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All Journal Journal of Psychological Perspective Asian Journal of Logistics Management
Khan, Muhammad Inzamam
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences Other

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The Role Generative AI in Human Resource Management: Enhancing Operational Efficiency, Decision-Making, and Addressing Ethical Challenges Khan, Muhammad Inzamam; Parahyanti, Endang; Hussain, Shah
Asian Journal of Logistics Management Vol 3, No 2 (2024): Asian Journal of Logistics Management
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ajlm.2024.24671

Abstract

This paper examines the use of generative AI in human resource management (HRM), emphasizing the improvement of operational efficiency and decision-making processes. The study used a literature based approach, combining information from peer reviewed journals, books, research articles and industry reports to examine the adoption of AI into HR tasks, such as recruiting, employee engagement, and performance management. This research demonstrates that generative AI significantly enhances recruiting by decreasing the time to hire and more precisely matching applicants with job specifications. Moreover, AI-driven technologies strengthen employee engagement by personalizing interactions and automating routine tasks, enabling HR professionals to concentrate on key objectives.The study's uniqueness is in its thorough assessment of the ethical dilemmas and challenges related to generative AI, including algorithmic bias and privacy issues. To address these dangers, the study emphasizes the need to include justice and openness in AI deployment. The results indicate that while generative AI has the potential for significant efficiency improvements, ethical governance is essential for its appropriate use.For strategic workforce management, HR managers must use generative AI while also being aware of ethical constraints. However, there are certain limitations, such as relying solely on current literature and the potential biases inherent in these sources. Subsequent research needs to concentrate on empirical validation and the formulation of frameworks to direct ethical AI implementation in human resources. This paper offers a comprehensive view of the advantages and obstacles associated with the integration of generative AI in HRM, highlighting the need for responsible and balanced implementation.
The Impact of Organizational Culture on Innovative Work Behavior Mediating Role of Perceived Organizational Support in Indonesian Small and Medium Enterprises (SMEs) Khan, Muhammad Inzamam; Salendu, Alice; Azzahra, Fadia; Hussain, Shah
Journal of Psychological Perspective Vol 7, No 1 (2025)
Publisher : Utan Kayu Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/jopp.7110702025

Abstract

This study examines how organizational culture influences innovative work behavior (IWB) in Indonesian small and medium enterprises (SMEs), focusing on the mediating role of perceived organizational support (POS). A survey of 296 SME employees, with 185 valid responses analyzed, shows that a culture emphasizing collaboration, adaptability, and employee empowerment significantly enhances innovation. However, POS does not mediate this relationship, indicating that cultural factors have a more direct impact. These findings highlight the need for SME managers to foster a workplace that encourages creativity, risk-taking, and knowledge-sharing to enhance innovation capacity. By embedding these cultural elements, SMEs can improve competitiveness despite resource constraints. The study contributes to the broader understanding of SME innovation in non-Western contexts, offering practical insights for leaders aiming to build innovation-driven organizations. Strengthening organizational culture can serve as a strategic approach to drive sustainable growth and resilience in the dynamic business landscape.
Co-Authors Alice Salendu Azzahra, Fadia Endang Parahyanti Hussain, Shah