Segmenting tourists by length of stay using regression tree models

Abstract

PurposeThis study analyses how the socio-demographic profile of the tourist, trip-related characteristics, distance, and economic conditions in the source country affect pleasure tourists' length of stay behaviours in Barbados.Design/methodology/approachThe study uses “biggish” data (over 3.6 million observations), parametric models (OLS) and statistical learning models (regression trees) to develop a length of stay decision rule to segment pleasure tourists' length of stay. Our sample period is January 2004 to March 2013.FindingsThe analysis revealed a great deal of heterogeneity in the impact of the predictors across segments, which would be typically hidden from simple parametric approaches often used to model length of stay (such as OLS).Practical implicationsThe main implication is that conventional models of length of stay should be complemented with segmentation analyses to shed some light on the heterogeneous length of stay behaviours of specific market segments.Originality/valueMany studies on small tourism-specialising states focus on modelling aggregate arrivals. By modelling micro-data for Barbados, we provide insights on this aspect of tourism demand for small states. Second, very few studies use classification tools to analyse length of stay. The study contributes to the literature through its methodological approach.

Regression trees for hospitality data analysis

“…RTs have been generally absent from the hospitality literature (Cankurt, 2016; Jackman and Naitram, 2021; Wilkins et al , 2018) in spite of gaining ground in other fields. The purpose of this paper was to describe the method and discuss its power and usefulness in analyzing hospitality data.…”

Can five sun-and-sand Sardinian destinations host longer visits?

“…In turn, this facilitates tourism operators to understand the needs of different tourist categories better and allows them to tailor specific products and services (Jeong et al, 2018). Quite surprisingly, while there is a large body of literature analysing segmentation based on satisfaction, spending, motivation, and the like, empirical studies that investigate segmentation for the LoS still need to be developed (Jackman & Naitram, 2023) 3 .…”

“…While some studies focus on a specific market segment (i.e., tourist categories), such as senior tourists (Alen et al, 2014;Campolo et al, 2022), the literature lacks studies on LoS that compare the different categories of tourists to grasp information on their needs and tailor specific products and services (Jeong et al, 2018). This evidence is quite surprising since the body of literature analysing segmentation based on satisfaction, spending, motivation, and the like is large (Jackman &Naitram, 2023). Market segmentation can be based on socio-demographic, behavioural, and psychographic variables.…”

Indian diaspora in Ghana: cultural and family heritage of tourists' travel preference

“…Preference has been characterized as the underlining intrinsic, psychological or mental urge that motivates a person to engage in recreational activities (Allaberganov and Preko, 2021; Pearce and Lee, 2005). The significance of preference within tourism research is inherent in recognizing tourists’ requirements and appropriately connect those demands to the right activities, hobbies or destination qualities (Albayrak and Caber, 2018; Jackman and Naitram, 2021). This study conceptualized the constructs with factors such as family heritage and cultural heritage as an antecedent that influences tourists toward preference to travel.…”