Exportar Publicação
A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.
Marques, C., Mohsin, A. & Lengler, J. (2018). A multinational comparative study highlighting students' travel motivations and touristic trends. Journal of Destination Marketing and Management. 10, 87-100
C. M. Marques et al., "A multinational comparative study highlighting students' travel motivations and touristic trends", in Journal of Destination Marketing and Management, vol. 10, pp. 87-100, 2018
@article{marques2018_1734883063232, author = "Marques, C. and Mohsin, A. and Lengler, J.", title = "A multinational comparative study highlighting students' travel motivations and touristic trends", journal = "Journal of Destination Marketing and Management", year = "2018", volume = "10", number = "", doi = "10.1016/j.jdmm.2018.06.002", pages = "87-100", url = "https://www.sciencedirect.com/science/article/pii/S2212571X17303773?via%3Dihub" }
TY - JOUR TI - A multinational comparative study highlighting students' travel motivations and touristic trends T2 - Journal of Destination Marketing and Management VL - 10 AU - Marques, C. AU - Mohsin, A. AU - Lengler, J. PY - 2018 SP - 87-100 SN - 2212-571X DO - 10.1016/j.jdmm.2018.06.002 UR - https://www.sciencedirect.com/science/article/pii/S2212571X17303773?via%3Dihub AB - The aim of this study is to assess differences and commonalities in the student travel market across different countries and to determine typologies based on touristic attractions/activities. The study generates groups based on travel motivations largely drawn from the Leisure Motivation Scale and other relevant tourism literature. To achieve the aim, data is obtained from a sample of 3,431 respondents from eight countries i.e. Brazil, India, Malaysia, Pakistan, Portugal, Spain, Thailand, and the USA. The data are analysed using two Principal Component Analyses (PCA), a combination of two clustering methods - the Ward method, and an optimal solution method, the K-Means method. Seven clusters based on touristic attractions/activities emerged. The findings from the current study suggest that perceptions of touristic attractions/activities are different by country although some similarities do exist. Besides providing important new insights for theory, this large comparative study also suggests synergies that could be generated from the information for both destination marketers and managers. ER -