A Proposed Framework for The Relationship between Emotional Intelligence and Employee Performance among Nurses in Private Hospitals in Melaka: A Moderation Effect of Job Demands

A Proposed Framework for the Relationship between Emotional Intelligence and Employee Performance among Nurses in Private Hospitals in Melaka: A Moderation Effect of Job Demands

Noorzalyla Mokhtar^*, Wan Musyirah Wan Ismail., Muna Kameelah Sauid., Nurul Ain Mustakim

Universiti Teknologi MARA (UiTM)

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000654

Received: 30 September 2025; Accepted: 08 October 2025; Published: 25 October 2025

ABSTRACT

The quality of nursing care is pivotal to patient outcomes, hospital reputation, and, within the framework of a health-tourism economy, regional economic success. Emotional intelligence (EI) comprises personal abilities that empower nurses to accurately recognise, manage, and utilise emotions in clinical and interpersonal contexts. While worldwide research associate emotional intelligence with enhanced performance and reduced burnout in nurses, there is a paucity of studies examining this correlation especially within Malaysia’s private hospital sector, which directly engages both local patients and medical tourists. This conceptual paper provides a detailed framework demonstrating that emotional intelligence (including self-awareness, self-regulation, motivation, empathy, and social skills) positively impacts employee performance (encompassing task performance, contextual performance, and service-quality performance) among nurses in private hospitals in Melaka. The paper contextualizes the investigation within Melaka’s tourism and medical tourism sectors, formulates testable hypotheses, delineates operationalization and measurement methodologies, and examines theoretical, practical, policy, and economic ramifications—specifically how enhanced nursing performance can bolster Malaysia’s medical tourism competitiveness and GDP.

Keywords: Emotional Intelligence, Employee Performance, Job Demands, Nurses, Private Hospitals

INTRODUCTION

Health care is fundamentally a social and service-oriented sector, since clinical outcomes rely not alone on technical proficiency but also on interpersonal relationships, communication, and emotional labour. Nurses are the profession most frequently engaged with patients, responsible for ongoing monitoring, patient education, emotional support, and care coordination. In private hospitals, particularly those catering to fee-paying domestic and international clients, nursing performance is evaluated based on clinical precision as well as service quality, communication, and patient-centered care.

Malaysia has aggressively sought to enhance medical tourism as a component of its larger economic diversification plans. States with robust tourist profiles, such as Melaka, occupy a distinctive confluence of leisure tourism and healthcare services. Melaka has had significant visitor numbers in recent years (Malaysia Tourism Key Performance Indicators 2023, 2024) and caters to both domestic visitors and medical travellers seeking elective procedures, diagnostics, or recuperative care. In this market-oriented context, patient perceptions of service quality are crucial; they affect immediate satisfaction, word-of-mouth referrals, and long-term repeat visits, all of which contribute to private hospital income and the broader local tourism economy.

Emotional intelligence (EI) is widely acknowledged as a human resource that influences the quality of interpersonal interactions in emotionally intense work environments. Emotional Intelligence (EI), originating in psychology (Mayer & Salovey, 1993) and popularised in practical applications (Goleman, 1995), denotes the capacity to properly sense emotions, utilise emotions to enhance cognitive processes, understand emotional information, and manage emotions in oneself and others. In nursing, emotional intelligence facilitates compassionate care, effective communication under pressure, and resilience over extended shifts—behaviors that likely correlate with improved staff performance and patient outcomes (Codier et al., 2011; Chao Miao et al., 2017a).

Despite the theoretical and empirical discussions, there is a lack of study focussing on private hospitals in Malaysian states such as Melaka, where medical tourism converges with local healthcare services. The majority of research concentrate on public hospitals or collective healthcare workforces. Considering the market orientation of private hospitals, where patient experience is directly correlated with competitive positioning, comprehending the role of emotional intelligence in enhancing nurse performance in this context is both academically significant and practically imperative.

This research proposes a conceptual framework that connects emotional intelligence and employee performance among nurses in private hospitals in Melaka. It formulates explicit hypotheses, delineates construct dimensions and measurement methodologies, and recognises possible mediators and moderators (e.g., work demands, organisational support, job security) that may influence the EI–performance link. The paper delineates implications for hospital management, policymakers, and the local economy, contending that focused emotional intelligence development for nurses serves as an effective mechanism for enhancing service quality, bolstering Melaka’s medical tourism appeal, and augmenting GDP through elevated healthcare and tourism revenues.

