Tourists' spatial-temporal behavior patterns in theme parks: A case study of Ocean Park Hong Kong. (March 2020)

• Record Type: Journal Article
• Authors: Huang, Xiaoting; Li, Minxuan; Zhang, Jingru; Zhang, Linlin; Zhang, Haiping; Yan, Shen
• Is Part Of: Journal of destination marketing & management. Volume 15(2020)
• Publication Date: 2020-03
• Subjects: Tourist behavior -- Spatial–temporal patterns -- Time geography -- Time–space path -- Ocean park Hong Kong -- Theme parks -- GIS research; Place marketing -- Periodicals; Tourism -- Management -- Periodicals; Electronic journals; 658.8005
• DOI: 10.1016/j.jdmm.2020.100411
• Languages: English
• ISSNs: 2212-571X

Abstract

Abstract: Time, space, and activities are considered three important domains of the tourist experience. The core time geography concept of the 'space–time path', which highlights activity-based constraints, serves as a powerful visualization and quantification tool revealing tourists' spatial-temporal behavior. Moreover, the proliferation of tourist-tracking technologies has enabled more precise tourist behavioral data than ever before. This paper aims to integrate multiple data sources to analyze tourists' spatial–temporal behavior patterns on a micro scale. A five-day survey was conducted at Ocean Park Hong Kong from July 6 to 10, 2014. Information about tourists' temporal–spatial behavior was gathered using handheld GPS tracking devices, and questionnaires were distributed to assess tourists' socio-psychological characteristics. Given marked differences in demographic and emotional characteristics, three spatial–temporal behavior clusters were identified via density center clustering, consisting of four factors: path length, tour time, coverage area, and oval circumference. This study presents a novel way to develop a better understanding of tourists' spatial-temporal behavior patterns based on GIS visualization and clustering methods from a microscopic perspective, thus contributing to theme park attraction management and tourist experience enhancements. Highlights: Develops a method to analyze tourists' spatial–temporal behavior patterns. Identifies four factors to visualize and cluster tourists' behaviour patterns. Factors comprise path length, tour time, coverage area, and oval circumference. Path length is the most accurate indicator of visitor behavior. Explores the relationship between behavior patterns and travel experience.