Lin Jinping, Zhang Bowen, Feng Jiajia, Yi Zeyu, Zhang Hao, Luo Man, Zhong Zhujun, Zhao Fei
School of Earth Sciences, Yunnan University, Kunming, 650500, China.
Heliyon. 2023 Mar 18;9(3):e14638. doi: 10.1016/j.heliyon.2023.e14638. eCollection 2023 Mar.
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.
作为旅游业六大要素之首,美食是旅游活动的重要组成部分。美食旅游作为旅游目的地经济发展的重要驱动力,在旅游业中发挥着越来越重要的作用,并逐渐成为连接游客、当地居民和旅游目的地的重要枢纽。本研究以云南野生菌为例,通过问卷调查获取数据,并应用投影寻踪模型(PPM)来探究影响美食旅游消费的驱动因素。研究表明,美食资源的质量和丰富程度是影响游客美食消费的最重要因素,游客的需求和体验在一定程度上也促进了他们的消费。这为云南省拓展客源市场提供了指导。其次,我们将PPM与结构方程模型(SEM)进行了比较,证明前者所需数据比后者少,并且不受非线性、交互效应和研究人员过多先验知识的影响。这使得PPM在处理问题时比SEM更稳健、抗干扰、准确和客观。最后,我们从政府、企业、当地居民和游客四个方面提出了合理建议,为云南省发展美食旅游提供了有效途径。此外,PPM在数据选择、数据处理和结果稳定性方面的优势填补了旅游领域数据处理的空白。