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Record W2254071388

Investigation of Consumer Acculturation in Dining-out: a Comparison between Recent Chinese Immigrants and Established Chinese Immigrants in the Greater Toronto Area

2010· dissertation· en· W2254071388 on OpenAlexaboutno aff
Tianmu Yang

Bibliographic record

VenueUWSpace (University of Waterloo) · 2010
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationAcculturationChinese americansGeographySociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The interaction between culture and consumption of immigrants is an important research area in a number of fields including consumer behaviour, marketing, and ethnic studies. This article offers a specific look at issues related to the impact of acculturation on dining-out behaviour of Chinese immigrants living in the Greater Toronto Area in Canada, and the influence of individual factor of acculturation process (i.e., ethnic identification, length of residence, and age at immigration). This study focused on the similarities and comparisons between recent Chinese immigrants who have been in Canada for ten years or less and established Chinese immigrants who have been in Canada for more than ten years, in terms of their dining-out behaviour in the Greater Toronto Area. 
\n There were two samples, the recent Chinese immigrants and the established Chinese immigrants in this study. Snowball sampling was applied to recruit the total 30 participants (15 of each sample). The author started to recruit from two participants of each sample among her friends and relatives and asked the interviewers to recommend another two qualified participants. Semi-structures, in-depth interviews were employed in this study to explore the impact of culture, levels of acculturation, ethnic identity, situational factors of ethnic identification and dining-out behaviour. The interviews were audio-recorded by permission and conducted in the participant’s preferable language (in English or in Mandarin Chinese). Data analysis was guided by several previous conclusions and model in the literatures and conducted in both qualitative (coding) and quantitative (SPSS) methods. 
\n The findings resulted in some major conclusions. In terms of similarities, it is found that recent Chinese immigrants and established Chinese immigrants obtained restaurants information mostly from friends and relatives. They also searched on internet for other’s reviews, menus, and printable coupons. Secondly, result showed that Chinese immigrants perceived that because they have a long history of food, Chinese people are more willing to try different types of food when immigrated to Canada. Thirdly, situational factors such as peer influences played more significant role on dining-out decision making and self ethnic identifications than parental influences. In terms of differences, data indicated that among Chinese immigrants living in the Greater Toronto Area, recent Chinese immigrants had stronger ethnic identity to their original culture, and dined out more frequently than the established Chinese immigrants. Future, the result suggested that the highest level of Chinese ethnic food purchasing behaviour were reported by highest ethnic identifiers (ones who identified themselves as more Chinese). However, there was another important factor that influenced the levels of acculturation in dining-out behaviour more greatly than the length of immigration: the age at immigration. The study found that Chinese immigrants who immigrated at early age had the highest level of acculturation and identified themselves as more Canadian, while ones who immigrated at late life had the lowest level of acculturation and identifies themselves as more Chinese. 
\n The findings reflected the impact of culture and consumer acculturation in dining-out among Chinese immigrants in the Greater Toronto Area and could potentially contribute to the marketing implications to both ethnic and mainstream restaurant marketers. This study also gives some future thoughts on the exploration of more variables at individual differences, as well as other perspectives of research conducting such as from psychological or economic perspective.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.026
GPT teacher head0.267
Teacher spread0.241 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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