Problem Statement And Research Gap

Private hospitals in Malaysia function within a competitive service economy where patient happiness and reputation provide significant revenue disparities. Nurses have a pivotal role in the patient experience; nevertheless, several human resource strategies in private hospitals emphasise technical skills at the expense of socio-emotional abilities. This oversight may restrict hospitals’ capacity to provide the service experiences anticipated by foreign medical tourists and discerning local patients. Empirical research has demonstrated correlations between emotional intelligence (EI) and workplace outcomes worldwide Miao et al., (2017b), while particular nursing literature associates EI with reduced burnout, enhanced patient satisfaction, and increased team performance Codier et al., (2011). Nonetheless, studies that specifically investigate the emotional intelligence-performance relationship among nurses in Malaysian private hospitals, particularly within the context of medical tourism and its local economic effects, are scarce. The study need includes (1) contextualised information for private hospitals in Melaka, (2) integrated models connecting emotional intelligence to service quality performance indicators esteemed by medical tourists, and (3) practical suggestions for human resources and policy that correspond with economic objectives pertaining to medical tourism. This conceptual study identifies these deficiencies by presenting a thorough, testable framework and practical methods for empirical validation.

LITERATURE REVIEW

Emotional Intelligence: Definitions and Dimensions

Emotional intelligence has been defined through several models. Mayer & Salovey, (1993) conceptualised emotional intelligence as a collection of cognitive-emotional competencies: the perception of emotions, the use of emotions to enhance cognition, the comprehension of emotional significance, and the regulation of emotions. Goleman, (1990) presented an expansive, competency-oriented framework highlighting self-awareness, self-regulation, motivation, empathy, and social skills. Bar-On R., (2006) paradigm emphasises emotional and social qualities that facilitate adaptive functioning. The competence method in nursing research is intuitive since it immediately correlates with observable behaviours such as empathetic communication, emotional management in crises, and collaborative social engagement.

Self-awareness denotes the acknowledgement of one’s emotional states and the consequences of those feelings on behaviour (Goleman, 1995). In nursing, self-awareness enables carers to recognise exhaustion, dissatisfaction, or emotional contagion that may compromise clinical decision-making (Codier et al., 2011).

Self-regulation refers to the ability to manage emotions; nurses exhibiting robust self-regulation maintain composure in situations and avert emotional responses that might compromise patient care (Bar-On R., 2006).

Motivation includes internal drive and perseverance, which are crucial in high-pressure healthcare settings where frequent pressures may dissuade personnel.

Empathy is the capacity to comprehend and connect with patients’ emotions, serving as a strong indicator of patient happiness and compliance.

Social skills encompass proficient interpersonal communication, conflict resolution, and collaboration—elements that facilitate coordination in multidisciplinary treatment (C Miao et al., 2021).

Employee Performance in Nursing: Operational Dimensions

Nursing performance should be conceptualized beyond technical competence. The literature commonly distinguishes:

• Task performance: competence in technical duties—med administration, monitoring, documentation (Motowidlo et al., 1997).
• Contextual performance: discretionary behaviors such as teamwork, initiative, and organizational citizenship behaviors that support the social and psychological environment of care (Organ, 1994).
• Service-quality performance: patient-facing behaviors—communication clarity, empathy, responsiveness—that shape patient perceptions and satisfaction (Ferreira D et al., 2023).

In private hospitals, the performance of service quality may have significant economic implications: enhanced patient satisfaction elevates hospital ratings and referrals, which are essential for attracting medical tourism (Ai et al., 2022).

Empirical Evidence Linking EI and Performance in Nursing

Meta-analytic findings demonstrate a modest positive correlation between emotional intelligence and job performance across many occupations, with more pronounced impacts in positions requiring emotional labour (Chao Miao et al., 2017a). Nursing-specific research corroborates these findings: (Codier et al., 2011) indicated that emotional intelligence (EI) correlates with leadership efficacy and nursing performance in clinical environments; other studies demonstrate EI’s inverse association with burnout and turnover intentions  (Galanis et al., 2024; Zakaria et al., 2022). Empathy and communication, fundamental components of emotional intelligence, reliably forecast patient satisfaction metrics (Atta et al., 2024).

