Domestic tourism destination choices — a choice modelling analysis

Abstract

Tourism destinations compete with each other to attract visitors. Although international tourism has received a lot of attention, domestic tourism remains the mainstay for many destinations. To inform the basis on which destinations compete, an understanding of the determinants of destination choices is required. In this paper, the discrete choice modelling method is applied to investigate the determining factors underlying the short-break holiday destination choices of prospective tourists from Melbourne, Australia. The results from an estimated nested logit model indicate the relative importance of a number of destination and trip attributes and respondent characteristics. The model results are used to simulate the effects on destinations' market shares resulting from various changes in attributes and tourist characteristics.

Factors Influencing Local Tourists’ Decision-making on Choosing a Destination: a Case of Azerbaijan

“…Despite international tourism being highlighted mostly and the development and research of domestic tourism rather neglected, the value of domestic tourism expendi-ture is significantly larger than that of inbound tourism (Huybers, 2003;Tourism as…, 2010;Pierret, 2011). The institutions and companies responsible for the development and promotion of domestic destination need to determine the factors influencing tourists' destination choices.…”

Uncovering the Macrostructure of Tourists' Preferences: A Choice Experiment Analysis of Tourism Demand to Sardinia

“…Morley, 1994). A slightly different approach, in line with a long tradition in transportation studies, has been that of applying discrete choice modelling to destination choice, both for international tourist demand (Huybers, 2003a;Huybers and Bennett, 2000), and for modelling factors that determine inbound tourism flows for short trips (Huybers, 2003b).…”

Short-term responses of Dutch vacationers to a sharp increase in transport costs

“…There is ample evidence in existing literature showing that sociodemographic characteristics such as gender, age, income, household type and composition and level of education can help explain vacation decisions (e.g. Huybers, 2003;Nicolau and Más, 2006). Therefore, these variables might also help to explain vacationers' responses to a sharp increase in transport costs.…”