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Record W4401879683 · doi:10.1080/1528008x.2024.2394953

Customer-Oriented Behavior in Full-Service Restaurants: A Moderated-Mediation Model of Emotional Intelligence, Work Engagement, and Customer-Oriented Attitude

2024· article· en· W4401879683 on OpenAlexaff
Hyunghwa Oh, Israt Jahan Linda, WooMi Jo

Bibliographic record

VenueJournal of Quality Assurance in Hospitality & Tourism · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of GuelphToronto Metropolitan University
Fundersnot available
KeywordsMediationCustomer engagementModerated mediationPsychologyBusinessService qualityCustomer serviceWork engagementWork (physics)Service (business)MarketingComputer scienceSocial psychologyEngineeringSociologyWorld Wide WebSocial media

Abstract

fetched live from OpenAlex

Using the job demands-resources model, this research explores the effects of emotional intelligence (EI) on customer-oriented behavior (COB) among frontline restaurant employees, with a focus on the mediating role of work engagement (WE) in the EI-COB relationship. The study also examines the moderating effects of customer-oriented attitude (COA) between EI and WE and on the mediated relationship. Data from 228 frontline restaurant employees were analyzed using Hayes’ PROCESS macro models 4 and 7. The results reveal a positive impact of EI on COB, with WE as a mediator. Moreover, COA strengthens the positive relationships between EI and WE, as well as the indirect effects of EI on COB through WE. This study simultaneously investigates both attitudinal and behavioral aspects of customer orientation, providing valuable theoretical and practical implications for restaurant employees, and laying the foundation for future research in this area.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.308
Teacher spread0.272 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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