Nonetheless, empirical findings differ according on context and measurement. Self-report emotional intelligence scales may yield exaggerated correlations due to common-method variation; ability-based assessments (e.g., MSCEIT) and multi-source performance evaluations (supervisor, peer, patient) offer more reliable conclusions (Joseph & Newman, 2010). This methodological distinction guides the measurement suggestions in following sections.

Theoretical Integration: Job Demands–Resources and Social Exchange Theories

The Job Demands–Resources (JD-R) paradigm asserts that job resources, including human resources such as emotional intelligence, mitigate the negative impact of job demands and enhance engagement and performance (Bakker, A. B., & Demerouti, 2016). Emotional intelligence serves as a personal asset that enables nurses to reassess difficult situations, utilise emotions effectively, and sustain involvement—ultimately enhancing performance.

Social Exchange Theory (Cropanzano & Mitchell, 2005) posits that emotionally intelligent nurses cultivate trust, reciprocity, and collaborative norms with patients and colleagues, hence facilitating positive exchanges and enhanced performance. Collectively, these frameworks elucidate the direct and indirect mechanisms by which emotional intelligence may influence performance.

Context: Melaka, Medical Tourism, and Economic Relevance

The tourism profile and healthcare infrastructure of Melaka provide a significant setting for this investigation. Tourism Malaysia and state-level data reveal substantial visitor traffic, with the state drawing considerable domestic tourism and functioning as a destination for regional travellers (Tourism Malaysia, 2024). The medical tourism revenue of Malaysia, projected to be in the hundreds of millions of USD according to recent post-pandemic studies (“Medical Tourism in Malaysia,” 2025), underscores the economic significance of the sector. The contribution of health services to GDP emphasises the sector’s macroeconomic significance. In Melaka’s private hospitals, favourable patient experiences—primarily influenced by nursing care—result in reputation impacts that are vital for recruiting medical tourists, who significantly depend on perceived service quality and interpersonal care when choosing a destination (Connell, 2013). Consequently, enhancements in nurse performance generated by emotional intelligence are both clinically significant and economically impactful.

Identified Gaps and Rationale for the Present Conceptual Paper

This conceptual work is driven by two primary gaps. Firstly, there exists a paucity of context-specific information about private hospitals in Malaysian tourist destinations such as Melaka, particularly concerning the relationship between emotional intelligence and service quality performance as assessed by medical tourists. Secondly, current research often depends on cross-sectional designs utilising single-source data; it is essential to establish rigorous measurement and analytical methodologies (such as multi-source performance evaluations, longitudinal studies, or SEM techniques) to elucidate causal and moderated linkages. This research addresses these deficiencies by (a) offering a comprehensive conceptual model specifically designed for the private hospital and medical tourism environment and (b) delineating operational measurements and methodological techniques suitable for rigorous empirical evaluation.

Conceptual Framework And Hypotheses

Conceptual Model Overview

The proposed model posits Emotional Intelligence (EI) as the antecedent variable influencing Employee Performance among nurses, assessed across task, contextual, and service-quality dimensions. The model includes moderators (job demand, workload and emotional demands) that refine the EI–performance relationship. Job demands, including workload, time constraints, and emotional strain, impose constant pressure on nurses, frequently resulting in stress and burnout. In this framework, we proposed that job demands moderate the relationship between EI and nurses’ performance, whereby nurses with EI are better equipped to navigate difficult scenarios, maintain motivation, and uphold their performance standards under elevated job demands, while those with low EI are more prone to a decline in performance as job demands rise. We also proposed that physical demands influence the correlation between EI and nurses’ performance, whereby nurses with elevated EI exhibit greater resilience and sustain performance despite substantial workloads and extended hours, whereas those with diminished EI are inclined to fatigue and performance decline under significant physical demands.

Figure 1: Propose Conceptual Framework

Hypotheses

Based on the literature, the following hypotheses are proposed:

H1: Emotional intelligence is positively related to total employee performance among nurses in private hospitals in Melaka.

