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Abstract

This study presents a comprehensive bibliometric analysis of emotional exhaustion (EE) research to uncover its intellectual structure, evolving trends, thematic clusters, and collaborative networks. A total of 3,667 peer-reviewed articles published between 1978 and 2024 were retrieved from the Scopus database. Using bibliographic coupling, co-authorship, and keyword co-occurrence analyses, the study maps the development of EE research and identifies influential contributors and thematic concentrations. The findings reveal consistent growth in publication volume and impact, with a 21% compound annual growth rate. Five key research clusters emerged: psychological and behavioral factors, mediators in EE research, antecedents of EE in education and health care, theoretical perspectives on EE, and emotional labor and its Link to EE. The United States and China are highlighted as leading collaborators in the field. This is the first bibliometric study to integrate multiple analytic techniques, offering a unique lens into the EE research landscape and proposing a structured agenda for future inquiry.

Keywords

Emotional exhaustion bibliometric analysis performance analysis science mapping

Introduction

Workplace stress has escalated significantly in recent years due to the compounded effects of the COVID-19 pandemic, growing economic and social pressures, and increasing technological fatigue. These challenges have led to a noticeable decline in employee well-being, contributing to rising levels of anxiety, job burnout, and emotional exhaustion (Allgood et al., 2024; Lim et al., 2024; World Health Organization, 2022). Recent evidence also shows that AI-driven job insecurity and hybrid work changes have amplified EE among employees across multiple sectors (Lanchimba et al., 2025; Zheng & Zhang, 2025). Burnout, as originally defined by Maslach and Jackson (1981), is the result of chronic, unresolved occupational stress. Recognizing its severity, the World Health Organization (2019) classified burnout as an “occupational phenomenon” in the 11th revision of the International Classification of Diseases. Among the components of burnout, emotional exhaustion (EE) is widely regarded as the core dimension, characterized by a depletion of psychological and emotional resources in response to sustained occupational demands (Maslach et al., 2001; Yavas et al., 2008).

EE encompasses persistent feelings of energy depletion and emotional fatigue, often arising from continuous exposure to intense psychological stressors (Chen & Chen, 2012; Kim et al., 2009). It is typically the first and most prominent manifestation of burnout, preceding both behavioral and affective dysfunctions (Cordes & Dougherty, 1993; Grobelna, 2021; Maslach & Leiter, 2017). As such, a deeper understanding of the emotional and physical fatigue experienced by frontline employees, and its organizational implications, is critically important (Saleh et al., 2023). This issue has gained prominence among scholars and organizational leaders alike, particularly in the context of public health crises, where EE intersects with phenomena such as compassion fatigue and change fatigue (Beaulieu et al., 2023; Chaves-Montero et al., 2025; Orgambídez et al., 2025). Moreover, EE has been linked to turnover intentions and diminished business performance across sectors, including health care, SMEs, and social work, underscoring its widespread economic and organizational impact (Chaves-Montero et al., 2025; Lanchimba et al., 2025; Zhang et al., 2025). Presently, excessive workloads, coupled with entrenched structural challenges, such as understaffing, rotating shifts, voluntary overtime, and erratic schedules, have contributed the pervasive nature of EE in modern workplaces (Woo et al., 2020).

EE is a widespread and largely unavoidable condition that affects employees at all organizational levels, from frontline staff to top management (Ejaz et al., 2025; Saleh et al., 2023). It often emerges in emotionally charged work environments where the psychological demands placed on individuals exceed their capacity to cope (Ducharme et al., 2007; Xu et al., 2017). Moreover, EE is a key antecedent to a range of counterproductive workplace behaviors, including incivility, aggression, deviant behavior, cyberloafing, and even violence (Liu et al., 2023; Wong et al., 2023). Recent research also highlights that toxic leadership, job insecurity, and lack of organizational justice exacerbate these effects, particularly in nursing and education sectors (Ahmed et al., 2024; Lim et al., 2024; Zhang et al., 2025).

From the employees’ perspective, EE is associated with a variety of physical health issues, such as frequent colds, gastrointestinal problems, sleep disturbances, headaches, fatigue, emotional depletion, and heightened irritability (Belcastro, 1982; Khan et al., 2014). It may also manifest in psychological distress, including depression, anxiety, and anger, which can, in extreme cases, lead to maladaptive coping mechanisms such as substance abuse and dependency (Burke, 1987; Kahill, 1988; Pines & Maslach, 2006). Emotionally exhausted individuals often describe a profound sense of depletion, expressing that they feel as though they have “no energy left” or are “at the end of their rope” (Schaufeli & Enzmann, 1998). The timely recognition of these symptoms is essential not only for safeguarding individual well-being but also for maintaining organizational health and performance (Cherniss, 1980; Cordes & Dougherty, 1993).

Considering the extensive psychological, physiological, and organizational consequences of EE, it is imperative to synthesize existing knowledge and identify emerging patterns within this expanding field of inquiry. Despite a surge of studies in 2024–2025 on digitalization, leadership, and moral distress as drivers of EE, the literature remains fragmented and often industry-specific (Chaves-Montero et al., 2025; Orgambídez et al., 2025; Zheng & Zhang, 2025). Consequently, this study undertakes a comprehensive bibliometric analysis to uncover the dominant research trends, thematic concentrations, and collaborative structures shaping the EE discourse. By mapping the evolution of scholarly contributions, this research aims to provide a consolidated knowledge base and a forward-looking research agenda for academics and practitioners seeking to address the escalating challenges of EE in contemporary workplaces.

