Modeling the Potential for Rural Tourism Development via GWR and MGWR in the Context of the Analysis of the Rural Lodging Supply in Extremadura, Spain

Abstract

The harmonious development of tourism activity in rural areas must be based on effective tourism plans adapted to the territory. To achieve this, it is necessary that the tourist potential of the area be taken into consideration. However, the tourist attraction capacity is not always considered, which has led to a significant increase in the number of rural lodgings. This has caused strong imbalances in Extremadura, Spain. On the basis of this premise, in this research study, we aim to determine whether there is an adjustment between the main factors that attract rural tourists to the study area. To determine this, we make use of different geostatistical procedures based on spatially weighted regression models (GWR and MGWR). A comparative study is conducted using these models, on the basis of which it is deduced that one type of regression offers advantages over the other. However, the results show that neither regression models can explain the presence of rural accommodation in places that do not meet the requirements demanded by tourists. This fact shows that the increase in the supply of rural accommodation follows unsuitable patterns in some cases, which translates into numerous problems, such as low occupancy levels. In this study, it is concluded that there is no strong relationship between the attractiveness of a territory and its volume of supply, highlighting the need to rethink tourism plans in order to adjust them relative to reality.

Application of Geographic Information System to Sensing Strength and Potentiality of Ecological Industrialization in China’s Huai River Ecological Economic Belt

“…We constructed a local development model to analyze the factors and their roles in unified development between ecological industrialization strength and potentiality from a local perspective based on a geographically weighted regression model. (33)(34)(35)(36)(37) The constructed model is…”