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Record W4414116181 · doi:10.24124/2025/30570

Consumer behavior on Facebook Marketplace: A cross-culture study of India and Canada

2025· dissertation· en· W4414116181 on OpenAlexaboutno aff
Rana Kidwai

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsInterpersonal communicationMediationRisk perceptionUsabilityInterpersonal influenceConsumer behaviourSelf-disclosureQuality (philosophy)

Abstract

fetched live from OpenAlex

,This study examines the cultural factors influencing differences in Facebook Marketplace usage between Indian and Canadian consumers. The research identified a model for factors influencing consumers behavior explaining by User Satisfaction, Interpersonal trust, Perceived Usefulness, Perceived Ease of Use, Financial Risk, Privacy Risk, Quality Risk and Facilitating Conditions on cross culture basis. Results of linear regression showed that there were significant differences on User satisfaction, Interpersonal trust and Perceived Usefulness but no significant differences in Facilitating condition between Indian and Canadian consumers. Furthermore, the study analyzed the mediation model which presented interpersonal trust, perceived usefulness, perceived ease of use and financial risk as a mediator between culture and user satisfaction. The implications of the study are discussed, and further research is suggested.

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)0.002
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 score0.021
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0110.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.329
Teacher spread0.318 · 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
Published2025
Admission routes1
Has abstractyes

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