The Rationale of the Study

While EE has garnered increasing scholarly attention in recent years, a consolidated and systematic understanding of its knowledge structure remains absent. Much of the existing research has been conducted through systematic literature reviews (Chaves-Montero et al., 2025; McFarland & Hlubocky, 2021; Orgambídez et al., 2025; Seidler et al., 2014) and meta-analyses, often focusing on specific occupational groups such as health care workers and educators (Edmondson et al., 2019; Kenworthy et al., 2014). More recent studies have also highlighted the rising impact of EE in the context of hybrid work models, digital transformation, and post-pandemic workplace stress (Lim et al., 2024; Zheng & Zhang, 2025). However, these studies remain fragmented and largely sector-specific, making it difficult to obtain a holistic view of the field.

Bibliometric studies have similarly addressed broader constructs such as burnout and mental fatigue but have seldom examined EE as a distinct research domain (Cecilia-Martín et al., 2020; Chen et al., 2023; Rua et al., 2023, pp. 119–149). As a result, there remains a notable gap in understanding the intellectual foundations, evolving themes, and social dynamics that shape EE research. This study aims to address these gaps by conducting the first dedicated bibliometric analysis of EE. In contrast to previous efforts, which often lack a cross-disciplinary perspective or fail to capture the field’s temporal development, this research provides a comprehensive mapping of EE’s publication trends, influential contributions, collaborative networks, and thematic clusters. By focusing on both the intellectual structure (key theories, concepts, and knowledge flows) and the social structure (author collaborations, institutional and country-level partnerships), the study offers a more integrated view of the field. It not only synthesizes past research but also identifies dominant themes and emerging research fronts, offering a strategic agenda for future inquiries. Ultimately, this study responds to the growing need for a cohesive framework to guide scholars, practitioners, and policymakers in addressing the increasing prevalence of EE in contemporary workplaces.

What are the annual publication and citation trends in EE research?

What are the most influential articles and journals in this field?

What are the intellectual and social structures in the area?

What are the key themes and possible avenues for future investigation in this area?

Methodology

This study employed bibliometric techniques to map the landscape of research on EE. Bibliometric analysis offers valuable insights into the evolution of academic domains, considering their intellectual, social, and conceptual dimensions (Zupic & Čater, 2015). Scopus and Web of Science (WoS) are among the most widely used databases for bibliometric research due to their broad disciplinary coverage (Waltman, 2016). Based on the recommendations of Donthu et al. (2021) and Mikul and Mittal (2024), this study relied on a single, appropriate database to avoid the complexities of data consolidation and reduce the potential for human errors. Data from Scopus were chosen for this analysis because it includes a wider range of subject areas and categories than WoS, making it ideal for aggregating extensive collections of documents from reputable academic journals, especially in emerging research domains (Paul et al., 2021). Formulating a well-defined search query is critical to bibliometric analysis, as it ensures clarity, reproducibility, and precision (Khatib et al., 2023). In this study, the search query emotional exhaustion (EE) was entered in the “Article Title, Abstract, and Keywords” section of the Scopus database. The analysis was limited to articles published in the subject areas of “Business, Management, and Accounting,” “Psychology,” and “Social Sciences.” The study covered publications from 1978 to 2024, aligning with the emergence of significant works on EE. To maintain a high standard of review, we excluded conference papers, book chapters, and other forms of “gray literature,” focusing solely on peer-reviewed journal articles and reviews. The search was conducted on April 21, 2024, to ensure that the most recent data from Scopus were captured without introducing bias from ongoing updates. This initial search resulted in 3,667 articles. The next step involved filtering out articles published in 1979 and 1980, as no relevant articles on EE were found in those years. After this filtering, we reviewed article titles, keywords, abstracts, and full texts to ensure the inclusion of only the most relevant works. Bibliometric methodologies can be categorized into two main types: (a) performance analysis, which assesses the roles of various research components, and (b) science mapping, which focuses on the relationships among these components (Mikul & Mittal, 2023). To perform the analysis, we used the Biblioshiny package in R (Aria & Cuccurullo, 2017) and the interactive mapping features of VOSviewer (van Eck & Waltman, 2010). The research framework is presented in Figure 1.

Figure 1.

Framework of the Research Design.

Results

Performance Analysis

Chronological Publication Trends

An annual trend analysis of EE research, examining both the volume of publications and their influence (RQ1) from 1978 to 2024, is illustrated in Figure 2. The number of publications has risen dramatically, from just one in 1978 to 439 in 2023. The heights of the rectangular bars in the figure represent the total number of publications, which amounts to 3,667. The influence, indicated by yearly citations, is depicted as a “zigzag” line. Between 1978 and 1992, the number of published studies was relatively low. However, 2023 recorded the highest number of publications, with 439. The trend equation in Figure 2 reflects significant growth in this research area, with a high model fit (R² = 0.93), showcasing the robustness of the growth trajectory. The regression coefficient of 1.877 suggests notable annual growth. The surge in EE research can be attributed to the expanding recognition of EE and its diverse manifestations. Notably, nearly 96% of the 3,667 publications (3,515) were published between 1998 and 2024, highlighting a clear upward trend in both the volume and citation influence of EE research over time.

Figure 2.

Chronological Publication Trends.

Citation Structure

Throughout the data set (see Table 1), a total of 151,971 citations were recorded, with an average of 6,128 citations per year, translating to an annual average of 241.53 citations. The h-index, which represents the number of articles that have been cited at least h times, is 52 in this data set (Hirsch & Buela-Casal, 2014). This suggests that 52 articles have each received no fewer than 52 citations. The g-index, an enhancement of the h-index that considers the total citation count, stands at 95 (Egghe & Rousseau, 2019), demonstrating the research’s significant citation impact. The m-index, calculated by dividing the h-index by the number of years since the first research publication, is 7.80 in this case (Bornmann et al., 2008). Additionally, the dataset’s i-10 index, which reflects the number of articles with at least ten citations, is 2,145, highlighting a strong citation presence with numerous influential works. These metrics suggest that the body of research covered in the dataset will continue to exert considerable scholarly influence in the years ahead. These findings suggest that the study of EE will maintain its relevance and continue to contribute meaningfully to the field in the coming years. The consistently high citation counts and strong metrics highlight the field’s increasing importance and the sustained attention it is garnering within academic discourse.

