Examining Attributes Associated with Tourist Arrivals to Forest Parks through Linear and Curve Estimations

Abstract

This research constructs the critical predictors of visitation that shall allow the practitioners to foresee the visitation in the years to come through secondary data. For this study, tourist arrival data associated with the most popular forest park (i.e., Xiton Forest Park) in Taiwan along with relevant socio-economic data are utilized. This research adopts a group of analytical procedures involving correlation analysis, regression, and curve estimation analyses. The results show that the number of holiday per month and the average monthly rainfall have positive and negative correlations, respectively, with the visitation. Meanwhile, average monthly temperature and monthly gross domestic product per capita show a positive correlation in all three analytical methods and therefore are regarded as the primary predictors of tourist arrival. Consequently, this study provides managerial implications to increase the tourist arrivals to the forest park.

Citation

Liu, W.-Y. (2018), "Examining Attributes Associated with Tourist Arrivals to Forest Parks through Linear and Curve Estimations", Advances in Hospitality and Leisure (Advances in Hospitality and Leisure, Vol. 14), Emerald Publishing Limited, Leeds, pp. 93-109. https://doi.org/10.1108/S1745-354220180000014006