| Summary: | The twentieth century is a golden era for technology and transportation boost, which facilitates taking journey all over the world. Traveling for any purpose such as leisure, meetings, conferences, conventions, business, educational and medical trips is considered to be one the most profitable industries in the world and the cornerstone of many economies. Norway has a great reputation among overseas visitors for being safe and having an abundance of diverse touristic sites. However, like any other country, Norway needs to make appropriate policies to increase its income in the tourism sector. In this regard, research is required to estimate the tourism demand in order to provide the policy makers with solid foundations for their decision-making processes. The aim of this research is to identify the factors, including economic and demographic, which can affect the international tourism demand in Norway. To achieve this aim, the present study uses a probabilistic approach in order to estimate the length of stay of tourists in Northern and Southern Norway. As tourist-attraction differs from North to South, investigating the tourism demand and analyzing how different covariates affect the demand provides a basis for recognizing the area that has a higher investment turnover. The findings of this study show that the tourism demand differs in Southern and Northern Norway and tourists in general have the tendency to stay longer in Northern Norway. The extent of such difference is modeled as a function of time and a set of explanatory variables, for instance tourist gender, age, purpose of trip, total cost, geographical area, preference of accommodation and transportation type. This means that the effects of the covariates on the probabilistic representation (using survival analysis) of tourism demand vary from one region to other. Such findings can be used to make appropriate regional and national policies to have a well-organized plan to promote tourist flow to Norway. Keywords: Tourism industry, Northern and Southern Norway, Survival analysis, Probabilistic approach, Policy-making.
|
|---|