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Record W2889355033 · doi:10.5539/ass.v14n9p107

Services Marketing Mix of Starbucks Coffee in Bangkok, Thailand

2018· article· en· W2889355033 on OpenAlex

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

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicMarketing and Advertising Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPromotion (chess)MarketingBusinessProduct (mathematics)Marketing mixAdvertisingCoffee shop

Abstract

fetched live from OpenAlex

The purposes of this study were to identify the importance of services marketing mix influencing the Starbucks consumers in Bangkok, Thailand, to examine the relationship between personal factors and consumer behaviors and to examine the relationship between services marketing mix and consumers behaviors.A questionnaire survey was used. The sample was 400 Starbucks coffee consumers. It was found that the respondents were female and male of 63.90 percent and 36.10 percent respectively. The majority respondents were in age group 21-30 years old, the majority occupation were office workers with level of monthly income more than 30,000 baht. The majority of respondents went to Starbucks coffee 1-2 times a week. The average expenditure of each purchase was 101-200 baht with the beverage size of Grande (16 oz.).The majority favorite beverage was Iced Cappuccino. The reason for buying Starbucks beverages was the flavor of coffee.The results indicated that the most importance of services marketing mix was product, process, people, place, physical environment, promotion and price, respectively. Both personal factors and components of services marketing mix affected consumer behaviors. The results showed that gender affected three consumer behaviors; the frequency of visit at Starbucks shop, cup sizes and favorite beverage. Career affected all five consumer behaviors. Age affected the frequency of visit the Starbucks shop and favorite beverage. While education and income level affected two consumer behaviors; the frequency of visit the Starbucks coffee shop and expenditure of each purchase.

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: none
Teacher disagreement score0.524
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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