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Record W3011490234 · doi:10.5430/ijfr.v11n2p88

Consumers’ Purchase Intention Toward Ergonomic Footwear in Malaysia

2020· article· en· W3011490234 on OpenAlexvenueno aff
Shyue Chuan Chong, Foong Yee Tan, Pei Yew Mah, Choon Wei Low

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsWord of mouthExpectancy theoryContext (archaeology)MarketingAdvertisingPsychologyValue (mathematics)Consumption (sociology)BusinessHuman factors and ergonomicsConsumer behaviourSocial psychologyPoison controlMedicineEnvironmental healthSociologyGeographyComputer science

Abstract

fetched live from OpenAlex

Ergonomic footwear is a type of shoe specifically designed for consumers to treat foot problems. In accelerating concern on foot health nowadays, ergonomic footwear is introduced to fill the gap in the context of Malaysia. This study applied the Theory of Planned Behaviour and Expectancy-Value Theory to explore the consumers’ purchase intention toward ergonomic footwear. Targeted respondents were adults in Klang Valley, Malaysia aged from 21 years and above through judgmental sampling. A total of 221 responses were collected using a survey questionnaire from June to July 2018. This study found that utilitarian consumption, consumer perceived value and perceived trust have a significant positive relationship with the purchase intention. Meanwhile, the word-of-mouth shows the insignificant relationship between purchase intention. Word-of-mouth is unimportant might be due to contrary word-of-mouth spread by experienced customers, and perhaps the less tendency the consumers rely on word-of-mouth.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.364
Teacher spread0.237 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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