The Measurement of Cultural Influence on Travel Lifestyle and Behaviour using Personal Values and Sensation-Seeking Behaviour: A Comparison of Koreans in Korea and Australia
Bibliographic record
Abstract
Immigration and international “floating populations” have increased in the past decade, arousing marketers’ interest in culture. In particular, culture has been used for analysing the direction of market trends, as well as providing a better understanding of consumers’ needs, expectations and preferences within and across countries. However, cross-cultural research has been hampered by the common use of nationality as a surrogate for cultural affiliation, even though a variety of ethnic, social class, lifestyle, and subcultures exist, particularly in countries that have been built from large immigrant populations such as the United States, Canada, Australia and New Zealand (Tan, McCullough, and Teoh, 1987). Furthermore, within the tourism discipline, the study of ethnic minorities has not received as much attention as specific populations of ethnic groups such as black American, Hispanic, and Chinese in the United States. This study investigated the influences of culture on travel lifestyle and behaviour, through the comparison of Korean Australians and Koreans in Korea. Korean residents who live in Korea (N = 325) and Koreans who live in Australia (N = 306) completed a self-administered questionnaire. The questionnaire sought information in regard to travel lifestyle and behaviour as well as personal values, sensation-seeking behaviour and travel experiences, in order to investigate factors associated with the differences between the two groups in travel lifestyle and behaviour. Socio-demographic characteristics of the sample were also measured. Furthermore, a measure of acculturation was taken for the Korean Australians. Data were analysed using factor analysis, t-test, one-way ANOVA, multiple regression analysis, chi-square and cluster analysis to test the proposed hypotheses. The results of this study showed differences between the two groups of Koreans in respect of travel lifestyle and behaviour, personal values, sensationseeking behaviour and travel experiences. Cluster analysis identified five distinct groups: “affluent group travellers”, “low resource group travellers”, “active independent travellers”, “non- active independent travellers”, and “low-interest travellers”. Korean Australians were more likely than Koreans to be represented in the clusters of “active independent travellers”, “non-active independent travellers”, and “low-interest travellers”. Koreans were more likely to want to travel as part of a group than Korean Australians. Relationships between personal values, sensation-seeking behaviour and travel experiences, as well as travel lifestyle and behaviour were also found. The “low resource group traveller” within Korean Australians was likely to report having low “community values” and “life values”, while the same cluster within Koreans was likely to report having low “social values” and “life values” as opposed to the “active independent traveller” for both samples of Koreans. The “active independent traveller” in both Korean groups was more likely to report holding a strong preference for “novelty” seeking than the other cluster travellers. Korean Australians who undertake frequent international travel were more likely to be in the “active independent travellers” cluster, whereas Koreans who are frequent international travellers were more likely to be in the “affluent group travellers” cluster. Acculturation also predicted, to some extent, the travel lifestyle and behaviour of Korean Australians. Demographic variables were mostly irrelevant to travel lifestyle and behaviour in each group. This study confirmed that personal values and sensation-seeking behaviour seemed to be associated with the different travel lifestyles and behaviour of Korean Australians compared to Koreans. The differences of travel lifestyle and behaviour may be caused by different cultures. Findings of the current study reinforce the importance of culture in the tourism market. The results revealed that overall predictability of travel lifestyle and behaviour by sensation-seeking behaviour was stronger than the predictability of travel lifestyle and behaviour by personal values. However, variables such as personal values, sensation-seeking behaviour, travel experiences and demographic characteristics, which were expected to predict travel lifestyle and behaviour, did not appear to explain much variance. Future research is recommended to investigate other factors that may predict travel lifestyle and behaviour among other ethnic groups. This study suggests that marketers should acknowledge that consumers in countries with diverse cultural backgrounds also need differentiated services and products. Crosscultural insights provide opportunities for marketers to develop and extend markets in multicultural countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".