CiteNScope — Scholarly Index & Analytics
Discover / Analytics RESEARCH INTELLIGENCE
CiteNScope / Analytics

Explore the evidence.
Understand the reach.

Research across participating journals · All insights follow your collection filters.

Compare journals ↗
OpenAlex coverage 100.0% · 3/3 recordsLast OpenAlex observation 21 Oct 2026, 07:22 UTC
PUBLICATIONS3In the selected collection
CROSSREF CITATIONS93/3 with known counts
OPENALEX CITATIONS183/3 with known counts
OPENALEX MEAN6.0Per article with a known count
Explore articles 3 →
Filter collection Publication years, search & more
Reset
topic: Emotional Labor in Professions Remove ×
Your research collection

Output and reach

Publication activity alongside incoming citations.

Publication activity

Articles grouped by publication year

Publications

Hover over a year or focus the chart and use arrow keys to inspect values.

2026 is year to date. 0 undated publications excluded.

View data & coverage

Citations received

OpenAlex · year of the citing work

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

View data & coverage

Research landscape

Leading affiliations and themes in this collection.

Full distributions & methodology ↓

Institutions

Vaal University of Technology1Istanbul Medipol University1I-Shou University13/3 records with data

Countries

Turkey1Taiwan1South Africa13/3 records with data

Primary topics

Emotional Labor in Professions33/3 records with data
Two perspectives on citations

Follow the research impact

Independent sources. Clear time scales.

Lifetime citations by publication year

Crossref and OpenAlex · separate totals for the same publication cohorts

Hover over a year or focus the chart and use arrow keys to inspect values.

Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.

View data & coverage

Citations received each year

OpenAlex · incoming citation links grouped by citing-work year

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

View data & coverage
Annual history: 3/3 articles. Latest history observation: 2026-10-21T07:22:57.100450+00:00. Source totals are never added together.
Research side by side

Compare journals

Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.

Leave all unchecked to include every matching journal. Selection affects only comparison charts.
Display range
International Journal of Research in Business and Social Science

Publications

Articles by publication year

View data & coverage

Crossref citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex · Citations received

By year of the citing work · 2017–2026

View data & coverage

2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.

Full analytics report All distributions, publications, comparisons & data provenance
3 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS3
CROSSREF CITATIONS9
CROSSREF · CITED PUBLICATIONS66.7%
CROSSREF · MEAN CITATIONS3.0

Crossref citation coverage: 3 / 3 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.

OpenAlex / Separate citation source

A broader view of this research

DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.

OPENALEX CITATIONS18
DOI MATCH COVERAGE100.0%3 / 3 publications
MEAN · KNOWN COUNTS ONLY6.03 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY2

Observation range: 21 Oct 2026 00:49 UTC — 21 Oct 2026 07:22 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations01–526–20121+0Unknown0

Institutions, countries & topics

OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.

Institutions

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Countries

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Primary topics

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Citation year / OpenAlex

Citations received over time

Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.

The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.

Annual history available for 3 / 3 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.

Annual-history observations (UTC): 2026-10-21T00:49:28.576123+00:00 — 2026-10-21T07:22:57.100450+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

52.50 2017 · All selected publications · OpenAlex · Citations received by year: 3 · Annual history coverage 3/32018 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32019 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32020 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32021 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32022 · All selected publications · OpenAlex · Citations received by year: 5 · Annual history coverage 3/32023 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32024 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32025 · All selected publications · OpenAlex · Citations received by year: 4 · Annual history coverage 3/32026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/3 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications333/3
2018All selected publications233/3
2019All selected publications233/3
2020All selected publications133/3
2021All selected publications033/3
2022All selected publications533/3
2023All selected publications133/3
2024All selected publications033/3
2025All selected publications433/3
2026All selected publications033/3

Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗

Crossref citation distribution

Latest Crossref totals for the selected publications; not citations received in the selected years.

Mean3.0
Median1
No citations11–516–20121+0Unknown0

Unknown counts are excluded from the mean, median and cited-publication rate.

Journal comparison

Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.

