“…The traditional techniques for tracking tourist flows mainly depend on observations, interviews or questionnaires ( Zeng, 2018 ). Researchers are asked to track the tourists' movements to develop a map of tourists' distribution within a given destination ( Dumont, Roovers, & Gulinck, 2005 ). In addition, tourists are required to retrace their movements through self-administered questionnaires ( Xia et al, 2009 ).…”
Tourist arrivals and tourism revenues have been extensively studied to evaluate international tourist flows, whereas the structure and evolution of these flows have received less attention. Based on international tourist arrival data from 221 countries/regions during the period 1995–2018, this study applies network analysis to explore the structure and evolution of international tourist flows, and the roles and functions of countries/regions in the international tourist flow network. The results of this study reveal that the network density of international tourist flows is increasing. Countries/regions in Europe, East Asia and North America generally occupy a significantly important position within the international tourist flow network, especially Germany and China. Those geographically close countries/regions demonstrate the same or similar roles and positions in international tourism. This study has significant implications for tourist destination management and marketing.
“…The traditional techniques for tracking tourist flows mainly depend on observations, interviews or questionnaires ( Zeng, 2018 ). Researchers are asked to track the tourists' movements to develop a map of tourists' distribution within a given destination ( Dumont, Roovers, & Gulinck, 2005 ). In addition, tourists are required to retrace their movements through self-administered questionnaires ( Xia et al, 2009 ).…”
Tourist arrivals and tourism revenues have been extensively studied to evaluate international tourist flows, whereas the structure and evolution of these flows have received less attention. Based on international tourist arrival data from 221 countries/regions during the period 1995–2018, this study applies network analysis to explore the structure and evolution of international tourist flows, and the roles and functions of countries/regions in the international tourist flow network. The results of this study reveal that the network density of international tourist flows is increasing. Countries/regions in Europe, East Asia and North America generally occupy a significantly important position within the international tourist flow network, especially Germany and China. Those geographically close countries/regions demonstrate the same or similar roles and positions in international tourism. This study has significant implications for tourist destination management and marketing.
“…This article proposes an alternative method of estimating spatial patterns in tourist use: park accessibility measurement with a geographical information system (GIS). It focuses on off-road use, which is the most difficult to estimate and most likely to have detrimental biophysical effects on natural resources (Marion and Leung 2004;Dumont et al 2005;Leung et al 2011;Wimpey and Marion 2011).…”
Section: Systems Knowledgementioning
confidence: 99%
“…Another concern is the possibility that, when official tracks are closed, visitors may create informal tracks in remote, roadless areas (Marion and Leung 2004;Dumont et al 2005). Therefore, it is necessary to balance tourists' needs with the protection of resources in any track closure decision.…”
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“…A variety of techniques have been applied in the observation of tourist movements by different scholars. The traditional tracking techniques are based on observations and interviews that require the researcher to follow an individual tourist and record his or her movements (Dumont et al , ). Participants are also asked to trace or retrace their spatial movements on a cartographic map using self‐administered questionnaires (Fennell, ; Wang and Manning, ).…”
The 2008 Beijing Olympic Games had a great impact on the tourism industry in Beijing, especially on tourism flows and movements. This study used content analysis and social network analysis methods to examine 500 online trip diaries and analyze overseas tourist movement patterns in Beijing during the Olympics. The result revealed that overseas tourists were most interested in famous traditional attractions, and their movements were focused in the central city area of Beijing. The study identified the diversity of tourist attractions and the expansion of main visiting areas as the two main changes during the Olympics.
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