Hui Guan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Hui Guan has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
- Sarah Shaharruddin
School of Business Management (College of Business), Universiti Utara Malaysia
1 shared publication - Siti Norasyikin Abdul Hamid
School of Business Management (College of Business), Universiti Utara Malaysia
1 shared publication
Latest Publications
- Open Access
- 12 May 2026
- Published by Editora Alumniin in Journal of Sustainable Competitive Intelligence
- Vol. 16, e0665
From Conflict to Intelligence a Competitive Intelligence Framework for Predicting Employee Turnover Intention
Purpose: This study develops and empirically validates a Predictive Human Capital Intelligence (PHCI) framework that treats interpersonal conflict not merely as an organizational behavior problem but as a competitive intelligence signal for detecting human capital risk. The study examines whether a formal CI architecture—based on signal collection, behavioral pattern analysis, dissemination to decision-makers, and preventive use—can predict and reduce employee turnover intention before conflict escalates into emotional exhaustion. Design/methodology/approach: A quantitative cross-sectional design collected data from 312 knowledge workers across information technology, financial services, telecommunications, and consulting industries. Moderated-mediation structural equation modeling (SEM) with bootstrapping (5,000 resamples) tested whether CI orientation—operationalized as systematic collection, analysis, dissemination, and use—attenuates the conflict–exhaustion pathway and channels task conflict toward retention. Findings: Relationship conflict functioned as a valid predictive intelligence signal (β = 0.542, p < 0.001). Emotional exhaustion served as the diagnostic threshold at which the signal converts to strategic risk (indirect β = 0.333, VAF = 64.5%). The CI intelligence system attenuated the signal–risk relationship by 36.5% (β = −0.284, p < 0.001). Task conflict reduced turnover intention exclusively under high CI conditions (β = −0.391, p < 0.001), demonstrating intelligence-mediated channeling. Originality/Relevance: This study extends CI theory from external market analysis to internal human capital risk prediction, introduces PHCI as a formal CI domain, operationalizes the complete intelligence cycle for behavioral signals, and provides empirical evidence that CI systems function as scalable, institutionalizable mechanisms for workforce risk prevention. This research also reframes turnover intention as a predictable breakdown in human capital intelligence, shifting from reactive attrition analysis to proactive interception. By repositioning interpersonal conflict as an intelligence input and CI orientation as a system-level organizational capability, the study advances JSCI scholarship beyond external market intelligence toward internal competitive intelligence for human capital risk prevention.
- 12 May 2026
- Published by Editora Alumniin in Journal of Sustainable Competitive Intelligence
- Vol. 16, e0665
Open AccessFrom Conflict to Intelligence a Competitive Intelligence Framework for Predicting Employee Turnover Intention
Purpose: This study develops and empirically validates a Predictive Human Capital Intelligence (PHCI) framework that treats interpersonal conflict not merely as an organizational behavior problem but as a competitive intelligence signal for detecting human capital risk. The study examines whether a formal CI architecture—based on signal collection, behavioral pattern analysis, dissemination to decision-makers, and preventive use—can predict and reduce employee turnover intention before conflict escalates into emotional exhaustion. Design/methodology/approach: A quantitative cross-sectional design collected data from 312 knowledge workers across information technology, financial services, telecommunications, and consulting industries. Moderated-mediation structural equation modeling (SEM) with bootstrapping (5,000 resamples) tested whether CI orientation—operationalized as systematic collection, analysis, dissemination, and use—attenuates the conflict–exhaustion pathway and channels task conflict toward retention. Findings: Relationship conflict functioned as a valid predictive intelligence signal (β = 0.542, p < 0.001). Emotional exhaustion served as the diagnostic threshold at which the signal converts to strategic risk (indirect β = 0.333, VAF = 64.5%). The CI intelligence system attenuated the signal–risk relationship by 36.5% (β = −0.284, p < 0.001). Task conflict reduced turnover intention exclusively under high CI conditions (β = −0.391, p < 0.001), demonstrating intelligence-mediated channeling. Originality/Relevance: This study extends CI theory from external market analysis to internal human capital risk prediction, introduces PHCI as a formal CI domain, operationalizes the complete intelligence cycle for behavioral signals, and provides empirical evidence that CI systems function as scalable, institutionalizable mechanisms for workforce risk prevention. This research also reframes turnover intention as a predictable breakdown in human capital intelligence, shifting from reactive attrition analysis to proactive interception. By repositioning interpersonal conflict as an intelligence input and CI orientation as a system-level organizational capability, the study advances JSCI scholarship beyond external market intelligence toward internal competitive intelligence for human capital risk prevention.