Search results

This 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.

The 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.

The 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).

The 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.

Many 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.

It is generally understood that during periods of economic hardship, some persons turn to crime to compensate for income deficiencies. The paper investigates the impact of economic misery on crime. The purpose of this paper is to provide insight into the relationship between economic conditions and economic misery.

An index of misery is employed that takes into account not only the rate of unemployment, but also the rate of inflation. The non-linearity of the relationship between economic misery and crime is modelled using Markov-switching (MS) models and the synchronization of their cycles is measured via the concordance index.

The paper looked at the relationship between economic misery and five types of crime: property crime, theft from motor, theft of motor, fraud and robbery. No evidence of a contemporaneous relationship between economic misery and crime was uncovered. Property and theft of motor crime respond to the state of misery with a lag of one period, supporting the criminal motivation effect. Economic misery is in the same regime as property crime 50 per cent of the time and with theft from motor crime almost 60 per cent of the time.

Most of the theoretical and empirical work is based on larger economies. The paper provides some insight into the relationship between economic conditions and economic misery in developing microstates, a niche which has been largely ignored in the literature. The use of MS models in the paper deviates from the tradition of examining linear relationships on the basis that the variables under investigation are inherently cyclical and linear analysis is likely to provide a weak fit under these circumstances.