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Record W2117022799 · doi:10.5430/bmr.v1n1p48

A Study of Consuming Behaviors of Budget Coffee

2012· article· en· W2117022799 on OpenAlex
Li-Mei Hung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBusiness and Management Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasingPreferenceProduct (mathematics)BusinessConsumer behaviourSample (material)MarketingAdvertisingRegression analysisEconomicsMicroeconomicsStatisticsMathematics

Abstract

fetched live from OpenAlex

This research aims to explore the benefits of budget coffee shop chains pursued by the consumers, conduct cost effectiveness analysis on product purchases, compare the differences between the different types of consumer characteristics, and attempt to conduct an in-depth analysis on the budget coffee shop chains’ current situations and their relation with consumer behavior. The source of the research sample is 480 randomly selected consumers in Taichung, including 168 males and 312 females. The data was collected via a closed questionnaire, and the linear relationships for basic individual information and consumer behavior in regards to consumer consideration and characteristics were tested via the SPSS version 12.0 of hierarchical regression. The results showed that, amongst elements of consumer considerations, ‘server friendliness’ seems to be most important, and ‘media advertising’ seems to be the least important. As for consumer characteristics, ‘personal preference’ is most important, and ‘coffee has already become a part of life’ is the least important. As indicated from the regression analysis, consumers with monthly incomes between NT$20,000 and NT$30,000 have significantly higher consumer characteristics than consumers with monthly incomes of lower than NT$20,000. Moreover, consumers with steady jobs possess significantly higher consumer characteristics than consumers without jobs. Consumers purchasing more than once a week have higher consumer characteristics than those who make purchases less than once a week, and weekday consumers have significantly higher consumer characteristics than weekend consumers.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.084
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.113
GPT teacher head0.369
Teacher spread0.256 · 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