Journal / publisherPublicationsCrossref citationsOpenAlex citationsOpenAlex coverageCrossref meanCrossref medianCrossref cited %*Crossref coverage
International Journal of Research in Business and Social Science
SSBFNET
39183/33.0166.73/3 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 3 →

Most cited · Crossref

JOURNAL ARTICLE

The Effect of Positive Psychological Capital on Emotional Labor

Idil Tamer

International Journal of Research in Business and Social Science · 2015

Read abstract

In modern age, positive psychological capital is as important as financial capital for organizational development and sustainability. Efficacy, hope, optimism, and resilience are the dimensions of positive psychological capital. Emotional labor is defined by Hochschild as control of self emotions at work by workers who have a high degree of contact with coworkers within the organization or with external clients, so as to create an expression, voice or body gesture which is acceptible to the clients. Emotional labor is analysized under three components: surface acting, deep acting and naturally felt emotions. This study is aimed to investigate the impact of positive psychological capital on emotional labor. So a research is conducted with the aim of exploring the relationship between the sub-dimensions of psychological capital and emotional labour.

DOI 10.20525/ijrbs.v4i2.238 Crossref citations15 OpenAlex citations
JOURNAL ARTICLE

How emotional labor affects job performance in hospitality employees

Nairei Hori · Ren-Feng Chao

International Journal of Research in Business and Social Science · 2022

Read abstract

The study examines how surface acting and deep acting affect emotional exhaustion and job performance in the hotel industry and whether emotional intelligence has a moderating effect on the relationship. The study was conducted using a questionnaire survey, and the data were analyzed using a structural equation model. The main findings of the study demonstrate that surface acting has no effect on emotional exhaustion while deep acting has a negative effect on emotional exhaustion. This indicates that deep acting not only produces better service performance but also reduces emotional exhaustion. Moreover, surface acting and deep acting both have a positive effect on job performance, showing that both acting skills are all about demonstrating a better job performance at work. Furthermore, emotional intelligence has a moderating effect on the relationships between surface acting and job performance and deep acting and job performance, this indicates that employees with higher emotional intelligence are more likely to perform a more effective outcome of acting on job performance, regardless of whether it is surface acting or deep acting. But this phenomenon only occurs when employees are not experiencing emotional exhaustion. If employees are already experiencing emotional exhaustion, emotional intelligence does not have any moderation effect on job performance.

DOI 10.20525/ijrbs.v11i3.17331 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

Navigating emotional labour: the role of deep acting in enhancing job performance and customer relations in the South African racecourse industry

Tshepo Mabotja · Nomonde Ngcobo

International Journal of Research in Business and Social Science · 2024

Read abstract

This study aims to examine the effects of deep acting on employees employed at the racecourse. The objective of this study is to examine the effects of deep acting, a type of emotional labour, on the well-being and job performance of service employees in the hotel industry in South Africa. Additionally, the study intends to provide effective coping strategies to minimise any negative consequences of emotional labour. This study employs a qualitative methodology, utilising purposive sampling to choose eight participants from the racecourse industry. The data was gathered using semi-structured in-depth interviews, enabling a thorough investigation of the participants' experiences and perceptions. Thematic analysis was employed to examine the data and discover significant themes and patterns pertaining to the practice of deep acting and its effects. According to the study, sales assistants reported that deep acting was less stressful than surface acting. The practice of deep acting had a positive impact on the job performance and communication abilities of the sales associates, hence contributing to their professional development. Notwithstanding these advantages, certain individuals experienced a sense of being underappreciated by their employers due to the emotional work they performed. The results indicate that engaging in deep acting promotes a heightened sense of empathy towards clients and improves the performance of sales associates as a result of their cumulative work experience. This research emphasises the necessity for organisations, especially those in the hospitality sector, to acknowledge and endorse the emotional labour carried out by their employees. By acknowledging the beneficial aspects of deep acting and providing appropriate coping mechanisms, employers can help alleviate potential negative impacts on employee well-being. Acquiring this comprehension can result in improved management techniques that foster employee contentment and productivity. This study adds to the scarce body of scholarship on emotional work in the South African setting, particularly within the racecourse business. This study presents innovative perspectives on the impact of deep acting on service employees and provides practical approaches for efficiently managing emotional labour. The research highlights the significance of maintaining a balance between employees' self-management and their regulation of client interactions, which ultimately improves the overall quality of customer service and staff satisfaction.