Table 1.

Citation Structure.

Year	TP	AC	TC	h	g	m	ACPY	≥100	≥50	≥25	≥15	≥10	≥5	≥1
1978	1	278.0	278	1	1	0.02	6.04	0	1	1	1	1	1	1
1981	3	2463.3	7,390	3	3	0.07	57.29	3	3	3	3	3	3	3
1982	1	205.0	205	1	1	0.02	4.88	1	1	1	1	1	1	1
1983	1	11.0	11	1	1	0.02	0.26	0	0	0	0	1	1	1
1984	4	59.8	239	3	3	0.07	1.49	1	2	3	3	3	4	4
1985	3	46.3	139	2	2	0.05	1.19	1	1	2	2	2	2	3
1986	7	148.6	1,040	7	7	0.18	3.91	2	4	7	7	7	7	7
1987	10	36.2	362	9	10	0.24	0.98	1	2	3	7	8	10	10
1988	8	147.5	1,180	15	8	0.41	4.10	2	3	6	7	8	8	8
1989	9	200.6	1,805	5	9	0.14	5.73	2	4	6	8	8	9	9
1990	7	90.0	630	5	7	0.15	2.65	3	3	4	4	4	5	6
1991	10	69.7	697	10	10	0.29	2.11	3	5	8	9	10	10	10
1992	12	75.0	900	10	12	0.30	2.34	3	6	7	9	10	11	12
1993	20	64.8	1,296	15	20	0.47	2.09	4	5	12	15	16	18	20
1994	14	39.7	556	12	14	0.39	1.32	0	5	12	12	16	18	20
1995	7	51.4	360	7	7	0.23	1.77	1	3	5	6	7	7	7
1996	19	262.8	4,994	19	19	0.66	9.39	6	12	17	19	19	19	19
1997	16	76.4	1,223	14	16	0.50	2.83	4	10	14	14	17	17	17
1998	21	117.1	2,460	18	21	0.67	4.51	5	9	15	18	20	21	21
1999	25	103.4	2,585	22	25	0.85	4.14	9	14	20	24	25	25	25
2000	30	120.4	3,611	23	30	0.92	5.02	15	19	25	25	25	27	29
2001	33	102.5	3,383	27	33	1.13	4.46	10	19	27	31	31	32	33
2002	22	90.7	1,995	17	22	0.74	4.12	7	10	12	19	19	19	20
2003	32	159.5	5,104	27	32	1.23	7.60	10	7	27	29	29	32	32
2004	34	91.3	3,105	25	34	1.19	4.57	10	14	25	27	26	26	26
2005	32	83.4	2,670	26	32	1.30	4.39	11	19	26	59	31	31	31
2006	55	123.9	6,813	38	55	2.00	6.88	20	35	41	31	48	50	54
2007	65	105.8	6,878	40	65	2.22	6.22	19	35	51	58	60	64	65
2008	57	70.1	3,994	35	57	2.06	4.38	14	29	39	44	46	49	53
2009	74	77.9	5,764	40	74	2.50	5.19	14	34	51	61	68	72	74
2010	99	92.6	9,166	48	95	3.20	6.61	23	48	68	79	88	97	99
2011	83	61.4	5,098	42	71	3.00	4.72	12	32	53	59	65	77	83
2012	93	61.8	5,743	49	75	3.77	5.15	19	43	67	76	80	83	90
2013	120	53.2	6,379	40	79	3.33	4.83	17	34	79	101	111	115	120
2014	126	60.1	7,578	52	87	4.73	6.01	22	52	77	95	109	119	125
2015	127	46.6	5,916	45	77	4.50	5.18	16	41	70	93	104	117	124
2016	166	43.6	7,241	47	85	5.22	5.45	19	45	92	124	143	156	162
2017	165	34.1	5,621	44	74	5.50	4.87	8	36	79	104	123	150	164
2018	193	32.2	6,208	44	78	6.28	5.36	14	36	78	114	142	164	186
2019	242	24.6	5,948	44	77	7.33	4.92	8	30	84	131	157	201	234
2020	307	22.0	6,768	39	82	7.80	5.51	6	33	81	135	191	243	295
2021	345	13.7	4,726	31	68	7.75	4.57	2	10	55	115	153	241	323
2022	401	6.9	2,761	22	51	7.33	3.44	0	2	19	45	89	196	356
2023	439	2.4	1,070	13	32	6.50	2.44	0	0	1	11	21	73	276
2024	129	0.6	81	4	9	4.00	0.63	0	0	0	0	0	4	39

Note: TP: Total publications; TC: Total citations; AC: Average citations; ACPY: Average citations per year; ≥: Number of publications cited equal to or greater than specific threshold level; h: h-index; g: g-index; m: m-index.

Most Active and Influential Journals

The identification of leading journals in EE research (RQ2) is essential for understanding the dissemination and influence of EE-related studies. Table 2 provides an in-depth review of the top 10 journals in this field, highlighting their bibliometric characteristics. Notably, Frontiers in Psychology (FIP) leads in publication volume, contributing 200 articles, demonstrating its central role in EE research. The Journal of Applied Psychology (JAP) follows with outstanding productivity metrics, including 13,839 total citations, an average citation counts of 239 and an impact factor (IF) of 9.9, emphasizing its significant academic influence. The Journal of Occupational Health Psychology (JOHIP) stands out with the highest g-index (74), reflecting its enduring scholarly impact. Further analysis reveals that these journals not only excel in productivity but also rank highly in terms of academic standing. JOHIP, for example, has earned an A* rating from the “Australian Business Deans Council” (ABDC), underscoring its prestigious position. Journals such as Current Psychology (CP) and Stress and Health (SAH) also show strong performance in CiteScore and the Journal Citation Indicator (JCI), highlighting their substantial contributions to advancing EE research. Furthermore, Table 2 reveals a compelling trend: the top 10 journals represent 33.55% of total citations, despite comprising only 18.27% of the articles, illustrating their disproportionate academic impact within the field.

