Mean-variance portfolio analysis leads to determine tourist demands mix but it does not provide any information regarding the risk attitude of the decision maker. In this article, we propose to fill this research gap by proposing a methodological approach which combines the portfolio theory with the utility function technique. By doing so, our approach incorporates the risk attitude of the decision maker through different values of risk tolerance. We apply this methodology on destination management framework. An illustration of its strengths is suggested by using the case study of European tourists visiting France between 2008 and 2013. Our article shows that the optimal origins mix depends on the level of risk aversion of the destination manager. Accordingly, the implications of our methodological approach are highlighted.
Number of overnight stays is an important variable in the context of tourism destination competitiveness. Recently, researchers suggested the mean-variance approach as a tool to measure the efficiency of this variable. However, this methodology is inadequate if the variable does not follow a normal distribution or if the decision-makers do not have a quadratic utility function. Thus, higher moments, such as skewness or/and kurtosis should be taking into consideration. The paper introduces the portfolio theory with skewness as an efficiency measure of the number of international overnight stays in France from 2002 to 2012. First, we show that this variable is not normally distributed. Then, we use a non-parametric approach based on the Mean-Variance-Skewness (MVS) introduced by Briec et al. (2007) to measure the performance of four different regional origins of international tourists staying in France. Finally, we demonstrate that the decision-makers should take the high-return/ low-risk option with a high-skewness.
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