Assessing Social Carrying Capacity of Tourism Destinations with Random Utility Models*

Abstract

Some local visitors or tourists avoid visiting resorts because they have experienced or anticipate overcrowding. Hence, policymakers are concerned to monitor congestion levels. The paper proposes the use of the elasticity of the probability of visiting a destination with respect to increases in congestion, from a random utility framework. More precisely, random parameter logit model is estimated. The advantage of this approach is that it captures not only the current level of congestion but other aspects, such as the sensitivity of different destinations towards crowding and different visitors’ concern about congestion and their probabilities of visiting alternative destinations. It is shown that the rate of change of the elasticity increases with the number of visitors, capturing the expected underlying non-linear relationship such that, when the number of visitors is low, the index is also low but increases exponentially with the influx of new visitors.