H1a: EI is positively related to task performance.

H1b: EI is positively related to contextual performance.

H1c: EI is positively related to service-quality performance.

H2: Job demands (workload, emotional demands) moderate the EI–performance link such that the positive effect of EI on performance is stronger under higher job demands (buffering effect).

Operationalization And Measurement

Emotional Intelligence (IV)

Instrument options:

The Wong and Law Emotional Intelligence Scale (WLEIS) is a prevalent self-report instrument with four dimensions: self-emotion evaluation, others’ emotion appraisal, use of emotion, and management of emotion. Beneficial for facilitating administration and ensuring comparability (Wong & Law, 2002).

The Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) is an ability-based assessment that mitigates self-report bias; nevertheless, it necessitates licensure and has a longer administration duration (Mayer et al., 2001).

Recommendation: Employ a hybrid methodology where feasible—utilizing WLEIS for extensive sample administration alongside a selection of MSCEIT questions or performance-based vignettes for a validation subsample. This reconciles practicality with measurement precision.

Employee Performance (DV)

Utilising several sources for measurement is essential to mitigate common-method bias. Contemplate the subsequent:

• Supervisor-evaluated task performance (e.g., standardised nurse performance checklists).
  • Peer-evaluated contextual performance (collaboration, altruistic behaviours).
• Patient-assessed service quality performance utilising proven tools (e.g., SERVQUAL adapted for healthcare, patient satisfaction surveys emphasising communication and empathy).
• Quantifiable measures, where accessible: rates of medication errors, punctuality of paperwork, and frequency of patient complaints.

Integrate these sources into a latent performance construct inside structural equation modelling (SEM) to encapsulate its multi-dimensionality.

Moderators

Job demands: measure via scales capturing workload, emotional labor, and shift intensity.

Control Variables

Control for demographic and job-related factors: age, tenure, education level, shift type, unit specialty (ICU vs. general ward), and prior EI training. For analyses involving medical-tourism outcomes, control for patient case-mix and hospital size.

Data Collection Methods

• Sample: nurses from multiple private hospitals in Melaka (aim for stratified sampling across hospitals and clinical units). A sample size of n ≥ 300 is desirable for SEM (Kline, 2016), with a smaller validation subsample for ability-based EI testing.
• Ethics: obtain institutional ethics approval and ensure patient data de-identification. Participation should be voluntary with informed consent.
• Timing: consider a two-wave design (predictors and mediators at Time 1; performance outcomes at Time 2, 3 months later) to strengthen causal inference.

Proposed Data Analysis

Initial analyses: Descriptive statistics, reliability (Cronbach’s α, composite reliability), exploratory confirmatory factor analysis to evaluate concept validity.

Measurement model: Employ confirmatory factor analysis (CFA) to validate the dimensions of emotional intelligence and the multi-source performance construct. Model task, contextual, and service quality as first-order variables, with a second-order latent performance factor for performance evaluation.

Hypothesis testing: Employ Structural Equation Modelling (SEM) to evaluate direct relationships (EI → performance), and moderation (utilising interaction terms or multi-group SEM for high vs low job demands).

Robustness assessments: Multi-source cross-validation; juxtapose outcomes of self-reported performance only against multi-source composites; conduct sensitivity analyses for hospital-level clustering (multilevel SEM) to accommodate nested data.

Qualitative triangulation (optional): Conduct semi-structured interviews with a purposive sample of nurses and managers to provide contextual insights on the manifestation of emotional intelligence in private hospitals in Melaka and to identify institution-specific training methods or obstacles.

Expected Contributions

Theoretical contributions: This study enhances emotional intelligence literature by contextualising the emotional intelligence–performance correlations within a private hospital, medical tourism framework, examining mediating mechanisms (engagement/exhaustion) and boundary conditions (job expectations, organisational support). It amalgamates the JD-R model with Social Exchange Theory within a specialised healthcare context.

Practical contributions: The findings will direct HR and training priorities by informing EI-based selection, specialised EI training programs (such as emotion regulation and empathic communication workshops), and managerial practices that enhance the translation of EI into performance (for instance, organisational support mechanisms).

