E-COMMERCE HUMAN RESOURCE MANAGEMENT SYSTEM: ONLINE MONITORING FOR ATTENDANCE TRACKING, DYNAMIC SCHEDULING AND AUTOMATED PAYROLL PROCESSING

Abstract

E-commerce enterprises face critical challenges in managing human resource functions efficiently. Reliance on traditional, manual processes for attendance tracking, shift scheduling, and payroll administration often leads to errors, operational delays, and increased administrative burdens. Such inefficiencies not only hamper productivity but also raise compliance risks and adversely affect employee satisfaction and engagement. This study addresses these challenges by proposing the design, development, and thorough evaluation of an automated E-commerce Human Resource Management System. The system is purpose-built to streamline and automate core HR processes, thereby enhancing accuracy and overall operational efficiency. Employing a mixed-methods approach, the research integrates quantitative metrics and qualitative insights to comprehensively evaluate the system’s impact on HR management within e-commerce settings. The development and assessment of the Human Resource Management System (HRMS) employed a mixed-methods approach to ensure comprehensive evaluation. Utilizing the Agile Scrum framework, the system was engineered with PHP handling backend operations and MySQL serving as the database platform. The frontend interface was developed using JavaScript, HTML, CSS, and SCSS to provide a seamless and interactive user experience. Its modular design enhances maintainability and facilitates scalability for future updates. Quantitative metrics such as processing speed, payroll accuracy, and system error frequency were collected to evaluate technical performance. Additionally, semi-structured interviews with e-commerce staff and HR personnel provided qualitative feedback on usability, user satisfaction, and the system’s effect on daily workflows. The Human Resource Management System successfully incorporated comprehensive attendance monitoring and tracking, a flexible scheduling module that accommodates dynamic shift adjustments, and fully automated payroll processing. Quantitative results demonstrated substantial decreases in payroll processing times and error frequencies, underscoring the system’s efficiency. Complementary qualitative feedback reflected heightened user satisfaction, significant reductions in administrative workload, and marked improvements in the accuracy and reliability of attendance and payroll records. The results affirm the hypothesis that automating human resource management processes through a tailored HRMS substantially improves efficiency and accuracy in e-commerce operations. The system’s modular design not only supports scalability but also enables seamless integration with existing and future business systems. This study highlights the critical importance of integrating both quantitative metrics and qualitative insights to holistically evaluate the system’s effectiveness. Furthermore, the research acknowledges its limitations and outlines avenues for future investigation, including scalability testing with larger datasets and a deeper exploration of user training and adoption strategies.