<abstract xmlns="http://www.w3.org/1999/xhtml"><p>How long a tourist stays in a host country acts as an indicator of tourism industry’s contribution towards the national economy. The purpose of this study is to examine how socio-demographic characteristics of international tourists, their travelling purpose, tourism products and characteristics of the destination influence the length of stay in Norway, by estimating a parametric survival model. Total cost of trip, purpose of travel, type of accommodation and transportation, age of tourist and geographical area are key elements that explain the variation in the length of tourist stay in Norway. The Cox proportional hazard model with time-independent covariates indicates the survival probability of tourists with less budget constraints and younger ages is higher than that of low-spending tourists and elderly travelers. Moreover, tourists with the purpose of friend and family visitation are at lower risk of leaving Norway than are tourists with other purposes. In terms of tourism products, choosing camping sites as the type of accommodation and road transport as the mode of transportation are associated with the highest survival probability. Another key finding is that tourists stay longer in northern Norway than in southern Norway; hence, on average, tourists’ overall expenditures are higher in northern Norway.</p></abstract>

How long a tourist stays in a host country acts as an indicator of tourism industry’s contribution towards the national economy. The purpose of this study is to examine how socio-demographic characteristics of international tourists, their travelling purpose, tourism products and characteristics of the destination influence the length of stay in Norway, by estimating a parametric survival model. Total cost of trip, purpose of travel, type of accommodation and transportation, age of tourist and geographical area are key elements that explain the variation in the length of tourist stay in Norway. The Cox proportional hazard model with time-independent covariates indicates the survival probability of tourists with less budget constraints and younger ages is higher than that of low-spending tourists and elderly travelers. Moreover, tourists with the purpose of friend and family visitation are at lower risk of leaving Norway than are tourists with other purposes. In terms of tourism products, choosing camping sites as the type of accommodation and road transport as the mode of transportation are associated with the highest survival probability. Another key finding is that tourists stay longer in northern Norway than in southern Norway; hence, on average, tourists’ overall expenditures are higher in northern Norway.

Determinants of trip duration for international tourists in Norway; a parametric survival analysis

European Journal of Tourism, Hospitality and Recreation

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

How long a tourist stays in a host country acts as an indicator of tourism industry’s contribution towards the national economy. The purpose of this study is...

Determinants of trip duration for international tourists in Norway; a parametric survival analysis

Publié en ligne: 10 oct. 2017

Pages: 75 - 86

Reçu: 19 avr. 2017

Accepté: 27 août 2017

DOI: https://doi.org/10.1515/ejthr-2017-0008

Mots clés
Tourism, Length of stay, Survival analysis, Cox proportional hazard model, Weibull distribution

© 2017 Tannaz Alizadeh Ashrafi et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Determinants of trip duration for international tourists in Norway; a parametric survival analysis

Publié en ligne: 10 oct. 2017

Pages: 75 - 86

Reçu: 19 avr. 2017

Accepté: 27 août 2017

DOI: https://doi.org/10.1515/ejthr-2017-0008

Mots clésTourism, Length of stay, Survival analysis, Cox proportional hazard model, Weibull distribution

© 2017 Tannaz Alizadeh Ashrafi et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Tourism, Length of stay, Survival analysis, Cox proportional hazard model, Weibull distribution