MétaCan
Menu
Back to cohort
Record W4407260520 · doi:10.1080/03081060.2025.2462970

Are online shoppers ready to use smart mobile city bus lockers?

2025· article· en· W4407260520 on OpenAlexafffundabout
Si Liu, Elkafi Hassini

Bibliographic record

VenueTransportation Planning and Technology · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransport engineeringAdvertisingEngineeringBusinessComputer science

Abstract

fetched live from OpenAlex

This research is a pioneer to introduce an innovative delivery paradigm termed Smart Mobile Lockers with City Buses (SML-CBs). The purpose of this study is to survey consumer perceptions pertaining to the adoption of this nascent technology, and in particular focusing on the prevailing attitudes among Canadian e-commerce customers towards the use of SML-CBs. The authors investigate the factors that lead the survey respondents to perceive SML-CBs as secure and to embrace their use, as well as develop two conceptual models to assess such attitudes. In addition, this paper differentiates participants' responses in various groups and through a comprehensive rating system, it identifies the participant groups that are most likely to adopt SML-CBs, which includes monthly online shoppers, participants who consistently opt for paid shipping, younger individuals, apartment dwellers, residents of Saint John's, and suburbanites.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.037
GPT teacher head0.287
Teacher spread0.250 · 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 routes3
Has abstractyes

Explore more

Same venueTransportation Planning and TechnologySame topicConsumer Retail Behavior StudiesFrench-language works237,207