DOI 10.20525/ijrbs.v13i5.34750 Crossref citations1 OpenAlex citations

Selected results

JOURNAL ARTICLE

Navigating emotional labour: the role of deep acting in enhancing job performance and customer relations in the South African racecourse industry

Tshepo Mabotja · Nomonde Ngcobo

International Journal of Research in Business and Social Science · 2024

Read abstract

This study aims to examine the effects of deep acting on employees employed at the racecourse. The objective of this study is to examine the effects of deep acting, a type of emotional labour, on the well-being and job performance of service employees in the hotel industry in South Africa. Additionally, the study intends to provide effective coping strategies to minimise any negative consequences of emotional labour. This study employs a qualitative methodology, utilising purposive sampling to choose eight participants from the racecourse industry. The data was gathered using semi-structured in-depth interviews, enabling a thorough investigation of the participants' experiences and perceptions. Thematic analysis was employed to examine the data and discover significant themes and patterns pertaining to the practice of deep acting and its effects. According to the study, sales assistants reported that deep acting was less stressful than surface acting. The practice of deep acting had a positive impact on the job performance and communication abilities of the sales associates, hence contributing to their professional development. Notwithstanding these advantages, certain individuals experienced a sense of being underappreciated by their employers due to the emotional work they performed. The results indicate that engaging in deep acting promotes a heightened sense of empathy towards clients and improves the performance of sales associates as a result of their cumulative work experience. This research emphasises the necessity for organisations, especially those in the hospitality sector, to acknowledge and endorse the emotional labour carried out by their employees. By acknowledging the beneficial aspects of deep acting and providing appropriate coping mechanisms, employers can help alleviate potential negative impacts on employee well-being. Acquiring this comprehension can result in improved management techniques that foster employee contentment and productivity. This study adds to the scarce body of scholarship on emotional work in the South African setting, particularly within the racecourse business. This study presents innovative perspectives on the impact of deep acting on service employees and provides practical approaches for efficiently managing emotional labour. The research highlights the significance of maintaining a balance between employees' self-management and their regulation of client interactions, which ultimately improves the overall quality of customer service and staff satisfaction.

DOI 10.20525/ijrbs.v13i5.34750 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

How emotional labor affects job performance in hospitality employees

Nairei Hori · Ren-Feng Chao

International Journal of Research in Business and Social Science · 2022

Read abstract

The study examines how surface acting and deep acting affect emotional exhaustion and job performance in the hotel industry and whether emotional intelligence has a moderating effect on the relationship. The study was conducted using a questionnaire survey, and the data were analyzed using a structural equation model. The main findings of the study demonstrate that surface acting has no effect on emotional exhaustion while deep acting has a negative effect on emotional exhaustion. This indicates that deep acting not only produces better service performance but also reduces emotional exhaustion. Moreover, surface acting and deep acting both have a positive effect on job performance, showing that both acting skills are all about demonstrating a better job performance at work. Furthermore, emotional intelligence has a moderating effect on the relationships between surface acting and job performance and deep acting and job performance, this indicates that employees with higher emotional intelligence are more likely to perform a more effective outcome of acting on job performance, regardless of whether it is surface acting or deep acting. But this phenomenon only occurs when employees are not experiencing emotional exhaustion. If employees are already experiencing emotional exhaustion, emotional intelligence does not have any moderation effect on job performance.

DOI 10.20525/ijrbs.v11i3.17331 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

The Effect of Positive Psychological Capital on Emotional Labor

Idil Tamer

International Journal of Research in Business and Social Science · 2015

Read abstract

In modern age, positive psychological capital is as important as financial capital for organizational development and sustainability. Efficacy, hope, optimism, and resilience are the dimensions of positive psychological capital. Emotional labor is defined by Hochschild as control of self emotions at work by workers who have a high degree of contact with coworkers within the organization or with external clients, so as to create an expression, voice or body gesture which is acceptible to the clients. Emotional labor is analysized under three components: surface acting, deep acting and naturally felt emotions. This study is aimed to investigate the impact of positive psychological capital on emotional labor. So a research is conducted with the aim of exploring the relationship between the sub-dimensions of psychological capital and emotional labour.

DOI 10.20525/ijrbs.v4i2.238 Crossref citations15 OpenAlex citations

Data coverage & freshness

Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.

Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0

SourceMost recent successful journal syncLatest attempt
crossref21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
ojs-rest21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 06:46 UTC
oai-pmh20 Oct 2026 19:55 UTC · ijrbscomplete · ijrbs · 20 Oct 2026 19:50 UTC
openalex-enrichment21 Oct 2026 07:23 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
Full import history & methodology →