ABSTRACT
In the post-pandemic era, nighttime tourism is vital in promoting the diversified development of tourism, enhancing the vitality of cities, and improving reemployment rates. Using Kunming City, China, as an example, this study used multi-theory and multi-source data to construct an evaluation model of the spatial distribution and suitability of nighttime tourism. The projection pursuit model and spatial analysis method were used to reveal spatial distribution and explore the suitability characteristics and spatial differences of nighttime tourism development. Our results revealed the following: (1) nighttime tourism resources showed a 'large aggregation, small dispersion' spatial distribution pattern, which is characterized by a distribution along the railway line; (2) at present, the spatial distribution of nighttime tourism in Kunming displays a pattern of 'taking a high-density large gathering area as the center and extending around; ' and (3) the most suitable nighttime tourism area accounts for 11.83% of the total land area of Kunming; highly suitable area accounts for 17.53%. The general suitable and unsuitable areas accounted for 43.29% and 27.35%, respectively. The results of this study assist in providing a scientific basis for the strategic planning and development of the nighttime tourism industry in Kunming.
ABSTRACT
As the first of the six elements of tourism, food is an important part of tourism activities. As an important driving force for the economic development of tourist destinations, food tourism plays an increasingly important role in tourism and has gradually become an important hub connecting tourists, local residents, and tourist destinations. This study takes Yunnan wild mushrooms as a case, obtained data through a questionnaire survey and applied a projection pursuit model (PPM) to explore the driving factors affecting food tourism consumption. Research shows that the quality and abundance of gourmet resources are the most important factors affecting tourist consumption of gourmet foods, and the needs and experiences of tourists also promote their consumption, to a certain extent. This provides a guide for Yunnan Province to expand the source market. Second, we compared PPM with structural equation modeling (SEM) and demonstrated that the former requires less data than the latter and is immune to nonlinearities, interaction effects, and the researchers' excessive prior knowledge. This makes PPM more robust, anti-interference, accurate, and objective than SEM when dealing with problems. Finally, we put forward reasonable suggestions from four aspects of government, enterprises, local residents, and tourists, which provide an effective way for Yunnan Province to develop food tourism. In addition, PPM's advantages in data selection, data processing, and result stability fill the gaps in data processing in the tourism field.
