Vacation length choice: A dynamic mixed multinomial logit model
Anna B. Grigolon,
Aloys W.J. Borgers,
Astrid D.A.M. Kemperman and
Harry J.P. Timmermans
Tourism Management, 2014, vol. 41, issue C, 158-167
Abstract:
This paper uses panel data to develop and estimate a dynamic model of choice of the length of stay of a vacation, controlling for unobserved heterogeneity and state dependency. Length of stay options vary from short (1–3 nights), medium (4–9 nights) to long vacations (10 nights or more) and the decision not to go on vacation in a particular year. Independent variables include family lifecycle stage, income, month and lags of the dependent variable. Results indicate that long holidays are most strongly affected by trips made previously in the same year than medium and short vacations. In contrast, there is an increased need for a vacation when any medium or long trips were not yet made in the current year. Month-specific variables confirm that respondents have preferences for making leisure trips during the main holidays and warm seasons. The observed differences given the various lifecycle stages reflect imposed constraints given age and/or household composition that are typical of each particular group.
Keywords: Vacation length; Dynamic mixed multinomial logit model; Panel data; State dependency (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0261517713001647
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:touman:v:41:y:2014:i:c:p:158-167
DOI: 10.1016/j.tourman.2013.09.002
Access Statistics for this article
Tourism Management is currently edited by Chris Ryan
More articles in Tourism Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().