Sarah Shaharruddin

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.

Aim/purpose – This study aims to develop a model of the relationships between job resources (autonomy, recognition), personal resources (self-efficacy), and work engage- ment among academic staff. Moreover, the moderation of job demand was also exam- ined in relation to the association between these constructs. Design/methodology/approach – In the context of survey research, 554 questionnaires were distributed using a simple random sampling technique in public secondary schools of seven districts across Punjab, Pakistan, out of which 398 questionnaires were consid- ered usable for the research. To analyze the data, the structural equation modeling meth- od was applied through PLS-SEM software. Findings – This study found that recognition and self-efficacy have a significant and positive impact on work engagement. Furthermore, the study revealed that academic staff’s work engagement was not significantly affected by job autonomy. Regarding the moderation analysis, no moderating effect was found on the association between job resources, self-efficacy, and work engagement. Research implications/limitations – This study contributes to the existing knowledge on the JDR model of work engagement and has several implications. The current study holds practical importance for individuals in all fields, especially those in the educational industry. It is recommended that future studies expand the relationship between these variables across a range of industries. Future research may consider other relevant fac- tors and longitudinal studies as alternatives to cross-sectional observational studies. Originality/value/contribution – This study makes a significant contribution to the work engagement literature by examining how job resources and self-efficacy affect work engagement while moderating job demands. To increase the work engagement of academic staff, this study presents a fresh approach to optimal management, enhancing the implementation of job and personal resources that increase work engagement. Keywords: Job resources, self-efficacy, job autonomy, recognition, job demand, work engagement. JEL Classification: M10, M12, M19

The Industry Revolution 4.0 (IR.4.0) presents a significant impact on work and lifestyle of most people in Malaysia especially in the banking industry. Industries that are adapting to advance technology such as VR (virtual reality), Internet of Things (IoT), cloud computing, data analytics, artificial intelligence and machine learning will bear changes through physical, digital and biological aspects. The banking industry will need to go through with these three aspects of transformation as its need to be relevant and quickly acquainted to serve their new customer demands besides protecting against risks in cybersecurity, fraud and money loundering in the financial transactions. In order for these banks to stay relevant, both employees and management must be able to bear the changes. To ensure the success in embracing the change, it is suggested in this paper that banks must use a new model of leadership to steer the institutions direction towards the right path and accelerate its transformation. There are four pillars comprises of disruptive driver, human touch, sense of urgency and continuous learning that will constitute the new leadership model called “Leadership 4.0” suggested to banks that will be discussed in this paper.

This article aims to foster an understanding of Industrial Revolution (IR) 4.0 and the opportunities and challenges it creates for online business. This study employed a qualitative approach using library research. Google Scholar and ResearchGate were used to collect and search past studies. The article selection process focused on relevant recent research and used keywords such as Online Business, Industrial Revolution (IR) 4.0, and Opportunities and Challenges in Online Business. Approximately 80 articles were found in the Emerald Insight database. The ProQuest database contained 20 articles, 100 articles were found in the Google Scholar database, and 10 articles were found in the ResearchGate database. Following the screening, 24 publications were chosen for further discussion. It was discovered that few studies had been conducted on this subject. The results revealed that internet-based companies will be assisted in developing their smartness and efficiency through IR 4.0, also known as the new industrial revolution. Organizations will be able to use data in real time within supply chains and economies that also operate in real time. They will become more sustainable and their operating conditions will improve, earning them the contemporary consumers’ trust and loyalty as they offer opportunities for personalization. Online companies were anticipated to grow tremendously because not only were easier and more convenient transactions permitted, but also significantly improved product offerings were made feasible by the IR 4.0 system. Online businesses should seize these opportunities and overcome the challenges to maximize their business performance. When examining the potential advancements, researchers have foreseen that IR 4.0 features both opportunities and challenges, although the opportunities to be gained far outweigh the challenges. Thus, further research should be conducted to gauge the impacts of the opportunities and challenges associated with IR 4.0, and a proper course of action should be suggested.