Díaz-Pérez Flora Ma, García-González Carlos G, Fyall Alan
Facultad de Economía, Empresa y Turismo, Universidad de La Laguna, 38071, La Laguna-Tenerife, Spain.
Rosen College of Hospitality Management, University of Central Florida, 9907 Universal Boulevard, Orlando, FL 32819, USA.
Heliyon. 2020 Jul 8;6(7):e04256. doi: 10.1016/j.heliyon.2020.e04256. eCollection 2020 Jul.
This paper considers the most suitable market segment(s) from an environmental and local economic development perspective in the specific context of visits to natural environments. More specifically, the paper explores the distinctions and differences between tourists (non-residents) and residents with regard to visit behavior at natural attractions. By using the CHAID algorithm, a decision tree is constructed for means of transportation which serves as a key factor in the segmentation process. However, such a tree for visitors' resident or non-resident status cannot be built as a first explicative variable, unless it is statistically forced. Once it is forced, the tree opens in several sub-segments, for non-residents and residents alike. Finally, it allows understanding of the means of transportation used by visitors according to their geographical origin as well as a set of added independent variables: accommodation establishment, length of stay, season, and other demographic variables (educational level, gender, and age). Also, more importantly, we have obtained segments with no overlap configured according to all the aforementioned variables. This is a very strong result from a methodological point of view and for policy makers in destination settings.
本文从环境和地方经济发展的角度，在自然环境游览的特定背景下，探讨了最合适的市场细分领域。更具体地说，本文探讨了游客（非居民）和居民在自然景点游览行为方面的异同。通过使用CHAID算法，构建了一个关于交通方式的决策树，这是细分过程中的一个关键因素。然而，除非进行统计强制，否则无法将游客的居民或非居民身份作为第一个解释变量构建这样的树。一旦进行了强制，该树会分为几个子细分领域，包括非居民和居民。最后，它能够根据游客的地理来源以及一组附加的独立变量（住宿设施、停留时间、季节和其他人口统计变量（教育水平、性别和年龄））来了解游客使用的交通方式。此外，更重要的是，我们根据上述所有变量获得了无重叠的细分领域。从方法论的角度以及对目的地设置中的政策制定者而言，这都是一个非常有力的结果。
