Journal of Human Resource Management Future Studies
Abstract: (211 Views)
Digital transformation in human resource management has accelerated adoption of biometric technologies in manufacturing organizations. This study investigates the effect of a smart biometric attendance system on employee performance, work autonomy, and privacy in a large Iranian manufacturing company (Saipa Automotive Parts Manufacturing Co., Tehran). The study adopts a future-oriented HRM perspective, examining technology-mediated performance outcomes.
Methodology:The research is applied in purpose and uses a descriptive-correlational design with quantitative data. The statistical population comprised 780 employees of the production and operations divisions. A sample of 258 was drawn via stratified random sampling. Data were collected through a validated questionnaire and analyzed using PLS-SEM (SmartPLS 4.0) and SPSS 27.
Findings: The biometric system significantly impacts: work quantity (β=0.738, t=25.91), work quality (β=0.672, t=16.84), punctuality (β=0.614, t=15.02), attendance (β=0.603, t=14.11), privacy perception (β=0.571, t=13.45), and work autonomy (β=0.543, t=10.12). All hypotheses were confirmed at the 95% confidence level. The model GOF index was 0.47.
Conclusion: Smart biometric systems, when implemented with transparency and participatory design, function as strategic HR levers that enhance performance, protect privacy, and promote employee autonomy. Future-oriented HRM should integrate biometric data with broader digital HR ecosystems for evidence-based people management.
Methodology:The research is applied in purpose and uses a descriptive-correlational design with quantitative data. The statistical population comprised 780 employees of the production and operations divisions. A sample of 258 was drawn via stratified random sampling. Data were collected through a validated questionnaire and analyzed using PLS-SEM (SmartPLS 4.0) and SPSS 27.
Findings: The biometric system significantly impacts: work quantity (β=0.738, t=25.91), work quality (β=0.672, t=16.84), punctuality (β=0.614, t=15.02), attendance (β=0.603, t=14.11), privacy perception (β=0.571, t=13.45), and work autonomy (β=0.543, t=10.12). All hypotheses were confirmed at the 95% confidence level. The model GOF index was 0.47.
Conclusion: Smart biometric systems, when implemented with transparency and participatory design, function as strategic HR levers that enhance performance, protect privacy, and promote employee autonomy. Future-oriented HRM should integrate biometric data with broader digital HR ecosystems for evidence-based people management.
Keywords: Biometric System, HR Technology, Employee Performance, Work Autonomy, Data Governance Transparency, Digital Transformation, Future HRM
Type of Study: Research |
Subject:
Special
Received: 2025/02/20 | Accepted: 2026/02/28 | Published: 2026/03/15
Received: 2025/02/20 | Accepted: 2026/02/28 | Published: 2026/03/15
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