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Record W2791310362 · doi:10.5539/ijms.v10n1p29

The Relationship among Consumer Attributions, Consumer Skepticism, and Perceived Corporate Social Responsibility in Taiwan

2018· article· en· W2791310362 on OpenAlexvenueno aff
Bryan H. Chen, Wan-Ching Chiu

Bibliographic record

VenueInternational Journal of Marketing Studies · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismCorporate social responsibilityAttributionStructural equation modelingPsychologyAssociation (psychology)Social responsibilitySocial psychologyMarketingBusinessPublic relationsPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

This study aimed to explore the relationship of consumer attributions, consumer skepticism toward CSR, and its influence on perceived CSR in Taiwan. Final usable questionnaires received from 659 respondents to reach the return rate of 78.8%. After confirming reliability and validity of survey questionnaire, the structural equation modeling was used for tests the model. Results were summarized as follows: (a) value-driven motives are negatively related to CSR skepticism, which was significant; however, the relationship was positive association. (b) CSR skepticism is positively related to ethical responsibility, which was supported. (c) CSR skepticism is negatively related to philanthropic responsibility, which was significant; however, the relationship was positive association. This study may make a positive contribution for business managers to understand the expectations of consumers in Taiwan.

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)0.005
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.336
Teacher spread0.259 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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