Table 2.

Leading Journals.

Rank	Journal	Publisher	TP	S%	TC	AC	H	G	M	JCI	CS	SNIP	SJR	Q	IF	ABDC
1	FIP	Frontiers Media S.A.	200	5.45	3,299	16	29	50	29	1.04	4.5	0.891	1.422	Q1	3.8	NA
2	JOHP	APA	74	2.02	6,022	81	42	74	42	1.78	11.1	2.478	2.566	Q1	5.1	A
3	WAS	Taylor & Francis	66	1.80	4,966	75	40	66	40	1.44	13.6	2.5	3.303	Q1	6.1	NA
4	JAP	APA	58	1.58	13,839	239	42	57	42	2.64	14	6.13	3.861	Q1	9.9	A*
5	CP	Springer Nature	50	1.36	650	13	15	24	15	0.98	4.6	0.661	0.994	Q2	2.8	NA
6	IJSM	APA	50	1.36	1,786	36	24	42	24	1.16	7.4	1.336	1.676	Q2	4	A
7	SAH	Wiley-Blackwell	49	1.34	2,298	47	25	47	25	0.91	5.4	1.196	1.505	Q2	4.1	A
8	JOB	Wiley-Blackwell	47	1.28	12,265	261	33	47	33	1.58	2.7	0.57	1.209	Q2	6.8	A*
9	EJWOP	Taylor & Francis	39	1.06	1,734	44	22	39	22	1.07	8.5	1.966	2.38	Q3	4.3	A
10	TTE	Elsevier	37	1.01	4,138	112	21	37	21	2	6.5	1.616	2.474	Q1	3.9	NA

Notes: FIP: Frontiers in Psychology; JOHIP: Journal of Occupational Health Psychology; WAS: Work and Stress; JAP: Journal of Applied Psychology; CP: Current Psychology; IJSM: International Journal of Stress Management; SAH: Stress and Health; JOB: Journal of Organizational Behavior; EJWOP: European Journal of Work and Organizational Psychology; TTE, Teaching and Teacher Education; APA: American Psychological Association; S%: Share in corpus; IF: Impact factor; JCI: Journal citation indicator; Q: Quadrant; CS: CiteScore; SNIP: Source normalized impact per paper; SJR: SCImago journal rank; ABDC: Australian Business Dean Council journal rank.

The values presented in bold indicate the highest values within the respective categories.

Most Influential Works

Examining the most influential works in the field of EE (RQ2) is vital to understanding the scholarly contributions that have shaped the research landscape. Table 3 presents the top 10 EE-related articles, highlighting key citation metrics that indicate their academic impact. The study by Maslach and Jackson (1981) is the most cited article with a total citation count (TC) of 7,089, as well as the highest citation density (CD: 164.86), reflecting its enduring relevance. The article also received 265 citations in 2024 (CCY) on Scopus, and it has garnered 24,321 citations on Google Scholar (CGS), further attesting to its wide reach. In contrast, Lee and Ashforth (1996) demonstrated substantial influence through their meta-analysis, which has accumulated 1,887 citations in Web of Science (CWoS). Their work also highlights demand–resource correlates as more closely tied to EE than to other burnout dimensions. The citation metrics, including FWCI and citation counts from multiple platforms, such as Google Scholar and Web of Science, underline the varying citation patterns across databases, with Google Scholar showing a broader citation distribution. Notably, the correlation between Scopus and Web of Science citations (r: 0.99) supports the reliability of Scopus for citation analysis. It is also noteworthy that the most-cited articles span from 1981 to 2013. This pattern is common in bibliometric studies because older publications generally have more time to accumulate citations compared to recent ones.

Table 3.

Rank	Title	Year	Authors	Journal	N	TC	CD	CCY	CGS	CWOS	FWCI
1	“The Measurement of Experienced Burnout”	1981	Maslach & Jackson	JOB	2	7,089	164.86	265	24,312	NA	NA
2	“A Meta-analytic Examination of the Correlates of the Three Dimensions of Job Burnout”	1996	Lee & Ashforth	JAP	2	2,149	76.75	51	5,658	1887	10.05
3	“When the Show Must Go On: Surface Acting and Deep Acting as Determinants of Emotional Exhaustion and Peer-rated Service Delivery”	2003	Grandey	AMJ	1	1,419	67.57	45	3,550	1286	16.89
4	“The Dimensions, Antecedents, and Consequences of Emotional Labor”	1996	Morris & Feldman	AMJ	2	1,389	49.6	24	4,942	1130	13.34
5	“Emotional Exhaustion as a Predictor of Job Performance and Voluntary Turnover”	1998	Wright & Cropanzano	JAP	2	1,068	41.07	33	2,493	951	4.25
6	“The Relationship of Emotional Exhaustion to Work Attitudes, Job Performance, and Organizational Citizenship Behaviors”	2003	Cropanzano et al.	JAP	3	980	46.66	26	2,348	870	5.47
7	“The Impact of Interpersonal Environment on Burnout and Organizational Commitment”	1998	Leiter & Maslach	JOB	2	854	32.84	14	3,535	NA	NA
8	“Sources of Social Support and Burnout: A Meta-analytic Test of the Conservation of Resources Model”	2006	Halbesleben	JAP	1	851	47.27	31	1,841	791	4.34
9	“Benefits of Mindfulness at Work: The Role of Mindfulness in Emotion Regulation, Emotional Exhaustion, and Job Satisfaction”	2013	Hülsheger et al.	JAP	4	805	73.18	34	1,889	706	14.7
10	“Teacher Job Satisfaction and Motivation to Leave the Teaching Profession: Relations with School Context, Feeling of Belonging, and Emotional Exhaustion”	2011	Skaalvik & Skaalvik	TTE	2	732	56.3	42	2,142	635	10.96

