Enhancing understanding of tourist spending using unconditional quantile regression
An important policy goal for governments is to increase expenditures by inbound tourists, requiring appropriate statistical analysis to correctly identify important drivers of spending. In 2014 the UK received 34.4 million visits from overseas residents, netting L5.5 billion, underscoring the import...
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Veröffentlicht in: | Annals of tourism research 2017-09, Vol.66, p.188-191 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | An important policy goal for governments is to increase expenditures by inbound tourists, requiring appropriate statistical analysis to correctly identify important drivers of spending. In 2014 the UK received 34.4 million visits from overseas residents, netting L5.5 billion, underscoring the importance of accurate analysis. Here, Rudkin and Sharma show that past emphasis on promoting longer tourist stays misses key factors such as reason for travel (business or leisure) mainly due to inappropriate methodologies employed previously. They demonstrate that conventional use of ordinary least squares and standard quantile regressions can lead to incorrect inferences and suboptimal decisions in relation to expenditure promoting activities. |
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ISSN: | 0160-7383 1873-7722 |
DOI: | 10.1016/j.annals.2017.06.003 |