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Record W4205186907 · doi:10.17762/de.vol2022iss1.8775

Effect of Consumer Trust on Consumer Buying Behavior towards Automobiles

2022· article· en· W4205186907 on OpenAlexvenueno aff
S. Shanmugasundaram U. Premkumar

Bibliographic record

VenueDesign Engineering · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSimple random sampleNewspaperSample (material)AdvertisingData collectionPsychologyMarketingConsumer behaviourBusinessStatisticsMedicineEnvironmental healthMathematics

Abstract

fetched live from OpenAlex

` The intention of the present research study is to explore and analyze the influence of the consumer trust on the buying behavior of the consumers towards the automobile’s purchase. The data needed for the study was both primary and secondary. Primary data was collected through questionnaires and also through face to face questioning. The secondary data was collected through the review of the previous study done in this regard. The secondary data was also collected from the newspapers, published reports, journals and websites. The study has been done among the consumers who purchase automobiles in Chennai. The respondents for the study are selected through simple random sampling and the sample size of the study is 100. The data needed for the study has been collected through a questionnaire and the analytical part of the study is done with the help of regression. The findings of the analysis show that __________.

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)0.002
metaresearch head score (Gemma)0.016
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.021
GPT teacher head0.239
Teacher spread0.217 · 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
Published2022
Admission routes1
Has abstractyes

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