Science Mapping

Bibliographic Coupling Analysis

Bibliographic coupling occurs when two documents cite the same references, indicating conceptual similarity (Jain et al., 2021; Zainuldin & Lui, 2022). This method helps uncover thematic connections and the intellectual structure of a field (Koseoglu, 2016). In the context of EE research, bibliographic coupling was employed to identify knowledge clusters. Applying a minimum citation threshold of 280, five distinct clusters were identified, comprising 50 articles with a total link strength (TLS) of 1,108 (see Figure 3).

Figure 3.

Bibliographic Coupling Analysis.

Cluster 1: Psychological and behavioral factors—This cluster highlights the psychological and behavioral underpinnings of EE, emphasizing stress as a primary antecedent. Chronic workplace stress can lead to burnout symptoms such as cognitive weariness, depersonalization, and reduced personal accomplishment (Taris et al., 2005). EE has also been linked to serious health concerns, including cardiovascular disease, metabolic syndrome, and weakened immunity (Melamed et al., 2006). Personality traits such as emotional stability, positive affectivity, and negative affectivity show a stronger association with EE compared to other traits (Alarcon et al., 2009; Swider & Zimmerman, 2010). Psychological detachment from work acts as a buffer, enabling recovery from emotional strain (Sonnentag et al., 2010). On the behavioral side, workplace incivility intensifies EE, particularly from difficult customers (Sliter et al., 2010; van Jaarsveld et al., 2010), whereas mindfulness practices help mitigate its impact by enhancing emotional regulation and present-moment awareness (Hülsheger et al., 2013).

Cluster 2: Mediators in EE research—This cluster emphasizes mediating variables that clarify the mechanisms underlying EE in organizational contexts. Studies have shown that teacher satisfaction mediates the relationship between school climate and EE (Grayson & Alvarez, 2008), while motivation plays a similar role between EE and job performance (Halbesleben & Bowler, 2007). Guided by the conservation of resources (COR) theory, job performance has been identified as a mediator linking EE and turnover intention (Lee & Ashforth, 1996; Wright & Cropanzano, 1998). Organizational commitment, rooted in social exchange theory, mediates the association of EE with turnover intention, job performance, and citizenship behavior (Cropanzano et al., 2003). EE itself acts as a mediator between various work-related, social, and personal factors and employee attrition (Deery et al., 2002). Organizational cynicism has been found to fully mediate the impact of psychological contract breaches on EE (Johnson & O’Leary-Kelly, 2003). Additionally, EE mediates the link between classroom management self-efficacy and personal accomplishment (Brouwers & Tomic, 2000).

Cluster 3: Antecedents of EE in education and health care—This cluster examines the key antecedents of EE among professionals in the education and healthcare sectors. In teaching, persistent job stress stemming from time pressures, disciplinary challenges, and perceived lack of belonging contributes to heightened psychological strain and reduced job satisfaction (Skaalvik & Skaalvik, 2011). Personality traits such as neuroticism, low conscientiousness, and low agreeableness further exacerbate EE in educators (Halbesleben & Buckley, 2004; Kokkinos, 2007). Teachers’ perceptions of adverse school climates, marked by limited autonomy, accountability pressures, and managing students with learning difficulties, have been identified as prominent triggers of EE (Skaalvik & Skaalvik, 2009). Conversely, higher levels of self-efficacy and perceived autonomy serve as protective factors (Skaalvik & Skaalvik, 2014). In the health care domain, a longitudinal study applying equity and social exchange theories found that emotionally demanding patient interactions, including complaints and threats, contribute significantly to EE among general practitioners by fostering perceptions of imbalance in the clinician–patient relationship (Bakker et al., 2000). Similarly, medical students reporting serious thoughts of withdrawal were found to exhibit elevated levels of EE (Dyrbye et al., 2010).

Cluster 4: Theoretical perspectives on EE—This cluster synthesizes key theoretical frameworks that elucidate the development of EE within the teaching and health care professions. Drawing from the self-determination theory (SDT), studies reveal that teachers’ perceptions of classroom overload and student misbehavior undermine autonomous motivation, thereby intensifying EE (Fernet et al., 2012). Teachers with higher self-determined motivation report greater personal accomplishment and reduced emotional fatigue (Roth et al., 2007). Supportive principal–teacher interactions further enhance engagement and buffer against EE (Klassen et al., 2012). Extrinsic occupational value orientations, when dominant, are linked to negative outcomes and heightened exhaustion (Vansteenkiste et al., 2007). The job demand-control (J-C) model posits that jobs characterized by high demands and limited control significantly contribute to EE, while the effort–reward imbalance (ERI) model highlights the emotional strain resulting from perceived inequities in effort and compensation (De Jonge et al., 2000). Additionally, the conservation of resources (COR) theory suggests that teachers who can emotionally detach from work and manage failure effectively experience greater occupational well-being and lower exhaustion levels (Klusmann et al., 2008).

