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Record W7036584991

Corporate Tax Avoidance and Customer Satisfaction

2018· other· en· W7036584991 on OpenAlexaff

Bibliographic record

VenueScholarSpace (University of Hawaii at Manoa) · 2018
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCustomer satisfactionCustomer retentionCustomer profitabilityCustomer equityCustomer delightTax avoidanceCustomer advocacyService quality
DOInot available

Abstract

fetched live from OpenAlex

We examine the empirical association between customer satisfaction and tax avoidance. Customer satisfaction is a valuable intangible asset for most firms. On the other hand, tax avoidance is considered a socially undesirable corporate practice, which may harm firm reputation. Therefore, we argue that firms that focus on satisfying customers will avoid engaging in excessively risky tax policies. Using American Customer Satisfaction Index score (ACSI) as a measure of customer satisfaction, we find that customer satisfaction has a negative association with uncertain tax benefits (UTB). This finding is supported by a positive relation between customer satisfaction and cash effective tax rate, a negative relation between customer satisfaction and interests and penalties imposed by the Internal Revenue Service (IRS) upon tax audit. Taken together, we conclude that firms that are more concerned about customer satisfaction and reputation have a higher likelihood of

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

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