Tourism in Latin America A Choice Analysis

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Abstract

The main aim of this paper is to estimate a mixed logit model in order to analyze the decision of Portuguese tourists traveling to Latin America in charter flights. The model estimates the probability of choosing this type of destination, by means of explanatory variables, disentangling homogeneous and heterogeneous variables. The conclusion is that strategies by clusters are needed in order to account for the heterogeneity identified. Moreover, the combination of all former variables, which contribute substantially to a better understanding of tourism choice behavior, with the latter variables is needed to define a comprehensive strategy.

Résumé

Tourisme en Amérique latine : une analyse de choix. Le but principal de ce travail est d’estimer un modèle logit multinomial afin d’analyser la décision des touristes portugais qui voyagent vers l’Amérique latine en vol charter. Le modèle estime la probabilité de choisir ce genre de destination par moyen de variables explicatives en dénouant les variables homogènes et hétérogènes. On conclut que, pour rendre compte de l’hétérogénéité identifiée, il faut des stratégies de groupement. En outre, il faut combiner toutes les variables homogènes, qui contribuent considérablement à une meilleure compréhension du comportement des choix de tourisme, et les variables hétérogènes afin de définir une stratégie compréhensive.

Introduction

This paper analyzes the probability that a Portuguese tourist traveling on Air Luxor will choose Latin America as a vacation destination. This is a privately-owned Portuguese airline which, besides scheduled flights in Europe, to the tropical Atlantic island of São Tome, and to Guinea-Bissau in West Africa, also has a separate charter operation. These flights operate on routes between Portugal and various Latin American destinations, particularly in Brazil and Mexico, and to certain African markets. For the purpose of this study, a detailed survey was conducted in 2004 on board Air Luxor charter flights, with a sample of 1,097 individuals. Given human complexity and diversity, it was anticipated that research into what led tourists to choose a certain destination would generate different perceptions meriting further analysis in order to develop more effective marketing strategies.

Previous findings suggest that a destination’s image is what drives the behavioral intentions (Gnoth 1997). Moreover, perceptions of the destination are a function of internal and external motivations that are determined by a set of psychological and socioeconomic variables and expectations (Baloglu and McCleary 1999). This paper estimates an econometric model testing the multi-attribute models of Fishbein and Ajzen (1980) and the destination choice model of Mathieson and Wall (1984), together with the evidence from the literature review. According to Sirakaya and Woodside (2005), the development of tourist-decision models that incorporate a wide array of variables and fill the gap between behavioral and choice-set approaches by means of probability theory are required in order to obtain deeper insights into the decision process.

This paper contributes to the literature in the two ways highlighted by Sirakaya and Woodside (2005). First, it demonstrates the usefulness in tourism research of the logit regression technique, more precisely, the mixed logit regression, to define clusters statistically significant in a sample, overcoming the limitations of traditional cluster analysis. Second, it offers an integrated approach to understanding how the different attributes related to tourist profiles, touristic awareness, destination characteristics, and holiday features affect the probability of choice. Third, this paper uses a mixed logit to determine the probability that Portuguese tourists will choose Latin America rather than Africa for their vacation. This is similar to Nicolau and Más, 2005, Nicolau and Más, 2006, who analyzed the determinants of the tourism decisions made by Spanish families, and Kemperman, Ponjé and Timmermans (2005), who analyzed preferences for urban parks.

The mixed logit is considered to be the most promising state-of-the-art discrete choice model currently available to analyze questionnaire data (Hensher and Greene 2003). Its advantage over alternative others derives from two improvements. First, it allows for the error term to combine different statistical distributions, which is an improvement on alternative specifications that rely on one specific distribution. Second, it allows for random preference parameters (parameters that describe characteristics not linked to observed characteristics), whereas the traditional logit permits preference variations related to observed characteristics. This procedure may be more effective in achieving results than the traditional procedure, which considers all the individuals as homogeneous. Therefore, the aim of the paper is to estimate a mixed logit model disentangling heterogeneous and homogeneous explanatory variables to identify those variables which can be managed in a homogeneous way and those that must be managed by clusters.

Section snippets

Tourism Choice AnalysIs

Discrete choice models in tourism are based on multivariate attributes of decision (Lancaster 1966), with the data obtained by means of questionnaires, and involve the use of either binomial or multinomial logit models. The nested logit (McFadden, 1974, McFadden, 1981) has proven very successful in identifying the determinants of choice in tourism models (Domencich and McFadden, 1975, McFadden, 1981). Examples of studies that use the binomial logit include those carried out by Fleischer and

Conclusion

In this paper, a mixed logit model was used to gain a deeper insight into what leads Portuguese tourists to exotic destinations in Latin America, validating Fishbein and Ajzen’s (1980) reasoned action theory and Mathieson and Wall’s (1984) tourist decisionmaking theory. The variables that affect the probability that Portuguese individuals will choose to vacation in Latin America are destination attributes, travel arrangements, and tourist socioeconomic profiles, validating previous research (

Acknowledgements

The authors acknowledge grant support from Air Luxor, SA for this study.

Antónia Correia is Assistant Professor of tourism economics at the University of the Algarve (Campus de Gambelas, 8005-139 Faro, Portugal. Email <[email protected]>).

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    Antónia Correia is Assistant Professor of tourism economics at the University of the Algarve (Campus de Gambelas, 8005-139 Faro, Portugal. Email <[email protected]>).

    Carlos Santos is Professor of tourism economics and Carlos Pestana Barros is Assistant Professor of microeconomics. Their research interests, respectively, are on consumer behavior; island tourism; and hotel and travel agency productivity.

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