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All Journal Amkop Management Accounting Review (AMAR) Vifada Management and Social Sciences
Duta Mustajab
Universitas Yapis Papua, Indonesia
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Physics Social Sciences

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Evolution of HRM Strategies in the Digital Age: A Comprehensive Review Sjamsier Husen; Risma Nur Wahidah; Duta Mustajab
Amkop Management Accounting Review (AMAR) Vol. 4 No. 1 (2024): January - June
Publisher : Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/amar.v4i1.1535

Abstract

This study explores the evolution of HRM strategies in the digital age, focusing on integrating technology, data-driven decision-making, employee experience and engagement, and the impact on organizational culture and change management. We used a qualitative research approach to conduct semi-structured interviews and focus groups with HR professionals, managers, and employees from various industries. The data was analyzed using thematic analysis to identify patterns and insights related to digital HRM strategies. The study reveals that e-HRM systems and AI technologies significantly enhance HR efficiency and strategic capabilities. Personalized development programs and flexible work arrangements, supported by digital tools, improve employee experience, engagement, and retention. Effective leadership is critical in fostering a culture of adaptability and continuous learning, essential for successful digital transformation. The findings align with transformational leadership theory and highlight the importance of data-driven decision-making in modern HRM practices. The research contributes to both academic knowledge and practical application. Organizations can enhance their HRM strategies by investing in digital tools, fostering flexible work environments, and promoting continuous learning and adaptability through strong leadership. These strategies can lead to higher employee satisfaction, engagement, and organizational performance. Future research should include a broader range of organizations and longitudinal studies further to understand the long-term impacts of digital HRM strategies and explore potential challenges in digital transformation. This study provides a comprehensive framework for leveraging digital advancements in HRM to achieve optimal outcomes.
Effective Production Planning and Scheduling: Literature Review Duta Mustajab
Vifada Management and Social Sciences Vol. 1 No. 2 (2023): July - December
Publisher : Yayasan Vifada Cendikia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70184/h9wy6f46

Abstract

This study investigates the integration of production planning and scheduling by leveraging advanced technologies such as machine learning, data analytics, and Industry 4.0 innovations to enhance operational efficiency and responsiveness in manufacturing. Employing a mixed-method approach, this research combines quantitative analysis of empirical data with qualitative insights from industry case studies. The study evaluates the effectiveness of advanced planning and scheduling (APS) systems through real-world data and stakeholder interviews, focusing on industries implementing or implementing Industry 4.0 technologies. The findings demonstrate that integrating production planning and scheduling significantly improves resource utilization, reduces lead times, and enhances adaptability to dynamic manufacturing environments. Machine learning and data analytics provide potent predictive and adaptive decision-making tools, while Industry 4.0 technologies enable real-time monitoring and control. These results confirm the hypothesis that advanced APS systems outperform traditional methods in managing variability and uncertainty, aligning with existing theories and expanding on previous research. This study contributes valuable insights into the scientific understanding and practical application of advanced production planning and scheduling techniques. The research highlights the transformative potential of integrating machine learning, data analytics, and Industry 4.0 technologies, offering a comprehensive framework for manufacturers. Despite its limitations, the study provides a foundation for future research to explore broader contexts and long-term impacts, guiding further enhancements in manufacturing efficiency and competitiveness.
Co-Authors Risma Nur Wahidah Sjamsier Husen