Determinants of Length of Stay: A Parametric Survival Analysis (original) (raw)

Survival Analysis in Tourism Demand: The length of stay in Latin American destinations

2007

This article analyses the determinants of the length of stay of Portuguese tourists taking vacations in Latin America, based on a questionnaire distributed on flights of a Portuguese charter airline, Air Luxor. A survival model is adopted to measure the relationship between vacation length and covariates. It is concluded that the most affluent tourists, who are motivated by culture, climate and security, will have the longest stays. The policy implication is derived.

Research Note: The Determinants of Tourists' Length of Stay: Some Further Modelling Issues

Tourism Economics, 2015

Very complicated so-called ‘survival’ (or duration) models have featured strongly in research aimed at explaining variation in tourists' length of stay at destinations. In a constructive critique of this research, Thrane (2012) has shown that use of these models lacks sound footing on conceptual as well as statistical grounds. In recent studies, length of stay has been thought of as a count variable, and the variation in this variable has accordingly been modelled with count data regression models. The purpose of the present study is to provide a constructive critique of this research. There are two conclusions. First, count data regression models should be used when analysing ‘how-many-times-something-happened’ data. Consequently, these models are not ideal when the non-discrete dependent variable is length of stay measured in days. Second, since an OLS regression analysis on the natural log of length of stay yields the same results as a far more complicated count data regressi...

Modelling tourists’ length of stay

Tourism Economics, 2016

Modelling of tourists’ length of stay (LOS) is an expanding topic of study. A common thread in this literature is the use of sophisticated statistical/econometric methods. The present study builds on and extends an article critical of the statistical craftsmanship in prior LOS modelling studies. On the basis of an updated assessment of current practice and two small-scale case studies, two main conclusions are drawn. First, the available evidence suggests that the ordinary least squares (OLS) regression model produces qualitatively similar findings to much more complicated methods, such as duration and count data models. The principle of parsimony and the so-called KISS rule thus dictate that OLS regression analysis should be the preferred estimation technique in LOS modelling studies. Second, the quality of LOS modelling studies will most likely be improved by intensifying the use of the long-established tools of the trade explicated in influential econometric textbooks rather than...

The lentgh of the stay of low cost tourism .

Awareness of tourists’ length of stay and the factors which determine that is an essential element for good planning and management at tourist destinations. This article analyses to what extent the personal characteristics of the low-cost tourist, those of the trip and stay and those of the destination itself are significant in determining the duration of a trip. To this end an econometric duration model is estimated. The results obtained show that the effect of time restrictions seem to be relevant for explaining the observed differences in length of stay, as well as the effects of the tourist’s spending capacity, prices and the differences between urban and ‘‘sun and sand’’ destinations. Furthermore, the model also allows us to analyse changes in the likelihood of the stay being ended at aspecific point in time (hazard) associated with changes in the explanatory variables, and to obtain predicted survival times for differentgroups of tourists

The length of stay of golf tourism: A survival analysis

Tourism Management, 2010

This study analyses the length of stay of golf tourists in the Algarve, on the southern coast of Portugal. The analysis employs a questionnaire to ascertain the significant characteristics influencing the length of stay of golf tourists. A survival model is used to analyse which characteristics are associated with the length of stay, taking into account the uncontrolled heterogeneity of the data. Robustness tests are implemented and policy implications are derived for improving the understanding and management of the length of stay of heterogeneous tourists.