MétaCan
Menu
Back to cohort
Record W4399592101 · doi:10.5267/j.msl.2024.6.002

The association of interactivity, perception of product quality and cost with purchase intention: A moderated mediation model

2024· article· en· W4399592101 on OpenAlexvenueno aff
Rowena Summerlin, Wendy Powell, Emiko Fukuda

Bibliographic record

VenueManagement Science Letters · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsMediationAssociation (psychology)InteractivityModerated mediationPerceptionProduct (mathematics)Quality (philosophy)PsychologyMarketingBusinessSocial psychologyComputer scienceAdvertisingMultimediaMathematicsSociology

Abstract

fetched live from OpenAlex

This study investigates whether perception of product quality positively mediates the relationship between interactivity and purchase intention and whether the relationship between interactivity and perception of product quality is moderated by cost such that higher-priced items strengthen the relationship. Differences between those consumers purchasing personally or as a business were considered. Three hundred and forty-nine participants experienced a simulated environment within a real-world retail website they had previously shopped at. Results from a questionnaire were analysed using moderated mediation regression analysis. The hypothesized theoretical model was supported for individual consumers with results indicating that the effect of interactivity on purchase intention is mediated by product quality, and this indirect effect is moderated by cost. No such result was found for business consumers. This research demonstrates a notable difference between purchasing behaviours of business and individual consumers when considering interactivity and perception of product quality.

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)0.006
metaresearch head score (Gemma)0.021
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.086
GPT teacher head0.392
Teacher spread0.306 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueManagement Science LettersSame topicTechnology Adoption and User BehaviourFrench-language works237,207