Determinants of Tourists’ Length of Stay: A Hurdle Count Data Approach

Abstract

This article analyses tourists' length of stay in a particular destination using a Hurdle Count Data model that allows us to first identify the determinants of the decision to be a same-day visitor or a tourist, and then to explain the length of stay for tourists. Apart from sociodemographic characteristics, we are interested in the effects of distance, mode of transport, and some relevant destination attributes of the destination such as tranquillity, natural environment, or climate. Another feature this article addresses is how advertising, recommendations, and previous experience at the destination affect both the probability of an overnight stay and the length of the stay. The results indicate that the determinants of the decision to stay overnight and how long to stay are not the same. Besides, a positive previous experience and having seen advertising of the destination positively affect the overnight stay decision and the number of days.

Using a consumer choice model to explain the effect of the newly developed oxford COVID-19 government stringency measure on hotel occupancy rates

“…Ozturk ( 2016 ) and Tang and Ozturk ( 2017 ) thoroughly explained the theoretical and empirical relationship between tourism, development, and growth. Other recent studies such as Calero and Turner ( 2020 ), Neuts ( 2020 ), Petrei et al ( 2020 ), Contu et al ( 2020 ), Santamaria and Filis ( 2019 ), Antolini and Grassini ( 2019 ) and Boto-Garcia et al ( 2018 ) have examined the impact of tourism on nations growth and development process, revealing beneficial impacts on international visitor recipient countries. Numerous other scholarly contributions of in the past, for example, Rugg ( 1973 ), Dwyer et al ( 2000 ), Divisekera ( 2003 ), Tosun et al ( 2003 ), Ozturk and Acaravici ( 2009 ), Tribe (2011), Song et al ( 2012 ) have also added significant value to the understanding of the determinants of international tourism.…”

International Remittances as a Driver of Domestic Tourism Expenditure: Evidence from Mexico

“…The literature on the determinants of domestic tourism expenditures is highly mixed, context-specific (Brida et al 2018; Lima, Eusébio, and Varum 2018; L. Wang et al 2018; Rashidi and Koo 2016), and focused on using micro data (Boto-García, Baños-Pino, and Álvarez 2019; Mitra et al 2019; Y. Wang and Davidson 2010).…”

“…Most of these articles use economic constraints (e.g., assets, financial difficulties, income), sociodemographic data (e.g., age, education, gender, number of household members), and travel-related variables (e.g., accommodation, activities, destination) as regressors in their analyses (Boto-García, Baños-Pino, and Álvarez 2019; Brida and Scuderi 2013).…”

A bibliometric analysis of length of stay studies in tourism

“…Research on length of stay (LOS) in tourism destinations has featured in tourism literature since the 1970s (Mak et al, 1977). Since then, many scholars have approached this concept from different perspectives to define the main determinants of LOS (Aguilar & Díaz, 2019;Alegre & Pou, 2006;Atsız et al, 2020;Barros et al, 2008;Bavik et al, 2020;Boto-García et al, 2019;de Menezes et al, 2008;Gokovali et al, 2007;Rodríguez et al, 2018;Thrane, 2016;Thrane & Farstad, 2012;Yang et al, 2011). The general consensus of previous studies is that LOS is crucial for tourism destinations because it is positively linked with high revenues from tourism which, ultimately, depend on increasing the LOS of tourists (Alegre & Pou, 2006;Barros et al, 2010).…”