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Record W2111253206 · doi:10.5539/ijps.v6n3p88

The Mediating Role of Job Burnout in the Relationship between Role Conflict and Job Performance: An Empirical Research of Hotel Frontline Service Employees in China

2014· article· en· W2111253206 on OpenAlexvenueno aff
Li Zhou, Liu Yong, Danling Luo

Bibliographic record

VenueInternational Journal of Psychological Studies · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyBurnoutJob performanceSocial psychologyJob attitudeHospitalityJob satisfactionService (business)Role conflictHospitality industryService qualityEmpirical researchQuality (philosophy)Applied psychologyMarketingBusinessPolitical scienceTourismClinical psychology

Abstract

fetched live from OpenAlex

As an increasingly fierce competition in hospitality industry?the service quality of frontline service employeesdetermine the success of hotels. Therefore, it is significant to improve the service quality of frontline serviceemployees by enhancing their job performance. According to the conservation of resources theory, frontlineservice employees are easily confronted with role conflicts, which result in job burnout and negatively influencejob performance. However, the relationship between “role conflict-burnout-job performance” is not consistentaccording to previous studies. Motivated by the theoretical concern to further understanding of this subject, thepurpose of this article is to explore whether role conflict will affect job performance through job burnout. Basedon the data of 189 frontline service employees from 18 budget hotels, this study tests the hypotheses. The resultsshow that: (1) Role conflict is positively related to burnout; (2) Both role conflict and burnout are negativelyrelated to job performance; (3) Burnout partially mediated the relationship between role conflict and jobperformance. Implications for practices are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.154
GPT teacher head0.444
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2014
Admission routes1
Has abstractyes

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