MétaCan
Menu
Back to cohort

Shaping hedonic-utilitarian attitudes and consumer Intentions: The determinant role of the indulgence vs. restraint culture dimension

2025· article· en· W4410942577 on OpenAlexafffundabout
Ali Heydari, Michel Laroche, Michèle Paulin, Marie-Odile Richard

Bibliographic record

VenueJournal of Retailing and Consumer Services · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsConcordia UniversityRoyal Bank of CanadaCape Breton University
FundersFonds de Recherche du Québec-Société et Culture
KeywordsIndulgenceDimension (graph theory)Consumer CulturePsychologySocial psychologyBusinessAdvertisingPolitical scienceMathematicsLaw

Abstract

fetched live from OpenAlex

This paper utilizes the newly developed individual-level scale for the indulgence vs. restraint cultural dimension to test a conceptual model examining its role as a determinant of hedonic and utilitarian attitudes and its impact on word-of-mouth (WOM) and repurchase intentions. The model explores the mediating role of positive post-purchase emotions on the influence of indulgence vs. restraint on hedonic and utilitarian attitudes. It also serves as a nomological framework for the newly developed individual-level indulgence vs. restraint scale. Using data from two product and service contexts (restaurant and car/cellphone, n = 458 Canadian and American respondents via MTurk), the results reveal that both hedonic and utilitarian attitudes mediate the relationships between individual-level indulgence vs. restraint and WOM and repurchase intentions, with stronger mediation for hedonic attitudes. Positive post-purchase emotions further mediate the relationships between indulgence vs. restraint and both attitudes. Sweetspot analysis was applied to enhance causal inference and reliability of mediation relationships. The study provides insights for aligning resources, communication, and marketing strategies with diverse customer needs across product and service settings.

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 score0.174
Threshold uncertainty score0.344

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 head0.016
GPT teacher head0.256
Teacher spread0.239 · 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

Citations9
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Retailing and Consumer ServicesSame topicConsumer Behavior in Brand Consumption and IdentificationFrench-language works237,207