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机构地区:[1]山东大学管理学院,济南250100 [2]中山大学旅游学院,广州510275
出 处:《资源科学》2015年第11期2140-2150,共11页Resources Science
基 金:国家自然科学基金项目(41301142)
摘 要:本文基于旅游者时空行为视角,以香港海洋公园为案例对大陆游客在境外旅游景区内部的旅游行为进行研究,以参与活动、停留时间和到访景点等为聚类要素进行聚类分析,结构化描述大陆游客在香港景区内的旅游时空行为模式,为更加全面和准确地认识大陆赴港游客在景区内的旅游时空行为,提升大陆游客出境旅游体验质量和优化景区产品管理提供研究基础。香港海洋公园大陆游客的样本性别结构、年龄结构、学历结构和收入结构基本符合正态分布的规律,地域结构基本符合距离衰减规律,在对有效样本进行聚类分析后得出8类模式,分别为全天覆盖型、半日覆盖型、下午覆盖型、全天山上型、半日山上型、中午场馆型、下午场馆型和短时折返型。本文通过研究旅游者外显时空行为模式的识别和结构化分析,在精确刻画的基础上帮助研究者更加深刻地理解旅游者行为方式,最终为优化旅游者行为、提高旅游者体验质量、提升旅游目的地和旅游景区管理水平提供理论支持。Based on tourist temporal-spatial behavior perspectives we examined Ocean Park Hong Kong as a case study to look at the tourism activities and dwell times of Chinese mainland tourists using frequency analysis and cluster analysis. Our aims were to describe a temporal-spatial behavior model in Hong Kong tourism attraction, improve tourism experience quality, and make tourism development sustainable. We examined the sex ratio, age, education background, monthly income and the native place of mainland tourists in Hong Kong Ocean Park. According to K-means Cluster analysis, eight mainland tourists' temporal-spatial behavior patterns were identified: day-covered pattem, half day-covered pattern, aftemoon-covered pattem, all day-summit pattem, noon-museum pattern, half day-summit pattern, aftemoon-museum pattern and short term-return pattern. Compared to previous research focusing on outbound tourism market sizes and demands, we paid attention to individual temporal-spatial behaviors of Chinese mainland tourists using GPS equipment during the tour specifically. By recognizing and analyzing structurally Chinese mainland tourist temporal-spatial behavior patterns, a better understanding of tourist behavioral patterns emerged. The results show that Chinese mainland tourists behave in different ways and some tourists even get behavior deformation due to information asymmetry and time-budget constraints. These factors do not support tourist behavior optimization, tourist experience quality upgrades and the management level of attractions and destinations.
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