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Record W2000682082 · doi:10.1300/j049v11n04_05

The Behavioral Implications of Consumer Trust Across Brick-and-Mortar and Online Retail Channels

2004· article· en· W2000682082 on OpenAlexaff
Qimei Chen, David A. Griffith, Fang Wan

Bibliographic record

VenueJournal of Marketing Channels · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBrick and mortarChannel (broadcasting)BusinessInteractivityMarketingLoyaltyBrickAdvertisingConsumer behaviourThe InternetComputer scienceTelecommunicationsEngineeringCivil engineeringWorld Wide Web

Abstract

fetched live from OpenAlex

Changes in the retail environment have stimulated retailers to develop strategies aimed at synchronizing multiple, complementary channels to service an increasingly diverse consumer marketplace. In this research, two studies are presented to test a model of the behavioral implications of trust in brick-and-mortar and online retail channels. Results from Study 1 indicate that trust was influenced primarily by channel interactivity, and that trust, in turn, influenced behavioral loyalty to the channel as well as intention to purchase from the channel in both brick-and-mortar and online retail channels. Results from Study 2 demonstrate carry-over effects from a retailer's online channel to its brick-and-mortar channel. Academic and practitioner implications related to multi-channel retailing are presented.

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)0.003
metaresearch head score (Gemma)0.025
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 score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.043
GPT teacher head0.308
Teacher spread0.265 · 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

Citations26
Published2004
Admission routes1
Has abstractyes

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