A flow-through analysis of the US lodging industry during the great recession

Singh, Amrik; Dev, Chekitan S.; Mandelbaum, Robert

doi:10.1108/ijchm-12-2012-0260

Cited by 18 publications

(22 citation statements)

References 9 publications

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“…1 we observe that the impact of the 2008 financial crisis on tourism growth only lasted for a year, as in 2010 tourist arrivals started growing again in all destinations except Chile. This result is in line with previous research by Song et al (2011) and Singh et al (2014). Fig.…”

Section: Datasupporting

confidence: 94%

Two-dimensional mapping of Asia Pacific destinations combining tourism and economic indicators

Clavería

2017

Asia Pacific Journal of Tourism Research

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The present study aims to cluster five Asia Pacific destinations (Cambodia, Hong Kong, Indonesia, the Philippines, and Singapore) with respect to other countries according to the evolution of the main tourism and economic indicators over the period between 2000 and 2014. By assigning a numerical value to each country corresponding to its position, we summarize all the information into two components ("tourism expenditure and profitability of tourism activity" and "tourism development and economic growth") using different multivariate techniques for dimensionality reduction. By means of perceptual maps, we find that the five Asia Pacific destinations can be clustered into three different groups: Hong Kong and Singapore, which are the most mature markets; Indonesia and the Philippines, with moderate growth rates in most variables; and Cambodia, with top positions in all variables, showing a huge potential in terms of growth and tourism development and the challenges derived therefrom.

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Section: Datasupporting

confidence: 94%

Two-dimensional mapping of Asia Pacific destinations combining tourism and economic indicators

Clavería

2017

Asia Pacific Journal of Tourism Research

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“…First, we find that the 2008 financial crisis had an impact on 2009 tourism growth, but in 2010 all variables started growing again. This result is in line with previous research on demand for hotel rooms in Hong Kong by Song et al (2011), and in the US lodging industry by Singh et al (2014).…”

Section: Graphical Analysissupporting

confidence: 92%

Positioning and clustering of the world’s top tourist destinations by means of dimensionality reduction techniques for categorical data

Clavería

Poluzzi

2017

Journal of Destination Marketing & Management

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The present study aims to cluster the world's top tourism destinations based on the growth of the main tourism indicators over the period between 2000 and 2010. We rank the destinations regarding the average growth rate over the sample period. We find that both China and Turkey are at the top of the rankings of all variables. By assigning a numerical value to each country corresponding to its position, we compute Spearman's coefficient and find a negative correlation between a destination's dependency on tourism and the profitability of the tourism activity. Finally, we use several multivariate techniques for dimensionality reduction in order to cluster all destinations according to their positioning. We obtain three groups: China on the one hand, Turkey on the other, and the rest of the destinations. These results show that the persistent growth of the tourism industry poses different challenges in different markets regarding destination marketing and management.

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“…demand for hotel accommodation in a destination), the important determinants for hotel demand are (Chen, 2013;Singh et al, 2014).…”

Section: New Explanatory Variablesmentioning

confidence: 99%

New developments in tourism and hotel demand modeling and forecasting

Song

Shen

2017

IJCHM

240

217

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Design/Methodology/approachArticles on tourism and hotel demand modeling and forecasting published in both Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) journals were identified and analyzed. FindingsThis review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior, and consumer confidence indicators, among others. More sophisticated techniques such as Research limitations/implicationsThe main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implicationsThis review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/valueThe value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

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A flow-through analysis of the US lodging industry during the great recession

Cited by 18 publications

References 9 publications

Two-dimensional mapping of Asia Pacific destinations combining tourism and economic indicators

Two-dimensional mapping of Asia Pacific destinations combining tourism and economic indicators

Positioning and clustering of the world’s top tourist destinations by means of dimensionality reduction techniques for categorical data

New developments in tourism and hotel demand modeling and forecasting

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