Cluster 5: Emotional labor and its link to EE—This cluster explores the multifaceted role of emotional labor in shaping EE. Emotional labor encompasses the regulation, planning, and strategic expression of emotions to align with organizational expectations during interpersonal interactions. Its core dimensions, emotional display frequency, adherence to display rules, emotional range, and emotional dissonance, significantly affect employee well-being (Morris & Feldman, 1996). EE, a core component of burnout measured by the validated Maslach Burnout Inventory (Maslach & Jackson, 1981), often stems from prolonged engagement in emotional labor. Notably, surface acting, which involves suppressing or faking emotions, is more strongly associated with EE than deep acting, which entails modifying internal feelings to match external expressions (Goldberg & Grandey, 2007). Although deep acting can be depleting, it generally induces less emotional strain than surface acting. Emotional dissonance, an incongruence between felt and displayed emotions, also emerges as a powerful predictor of EE (Grandey, 2003; Johnson & Spector, 2007; Judge et al., 2009).

Co-authorship Analysis

Co-authorship analysis identifies collaboration patterns and social structures among researchers in a given field (Donthu et al., 2020). The growing methodological and theoretical sophistication in research has encouraged greater academic collaboration (Acedo et al., 2006). Analyzing these collaborations, including key attributes such as author affiliations and countries, offers insights into the intellectual landscape of a domain (Donthu et al., 2021). As co-authorship reflects stronger social ties than other bibliometric connections, it serves as a valuable metric in social network analysis (Zupic & Čater, 2015). To examine the collaborative structure of EE research (RQ3), a co-authorship network was generated, displaying countries with at least 14 co-authored publications (Figure 4).

Figure 4.

Co-authorship Network of Countries.

Out of 162 countries, 44 met the inclusion threshold, forming a co-authorship network of five clusters interconnected by 375 links, with a TLS of 1,360. Country clusters were color-coded based on the similarity of their collaborative patterns. The United States, positioned within the purple cluster, emerged as the most influential node, with 41 connections and a TLS of 365. Notably, the strongest edge in the network links the United States and China (green cluster), reflecting intensive academic collaboration, particularly in higher education. China follows as the second most central node, with 31 connections and a TLS of 252. The red cluster, dominated by European countries such as the United Kingdom, Belgium, the Netherlands, and Sweden, represents the largest grouping, underscoring strong intra-European cooperation. The blue cluster includes Italy, Poland, Turkey, India, and Nigeria, illustrating cross-regional research ties beyond political boundaries. Spain, within the yellow cluster, stands out for its high productivity and collaborative intensity. The fifth cluster, also purple, features advanced economies including Australia, Austria, Singapore, and South Korea, highlighting their global influence in academia, trade, and technology. Smaller nodes across all clusters suggest untapped potential for expanding international collaboration.

Co-word Analysis

Co-word analysis is a content analysis technique that leverages the terminology used in texts to identify conceptual linkages and develop a thematic structure within a research domain (Callon et al., 1983). This method commonly employs “author keywords,” where the frequent co-occurrence of terms signifies a relationship between the underlying concepts (Zupic & Čater, 2015). To address RQ4, we conducted a co-word analysis to identify the major themes associated with EE. The analysis utilized all author keywords that appeared together at least 25 times, resulting in a simplified yet meaningful network. Out of 6,251 keywords, only 61 met this threshold. The resulting co-occurrence network, depicted in Figure 5, comprises 835 links with a TLS of 4,058 and reveals five distinct thematic clusters.

Figure 5.

Co-occurrence Network of Keywords.

Cluster 1: Work-related psychological factors—The first and largest cluster (red) explores the multifaceted dimensions of psychological well-being, encompassing key concepts such as anxiety, burnout, burnout syndrome, depression, occupational stress, mental health, and occupational health. These factors are categorized as “work-related psychological well-being elements” and are deeply interconnected in the development and experience of EE, particularly in professional settings. Addressing these factors is critical in alleviating EE and fostering a healthier work environment. Among these, burnout stands out as the most frequently occurring term, appearing 1,038 times, and serves as the most prominent factor linked to EE.

Cluster 2: Drivers and outcomes of EE—This is the second largest cluster (green) and centers around the various drivers and outcomes of EE. The key drivers, or antecedents, include work–family conflict, perceived organizational support, role conflict, job satisfaction, and abusive supervision. The outcomes of EE explored in this cluster encompass turnover, turnover intentions, organizational commitment, job performance, and life satisfaction. “EE” is the largest node in this cluster, as anticipated based on the synthesis of the EE literature. These terms, “EE” and “burnout,” are found in the majority of articles, with 128 occurrences each.

Cluster 3: Factors contributing to and mitigating EE—This cluster (blue) focuses on core themes related to EE in the workplace. It categorizes these themes into two main groups: contributing factors and mitigating initiatives. Contributing factors include lower work engagement, workload, job pressure, job insecurity, and workplace bullying, all of which exacerbate EE. On the other hand, mitigating factors include leadership, well-being initiatives, employment resources, and mindfulness practices, which help alleviate the effects of EE. The most significant node in this cluster is “well-being,” which appears 123 times across the cluster.

Cluster 4: Interpersonal and emotional dynamics in the workplace—The yellow cluster delves into the interpersonal and emotional dynamics within the workplace, encompassing concepts such as emotional intelligence, emotional labor, surface acting, and emotional dissonance. These interconnected themes influence how individuals experience emotional depletion, particularly when there is a discrepancy between their true emotions and the emotions they are expected to display. Such dynamics are key contributors to EE. The most prominent node in this cluster is “emotional labor,” which appears 37 times.

Cluster 5: Psychosocial stressors and coping mechanisms at work—This cluster examines the impact of psychosocial work stressors and the resources available for coping. Key stressors such as job uncertainty, workplace bullying, and depersonalization contribute to heightened stress and EE. On the other hand, coping resources such as personal accomplishment, mindfulness, self-efficacy, and emotional regulation help alleviate EE and are closely tied to these stressors. These factors significantly influence how individuals perceive and respond to workplace stress, either exacerbating or mitigating EE. The predominant node in this cluster is “self-efficacy,” appearing 31 times.

