Issues in modeling repeat leisure consumption: Markov modeling examples [Problèmes associés à la modélisation de la consommation régulière de loisirs : Exemples de la modélisation par chaînes de Markov] [Problemas asociados a la modelización del consumo regular de actividades de ocio: Ejemplos de la modelización por las cadenas de Márkov]

Abstract

Models should be used to facilitate understanding structure in data. This article is about using models that are adequate approximations to reality if models are used. A theory and research context for Markov modeling is given for repeat holiday travel and the examination of destination loyalty. A simple Markov model based on the literature and an expanded state space Markov model based on repeat travel related concepts in the literature are presented. Analysis of travel to Turkey from the UK and to the USA from Australia, Japan and the UK confirms Oppermann’s (1998a) claim that simple Markov models result in a poor approximation to reality. It is shown that expanded state space models can accommodate realism. Models producing hypothetical behavior or behavior that mirrors reality are discussed both generally and regarding repeat travel, specifically. Application of the ideas and methods presented to leisure research on matters other than travel is discussed. © Presses de l’Université du Québec.