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Record W4220656582 · doi:10.5539/ijbm.v17n4p53

The Future of Tipping in Hospitality: An Exploratory Study on Consumer Attitude in Canada

2022· article· en· W4220656582 on OpenAlexaffabout
Sylvain Charlebois, Poppy Riddle, Janet Music

Bibliographic record

VenueInternational Journal of Business and Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHospitalityExploratory researchProsocial behaviorPsychologyFeelingPerceptionMarketingSocial psychologyHospitality industryAffect (linguistics)Social mediaBusinessPolitical scienceSociologyTourism

Abstract

fetched live from OpenAlex

This exploratory study examines the perception of gratuity behaviours in Canada during the COVID-19 pandemic. Using a nationwide survey, results were analyzed using statistical and cross tabulation analysis and interpreted through a prosocial spending framework to understand consumer behaviour in which food service patrons perceive emotional benefits from the experience. We find tipping is still strongly supported and most do not anticipate this to change. Social expectations of tipping amounts have not changed and remain at 15% (restaurant) and 10% (deliveries). Though most respondents perceive an increase in social expectations during the pandemic, there seems to be a slight decrease in support for tipping with the youngest age range and more supportive of tipping alternatives. Financial impacts of income loss may have contributed to less use of tipped services but does not seem to affect tipping behaviours. With people feeling in control of their own decisions, and perceive it as benefiting others and enabling connection, there is still strong support for tipping as a social norm.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.325
Teacher spread0.300 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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