Implications

Theoretical Implications

This study contributes significantly to the theoretical understanding of EE by integrating key theories such as the JD-R model, SDT, COR theory, and emotional labor theory. By employing these frameworks, the study explores the complex relationship between work-related psychological well-being factors, such as burnout, anxiety, depression, and occupational stress, and their role in both contributing to and alleviating EE. It highlights how antecedents such as work–family conflict, perceived organizational support, role conflict, and job satisfaction directly influence EE, while consequences such as turnover intentions, organizational commitment, job performance, and life satisfaction are explored in depth. The research also sheds light on the critical role of coping resources, such as leadership, mindfulness, and well-being initiatives, in reducing EE. Furthermore, the study explores the influence of interpersonal dynamics at work, such as emotional intelligence, emotional labor, and emotional dissonance, and how they act as significant predictors of EE. This research highlights how organizational structures, leadership practices, and resource management can either exacerbate or mitigate EE, emphasizing the importance of developing tailored strategies for reducing EE in different professional contexts, particularly in high-stress sectors such as education and health care. The study also underscores the need for more targeted interventions, such as fostering emotional regulation and resilience among employees, to prevent burnout and improve overall workplace well-being. Overall, this research broadens the scope of existing EE literature by applying these diverse theoretical frameworks to understand and manage EE more effectively across different industries.

Practical Implications

This research, while rooted in scientometrics, provides significant practical implications for management, organizational leaders, and HR professionals aiming to mitigate EE in the workplace. To effectively address EE, organizations must adopt a comprehensive, proactive approach that integrates both preventive and corrective strategies. First, creating a supportive environment is critical. Job redesign, stress-reduction initiatives, and leadership support are essential in reducing job-related stress and EE. Proactive mental health care, such as offering employee assistance initiatives (EAIs), on-site counseling, virtual therapy, and mental health awareness programs, can further help employees manage the psychological demands of their roles. Second, organizations should focus on enhancing emotional intelligence among employees through training programs. This can be complemented by fostering a workplace culture with transparent communication, mindfulness practices, resilience workshops, and access to mental health resources. Implementing flexible work schedules and promoting work–life balance are also vital strategies that enable employees to manage their time and reduce stress.

Third, recognizing and valuing both individual and team accomplishments helps boost morale and motivation. Regular check-ins with employees to monitor stress levels and workload are necessary for maintaining employee well-being and ensuring clear role expectations, which foster a sense of purpose and reduce exhaustion. Fourth, organizations should cultivate a workplace where employees can express their emotions authentically, minimizing emotional dissonance. Reducing pressure to conform to inauthentic emotional expressions lessens EE. Aligning tasks with employees’ skills and career aspirations, while managing workloads effectively, ensures that employees feel valued and supported in their roles. Finally, implementing training on workplace dispute resolution enhances employees’ ability to handle interpersonal conflicts, ultimately reducing EE and fostering a cooperative team environment. By adopting these strategies, organizations can not only mitigate EE but also improve overall job satisfaction, productivity, and employee well-being.

Discussion and Conclusion

This study offers a comprehensive scientometric analysis of the EE research landscape by examining 3,667 articles published between 1978 and 2024, accumulating a total of 151,971 citations. The analysis reveals the increasing academic interest in EE, evidenced by a ‘compound annual growth rate’ (CAGR) of 21% in publications. The United States and China emerged as dominant contributors, underscoring the global recognition of EE as a pressing issue in today’s workplaces. By applying bibliometric techniques such as bibliographic coupling, the study identified five core research clusters: (a) psychological and behavioral factors, (b) mediators related to the literature on EE, (c) causes of EE in teaching and health care professions, (d) emotional labor and its relations with EE, and (e) psychosocial work stressors and coping resources. These clusters collectively capture the multifaceted and interdisciplinary nature of EE research. The leading journals, Journal of Applied Psychology, Stress and Health, and Journal of Organizational Behavior, have played a pivotal role in disseminating foundational knowledge. Seminal works, such as Maslach and Jackson’s (1981) development of the Maslach Burnout Inventory and Schaufeli’s contributions to burnout theory, continue to shape the scholarly discourse, alongside contemporary studies exploring emotional intelligence, organizational support, and employee well-being.

The study also highlights key thematic areas gaining momentum in the field, such as psychological well-being, antecedents and consequences of EE, contributors and mitigators of EE, and emotional and interpersonal dynamics at work. Co-authorship analysis reveals strong international collaboration, particularly between scholars in the United States and China, opening avenues for more nuanced cross-cultural investigations. From a practical standpoint, the findings emphasize the importance of comprehensive organizational interventions. Strategies such as emotional intelligence training, stress management programs, mental health support, and work–life balance initiatives are essential in mitigating EE. Additionally, recognizing the influence of emotional labor and interpersonal stressors can inform more empathetic and supportive workplace practices. Clear job roles, fair workload distribution, and conflict resolution training are crucial to fostering healthier and more resilient work environments.