Demonstrated correlations between nurse emotional intelligence, service quality performance, and patient happiness provide practical strategies for policymakers seeking to improve the competitiveness of medical tourism. Enhanced service experiences might augment medical tourism revenues and stimulate local economic activity, so bolstering state-level development objectives in Melaka.

Limitation And Deliminations

Limitations: As a conceptual work, empirical assertions are speculative until substantiated; measurement obstacles (self-report bias) and causal inference concerns must be resolved through multi-source methodologies and longitudinal designs. The generalisability may be confined to private hospital systems in tourist-centric states and may not immediately apply to public hospitals or non-tourist areas.

Delimitations: The research concentrates on registered nurses in private hospitals in Melaka, excluding allied health workers. It focusses on emotional intelligence as an individual asset, whereas organisational culture and structural resource limitations are considered as modifiers, but not comprehensively modelled.

Research Implications (Policy, Practice And Future Research)

Policy: Policymakers ought to contemplate the incorporation of emotional intelligence abilities into national nursing standards and ongoing professional development frameworks. Accreditation criteria for private hospitals may incorporate patient-experience measures associated with nursing performance, so promoting the development of emotional intelligence.

Hospital administrators ought to execute multifaceted interventions: (1) emotional intelligence assessments during recruitment, complemented by clinical evaluations, (2) tiered emotional intelligence training modules ranging from fundamental empathic communication to advanced emotion regulation, and (3) organisational support systems, including peer debriefings, clinical supervision, and manageable shift patterns, that facilitate nurses in converting emotional intelligence into sustained performance.

Economic: In Melaka and similar states, public–private collaborations that enhance service-quality standards for medical tourism can bolster destination brand equity. Hospitals that record enhanced patient satisfaction resulting from EI programs might promote these benefits to overseas agents and insurers.

Future research should implement longitudinal and multilevel designs to empirically compare public and private settings, assess cross-cultural generalisability across Malaysian states (specifically Melaka and Kuala Lumpur), and evaluate economic impacts, such as the incremental medical-tourism revenue linked to quantifiable enhancements in patient satisfaction resulting from improved nursing performance.

CONCLUSION

The emotional intelligence of nurses is a significant, albeit underutilised, opportunity to improve staff performance in both clinical and service aspects, particularly in private hospitals competing for medical tourism clients. This conceptual study integrates theoretical and empirical evidence to present a comprehensive model connecting emotional intelligence to multi-dimensional nursing performance, mediated by engagement and emotional tiredness, and modulated by job demands and perceived organisational support. The suggested research, utilising rigorous measurement (multi-source performance indicators) and suitable analytic methodologies (SEM, longitudinal design), can provide actionable insights for hospital management and policymakers. In Melaka, a state with considerable tourism activity, investments in nurse emotional intelligence are not solely clinical or human resources initiatives; they represent strategic economic interventions capable of enhancing patient experiences, bolstering hospital reputations, and positively impacting Malaysia’s medical tourism performance and GDP.

