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Record W4403549219 · doi:10.1108/ijchm-04-2024-0535

Unraveling the customer orientation paradox

2024· article· en· W4403549219 on OpenAlexaff
Hyunghwa Oh, WooMi Jo, Jinok Susanna Kim, Jeongdoo Park

Bibliographic record

VenueInternational Journal of Contemporary Hospitality Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversity of GuelphGuelph General HospitalTed Rogers Centre for Heart Research
Fundersnot available
KeywordsCustomer orientationOrientation (vector space)BusinessMarketingGeometryMathematics

Abstract

fetched live from OpenAlex

Purpose This study aims to examine the roles of customer orientation (CO) and two distinct stress coping strategies – problem-focused (PC) and emotion-focused (EC) – in the positive relationship between customer incivility (CI) and job stress (JS). Design/methodology/approach Data were collected via a survey of casino dealers in South Korea. Common method variance was assessed using an unmeasured latent method construct, confirming both convergent and discriminant validity. Collinearity diagnostics were conducted to evaluate potential multicollinearity among independent variables. Hypotheses were tested using PROCESS Macro Models 1 and 3 to examine moderating effects and three-way interactions. Findings CI is positively related to JS. Employees with high CO experience greater JS when faced with CI compared to those with low CO. Highly customer-oriented employees with low coping strategies encounter significant JS when dealing with uncivil casino patrons. Practical implications Casino practitioners should balance CO strategies with effective stress management and support systems. This finding calls for a reevaluation of training programs and policies to maintain high service quality while ensuring employee well-being. Originality/value This study challenges the traditional view of CO as merely a stress-buffering factor by revealing its paradoxical role. It identifies individuals more susceptible to JS and demonstrates how the interaction between CI, CO and coping strategies (i.e. PC or EC) can escalate JS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.026
GPT teacher head0.287
Teacher spread0.261 · 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 designNot applicable
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

Citations5
Published2024
Admission routes1
Has abstractyes

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