An Interactive Mobile Human Resource Management Platform Based on Affective Computing and Dynamic Causal Modeling.

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Bibliographic Details
Title:	An Interactive Mobile Human Resource Management Platform Based on Affective Computing and Dynamic Causal Modeling.
Authors:	Li, Xijin¹ p130010@siswa.ukm.edu.my, Hanafiah, Mohd Hizam¹ mhhh@ukm.edu.my
Source:	International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 10, p143-156. 14p.
Subjects:	Affective computing, Causal models, Distributed computing, Privacy, Personnel management, Job performance, Mobile operating systems, Employee psychology
Abstract:	Traditional human resource management approaches rely on low-frequency, questionnairebased methods to capture employee emotional states, whereby elevated risks of privacy leakage are introduced and the relationships between emotion and performance are statistically modeled. Such limitations hinder adaptation to the evolving demands of mobile-enabled management environments. Leveraging the portability of mobile devices and the heterogeneity of embedded sensors, an interactive mobile human resource management platform based on affective computing was proposed. To address the requirements of mobile scenarios, an integrated technical framework combining edge-cloud collaboration and dynamic causal inference was constructed. Three critical challenges were addressed, including the lightweight deployment of affective computing models on edge devices, privacy-preserving mechanisms for sensitive data, and the dynamic modeling of causal relationships among employee emotional responses, work engagement, and performance outcomes. A robust technical paradigm is thus provided for the intelligent upgrading of mobile human resource management systems, while new research directions are established for the interdisciplinary integration of affective computing and mobile office systems. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Traditional human resource management approaches rely on low-frequency, questionnairebased methods to capture employee emotional states, whereby elevated risks of privacy leakage are introduced and the relationships between emotion and performance are statistically modeled. Such limitations hinder adaptation to the evolving demands of mobile-enabled management environments. Leveraging the portability of mobile devices and the heterogeneity of embedded sensors, an interactive mobile human resource management platform based on affective computing was proposed. To address the requirements of mobile scenarios, an integrated technical framework combining edge-cloud collaboration and dynamic causal inference was constructed. Three critical challenges were addressed, including the lightweight deployment of affective computing models on edge devices, privacy-preserving mechanisms for sensitive data, and the dynamic modeling of causal relationships among employee emotional responses, work engagement, and performance outcomes. A robust technical paradigm is thus provided for the intelligent upgrading of mobile human resource management systems, while new research directions are established for the interdisciplinary integration of affective computing and mobile office systems. [ABSTRACT FROM AUTHOR]
ISSN:	18657923
DOI:	10.3991/ijim.v20i10.61941