Abstract
Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a first-tier city in southern China, we conducted a comprehensive study of the attraction features involving different aspects, such as tourist source, duration of stay, check-in activity index, and attraction correlation degree. The results showed that (1) theme parks established in the early 1990s were the most popular tourist attractions in Shenzhen, but a negative trend was detected in the check-in population; (2) compared with check-in times from surrounding activities and the kernel density of tourists, most destinations in Shenzhen showed a lack of attraction, failing to make the most of their geographic accessibility; and (3) the homogeneity and inconvenient traffic conditions of major tourist destinations leading to the construction of a tourism tour chain has become a challenge. The results of this study demonstrate the potential of big-data mining and provide valuable insights into tourism market design and management in mega-cities.
Highlights
Over the past six decades, tourism has experienced continued expansion and diversification and has become one of the largest and fastest growing economic sectors in the world, contributing 10% to worldwide gross domestic product [1]
Attention has been given to the considerable demand for research on smart tourism [3,4], with many smart tourism studies stressing that the real sense of smart tourism is to focus on tourists' needs in order to maximize tourist satisfaction as well as improve the effectiveness of resource management [5,6]
The rapid evolution of information and positioning technologies has made it possible to accurately track the paths tourists are taking and to collect a large amount of geographical information on users’ activities cheaply and. Both public and private entities interested in developing the tourism sector have realized the considerable importance of adequately segmenting the tourist market and efficiently using online techniques for marketing tourism destinations and products [7]
Summary
Over the past six decades, tourism has experienced continued expansion and diversification and has become one of the largest and fastest growing economic sectors in the world, contributing 10% to worldwide gross domestic product [1]. Many mega-cities are tourist destinations, distribution centres, and key tourism sources because of their large population and unique environment as well as important status and function in the national urban system [2] Given this situation, mega-cities must create awareness and brand image for their tourism resources to effectively segment, target, and attract potential customers. The rapid evolution of information and positioning technologies has made it possible to accurately track the paths tourists are taking and to collect a large amount of geographical information on users’ activities cheaply and Both public and private entities interested in developing the tourism sector have realized the considerable importance of adequately segmenting the tourist market and efficiently using online techniques for marketing tourism destinations and products [7]. The application of geographical information can help people make efficient and economic travel decisions [8] and effectively explore attractive features of tourist destinations, providing new ideas and methods for the management and planning of tourist destinations
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