human resource dynamics in public institutions and aligns with Sustainable Development Goal (SDG 8)—Decent Work and Economic Growth. This is essential for building resilient infrastructure (SDG 9).Further research is recommended to explore other organizational factors such as career advancement, employee engagement, and workplace culture to develop more comprehensive retention strategies.
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Copyright (c) 2026 Janissa Tanggol Ibrahim, Cyril C. Chavez
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Open Access. This article published by JPAIR Multidisciplinary Research is licensed under a Creative Commons Attribution-Noncommercial 4.0 International (CC BY-NC 4.0). You are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material). Under the following terms, you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.