REFERENCES

1. Ai, Y., Rahman, M. K., Newaz, M. S., Gazi, M. A. I., Rahaman, M. A., Mamun, A. Al, & Chen, X. (2022). Determinants of patients’ satisfaction and trust toward healthcare service environment in general practice clinics. Frontiers in Psychology, 13(856750), 1–19.
2. Atta, M. H. R., Hammad, H. A. H., & Elzohairy, N. W. (2024). The role of Empathy in the relationship between emotional support and caring behavior towards patients among intern nursing students. BMC Nursing, 23(1), 1–12. https://doi.org/10.1186/s12912-024-02074-w
3. Bakker, A. B., & Demerouti, E. (2016). Job Demands-Resources Theory : Taking Stock and Looking Forward Job Demands – Resources Theory : Taking Stock and Looking Forward. 22(September 2018), 273–285.
4. Bar-On R. (2006). The Bar-On model of emotional-social intelligence (ESI). Psicothema, 18, 13–25.
5. Codier, E., Muneno, L., & Freitas, E. (2011). Emotional intelligence abilities in oncology and palliative care. Journal of Hospice and Palliative Nursing, 13(3), 183–188. https://doi.org/10.1097/NJH.0b013e31820ce14b
6. Connell, J. (2013). Contemporary medical tourism: Conceptualisation, culture and commodification. Tourism Management, 34, 1–13. https://doi.org/10.1016/j.tourman.2012.05.009
7. Cropanzano, R., & Mitchell, M. S. (2005). Social exchange theory: An Interdisciplinary review. Journal of Management, 31(6), 874–900. https://doi.org/10.1177/0149206305279602
8. Ferreira D, Vieira I, Pedro M, Caldas P, & Varela M. (2023). Patient Satisfaction with Healthcare Services and the Techniques Used for its Assessment: A Systematic Literature Review and a Bibliometric Analysis. Healthcare (Switzerland) [revista en Internet] 2023 [acceso 8 de octubre de 2023]; 11(5): 1-31. Healthcare Review, 21(2), 693. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001171/pdf/healthcare-11-00639.pdf
9. Galanis, P., Katsiroumpa, A., Moisoglou, I., Kalogeropoulou, M., Gallos, P., & Vraka, I. (2024). Emotional intelligence protects nurses against quiet quitting, turnover intention, and job burnout. AIMS Public Health, 11(2), 601–613. https://doi.org/10.3934/publichealth.2024030
10. Goleman, D. (1990). Emotional Intelligence : Issues in Paradigm Building. 1–13.
11. Goleman, D. (1995). Emotional Intelligence: Why It Can Matter More Than IQ (25th Anniv). Bantam Books.
12. Joseph, D. L., & Newman, D. A. (2010). Emotional Intelligence: An Integrative Meta-Analysis and Cascading Model. Journal of Applied Psychology, 95(1), 54–78. https://doi.org/10.1037/a0017286
13. Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling, Fourth Edition. In The Guilford Press (Vol. 8, Issue 5).
14. Malaysia Tourism Key Performance Indicators 2023. (2024).
15. Mayer, J., & Salovey, P. (1993). The intelligence of emotional intelligence. INTELLIGENCE, 17, 433–442. https://www.sciencedirect.com/science/article/pii/0160289693900103
16. Mayer, J., Salovey, P., Caruso, D., & Sitarenios, G. (2001). Emotional intelligence as a standard intelligence. https://psycnet.apa.org/journals/emo/1/3/232.html?uid=2001-10055-002
17. Medical Tourism in Malaysia. (2025). Frost & Sullivan: Business Circle, 1–7. http://www.businesscircle.com.my/medical-tourism-in-malaysia/
18. Miao, C, Humphrey, R. H., & Qian, S. (2021). Emotional Intelligence and Job Performance in the Hospitality Industry Miao, C., Humphrey, R. H., & Qian, S. (in press, 2021). Emotional Intelligence and Job Performance in the Hospitality Industry: A Cross-Cultural Qualitative and Quantitative Review. https://doi.org/10.1108/IJCHM-04-2020-0323
19. Miao, Chao, Humphrey, R. H., & Qian, S. (2017a). A meta-analysis of emotional intelligence and work attitudes. Journal of Occupational and Organizational Psychology, 90(2), 177–202. https://doi.org/10.1111/joop.12167
20. Miao, Chao, Humphrey, R. H., & Qian, S. (2017b). A meta-analysis of emotional intelligence effects on job satisfaction mediated by job resources, and a test of moderators. Personality and Individual Differences, 116, 281–288. https://doi.org/10.1016/j.paid.2017.04.031
21. Motowidlo, S. J., Borman, W. C., & Schmit, M. J. (1997). Motowidlo & Borman (1997).pdf. In Human Performance (Vol. 10, Issue 2, pp. 71–83).
22. Organ, D. W. (1994). Personality and Organizational Citizenship Behavior. Journal of Management, 20(2), 465–478. https://doi.org/10.1177/014920639402000208
23. Wong, C. S., & Law, K. S. (2002). The effects of leader and follower emotional intelligence on performance and attitude: An exploratory study. Leadership Quarterly, 13(3). https://doi.org/10.1016/S1048-9843(02)00099-1
24. Zakaria, N., Zakaria, N. H., Bin Abdul Rassip, M. N. A., & Lee, K. Y. (2022). Burnout and coping strategies among nurses in Malaysia: a national-level cross-sectional study. BMJ Open, 12(10). https://doi.org/10.1136/bmjopen-2022-064687