This study’s outcomes also open opportunities to link EE with other related topics from an industry perspective. Understanding how EE interacts with employee engagement, job satisfaction, retention, productivity, and workplace innovation is highly relevant for industries such as health care, education, information technology, manufacturing, hospitality, and customer service, where high job demands and interpersonal interactions often intensify emotional strain. EE has been shown to lead to absenteeism, lower service quality, and increased turnover, all of which directly impact organizational performance and profitability. Future research could adopt sector-specific approaches by comparing how EE manifests across industries and examining whether certain job characteristics (e.g., shift work, customer-facing roles, or high-stress environments) amplify its effects. There is also significant scope to explore how EE connects with emerging workplace challenges such as hybrid/remote work models, the integration of AI and digital tools, and increasing mental health risks in fast-paced industries. Further, EE can be studied alongside related organizational constructs such as leadership styles, organizational culture, diversity and inclusion initiatives, and occupational health policies to generate actionable insights for managers. Linking bibliometric findings with industry-focused case studies, longitudinal surveys, or mixed-methods research would strengthen the practical relevance of EE scholarship. Such work could help organizations design more targeted interventions, improve employee well-being, and build more resilient and sustainable workplaces across sectors.

In addition to presenting the theoretical foundations of EE research, this study underscores the importance of mapping its future trajectories. A content analysis of documents from the five bibliographic clusters revealed critical gaps and unresolved questions within the field. This informed the development of a structured research agenda addressing RQ4, future directions in EE research. By integrating insights from recent trends and emerging themes, this agenda outlines several promising avenues for scholarly exploration (see Table 4 for future directions). In conclusion, EE remains a complex and evolving challenge in organizational life. This study contributes meaningful insights to the academic literature and offers practical guidance for managerial action. By continuing to investigate the psychological, emotional, and contextual dimensions of EE, and by implementing thoughtful interventions, researchers and practitioners alike can work toward reducing its impact and fostering more sustainable work environments.

Table 4.

Intellectual Structure and Research Avenue.

Sr. No.	Clusters	Future Research
1	Psychological and behavioral factors	• Examine how elements such as cynicism and professional efficacy interact with customer incivility and interpersonal rudeness among employees to affect EE.• Explore moderating variables, such as coping strategies, job roles, or organizational culture, that influence the personality–burnout link, especially in high-stress professions.• Conduct longitudinal studies to examine the causal relationship between personality traits and burnout over time.
2	Mediators in EE research	• Investigate how individual perceptions of work environments mediate the relationship between personality characteristics and EE.• Identify supervisor characteristics associated with abusive behaviors within high-quality leader–member exchange (LMX) relationships, and examine how subordinates distinguish between genuine support and “tough love” approaches.• Investigate whether in-group members experience higher levels of abusive supervision compared to out-group members, and examine the coping mechanisms adopted in such dynamics.• Future research should explore the nuanced relationships among different forms of workplace misconduct, such as incivility, petty tyranny, workplace deviance, bullying, aggression, and undermining, and their collective impact on EE.
3	Antecedents of EE in education and health care	• Future studies should delve deeper into school-specific variables that influence teachers’ sense of belonging, job satisfaction, and intention to leave the profession.• Investigate the longitudinal effects of teacher self-efficacy and autonomy on EE and professional engagement.• Since the three dimensions of teacher burnout (EE, depersonalization, and reduced personal accomplishment) impact school context and job satisfaction differently, future research should evaluate these dimensions separately to derive more nuanced insights.
4	Theoretical perspectives on EE	• Future research could assess autonomy-supportive teaching behaviors using observational and multi-source assessment methods to enhance objectivity.• There is a need to investigate psychological safety climate (PSC) as a distinct, facet-specific component of organizational climate, particularly in comparison to related constructs such as safety climate, psychological safety, and broader organizational climate.• Future studies should clarify the referents of PSC by distinguishing between team-level and organizational-level conceptualizations and their respective influences on EE.
5	Emotional labor and its link to EE	• Future research should investigate how organizational and job-level factors shape emotional labor by employing multi-level hierarchical models that capture variance across occupations, jobs, individuals, and intra-individual experiences.• There is a need to explore situational moderators, such as fluctuating work demands and context-specific challenges, to understand their influence on emotional labor and EE.• Since mechanisms like negative affectivity inadequately explain the dual outcomes of emotional labor, future studies should examine how work-related stressors and strain interact with emotional traits to shape burnout outcomes.• Researchers should assess whether emotional regulation efforts vary depending on interaction targets (e.g., customers vs. colleagues) and evaluate their differential impacts on EE.

Limitations and Future Direction

While this review provides valuable insights into EE, a few limitations should be acknowledged. First, the analysis was based only on the Scopus database. Although we removed duplicate and retracted articles, relying on a single source can result in coverage gaps. Future research could include additional databases such as Web of Science and Google Scholar to broaden the coverage and ensure a more comprehensive view of the field. Second, we focused only on a defined set of keywords related to EE. This approach may have excluded studies using related terms such as “mental exhaustion,” “emotional fatigue,” or “compassion fatigue.” Future work could broaden the search terms and even include studies published in other languages to capture a wider body of work.

Third, certain publication types, such as conference papers, books, and dissertations, were excluded. Although this ensures a more consistent quality of sources, it may leave out fast-moving or practice-oriented research. Including this gray literature in future reviews could provide a fuller picture of the field. Fourth, bibliometric indicators such as citation counts have inherent limitations. Highly cited papers are not always the most methodologically sound or relevant, and emerging studies may be underrepresented simply because they have had less time to accumulate citations. Future studies could combine bibliometric measures with peer-assessed quality indicators or altmetrics to balance these effects.

Fifth, the study relied mainly on bibliographic coupling for science mapping. Different techniques, such as co-citation or keyword co-occurrence analysis, might highlight different relationships. Future research could compare and combine these methods to gain deeper insights. Finally, this study provides a broad overview and does not focus on sector-specific applications. Future researchers could analyze EE trends within particular industries, such as health care, education, IT, or manufacturing, and link these findings to industry practices. Combining bibliometric analysis with interviews, surveys, or meta-analyses could also help translate research into actionable strategies across industries and regions.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The authors received no financial support for the research,authorship,and/or publication of this article.

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