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Record W2010349348 · doi:10.5539/ijms.v7n1p106

Multinational Fast Food Chains’ “Global Think, Local Act Strategy” and Consumer Preferences in Turkey

2015· article· en· W2010349348 on OpenAlexvenueno aff
İsmail Metin, Yıldıray KIZGIN

Bibliographic record

VenueInternational Journal of Marketing Studies · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationBusinessMarketingGlocalizationContext (archaeology)PerceptionAdvertisingGlobalizationEconomicsPsychology

Abstract

fetched live from OpenAlex

In global competitive environment, to move one step forward fast-food companies turn to different methods of international marketing. Foremost among these international marketing methods is “Think global, act local”. There are lots of differences among the nations’ cultures and it may affect the cooking or preparing the food and beverage. In this context, to adapt their selves to local communities, global fast-food chains have to take into consideration about the economic, cultural and religious properties of the consumers who live all over the world. The purpose of this study is to investigate consumers’ perceptions and behaviors regarding the multinational fast-food chains’ glocal activities in Turkey. The paper also addresses a research question that Turkish consumers pay attention to multinational fast-food chains’ strategy or not. The results of individual surveys show that marital status and age of the consumers have positive impacts on preferring and perceiving glocal menus of the multinational fast-food chains. Also, it is found that the advertisements regarding the multinational fast-food chains have positive effect on perception and they increase the perception level of the fast food chains’ glocal menus. Mc Donald’s restaurants’ and Domino’s Pizza restaurants’ customers have the highest perception possibility regarding the glocalized menus. This result indicates that marketing managers of fast-food chains should take a glocalized approach via advertisements to success in the local markets. In regards, by theoretical and empirical analysis at our study it is aimed to contribute literature on the subject.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.463
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.058
GPT teacher head0.301
Teacher spread0.243 · 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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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