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Record W1995090407 · doi:10.5465/ambpp.2011.65869495

EMPLOYEE SABOTAGE ASSOCIATED WITH CUSTOMER INJUSTICE: A COMPARISON OF NORTH AMERICA AND EAST ASIA

2011· article· en· W1995090407 on OpenAlexaffabout
Ruodan Shao, Daniel P. Skarlicki

Bibliographic record

VenueAcademy of Management Proceedings · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInjusticeIndividualismCustomer serviceHofstede's cultural dimensions theoryChinaBusinessMarketingCustomer satisfactionUncertainty avoidanceCultural valuesPower (physics)Service (business)PsychologySociologySocial psychologyPolitical scienceCollectivismGender studies

Abstract

fetched live from OpenAlex

Research has found that North American employees react to unfair treatment from customers by engaging in customer-directed sabotage. The present research examined whether customer service employees in East Asia react similarly toward customer injustice. Specifically, we explored whether differences in employee reactions to customer unfairness exist between China and Canada, and whether cultural values (i.e., Individualism, Uncertainty Avoidance, Power Distance) account for these differences. Surveys were administered to 203 front-line employees working in the same hotel chain in China and Canada. Results revealed that the strength of the association between customer injustice and employees' sabotage toward customer was significantly weaker in China than in Canada. Cultural values accounted for these between-country differences, with Individualism as the strongest mediatory factor. Implications and future directions 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.129
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.264
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2011
Admission routes2
Has abstractyes

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