Network behavior as driving forces for tourism flows

Hong, Tao; Tao, Ma; Huan, Tzung‐Cheng

doi:10.1016/j.jbusres.2014.04.006

Cited by 42 publications

(31 citation statements)

References 23 publications

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“…Yang and Wong 2012). In terms of destination attractiveness measures, we considered the three most distinguished tourist attraction types in China: AAAAA scenic spots, which are designated by the country’s National Tourism Administration as the highest level of scenic spots in the country (Hong, Ma, and Huan 2015), national parks (Y. Yang and Wong 2012), and world heritage sites (Patuelli, Mussoni, and Candela 2013; C.-H. Yang, Lin, and Han 2010).…”

Section: Methodsmentioning

confidence: 99%

Public Transport Connectivity and Intercity Tourist Flows

Yang

Dong

2017

Journal of Travel Research

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In this study, we investigate how dyadic air and rail transport connectivity affects domestic tourist flows among 343 Chinese cities. Using geo-tagged Sina Weibo data to track tourists during China’s National Day Golden Week in 2014, we estimate several gravity models with a negative binomial distribution. The estimation results suggest that air transport connectivity generally has a greater influence than rail transport on dyadic tourist flows, while connectivity provided by ordinary trains (compared to other rail types) is most important in the context of rail transport. Also, we find the effects of transport connectivity and intermodal transport competition to depend on the origin-to-destination distance. Different types of railway trains appear to have distinct effective distance ranges: the effect of high-speed rail trains is strongest at travel distances between 1,800 and 2,000 km, whereas bullet trains’ effect is strongest at distances between 400 and 600 km.

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Section: Methodsmentioning

confidence: 99%

Public Transport Connectivity and Intercity Tourist Flows

Yang

Dong

2017

Journal of Travel Research

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“…In these cases the correlation between the tourist flows and the network connections between the destinations is highlighted. The study of networks assumes that individuals or organizations do not act in isolation and that the pattern of relationships developed with other actors is strongly influenced by their behavior [33]. In the network, the tourists/actors of the destination are connected to the places visited/attractions, which they choose based on their behaviour and their free choice.…”

Section: Network Analysis and Mca In The Tourismmentioning

confidence: 99%

Using the Network and MCA on Tourist Attractions. The Case of Aeolian Islands, Italy

et al. 2018

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This study highlights the preferences and motivations of tourists for the choice of destinations to visit. Natural, cultural, gastronomic attractions, places of consumption, and identity/immaterial motivations are examined through social network analysis and validated through the multiple correspondence analysis (MCA). The study explores the relational variables that can explain the attractiveness of the places and the propensity to visit them. To identify the visitor profiles and the reasons behind their choices, a sample survey was carried out in Lipari, in the Aeolian Islands, interviewing tourists, residents, and people present on the island for work reasons. From the results obtained, profiles emerged with very different characteristics. They vary among those who are attentive to the identity and sustainability of the territory and appreciate the beauty of the sea to others who are attracted mainly for places of consumption and gastronomy, and finally, to people who are indifferent to the attractiveness of the place. This study contributes to the knowledge of the tourist understanding of fragile places with a strong tourist attraction and provides indications for better use of the resources present, oriented towards eco-sustainable hospitality systems and the environment. The study discusses the implications of its findings for future research and provides insights for planning tourism services.

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“…Besides, concepts related to agglomeration, clustering, collaboration, and partnership are within the DNA of the tourism and hospitality sector as a single company or destination per se cannot successfully develop and deliver travel packages [9]. Essentially, urban tourism agglomeration improves the urbanization and informatization, enhances the connection between complementary tourism destinations, establishes economies of scale, and reduces internal transaction costs, and thereby promotes the development of resilient and sustainable tourism destinations [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…In general destination research, network analysis provides theoretical and empirical evidence that the structure of networks determines destination development in several facets including promoting education [14], accelerating technological diffusion [15], and facilitating citizens' mobility [16]. Especially, Hong and Ma [10] highlighted that the structure of network influences the intensity of competition among destinations and market equilibrium.…”

Section: Introductionmentioning

confidence: 99%

Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review

Hua

Wondirad

2020

Sustainability

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This study analyzes tourism network in urban agglomerated destinations and puts forth implications for future sustainable development through a critical and extensive review of related literature. First of all, with a bibliometric analysis of 2670 selected articles from three research fields of urban tourism, urban agglomeration tourism and tourism destination network, we analyzed their respective research themes and classified them accordingly. Then, the study further investigates the role of tourism network in urban agglomerated destinations by identifying the differences and connections between urban agglomeration tourism and urban tourism. Finally, a basic architecture is established for the study of tourism networks in urban agglomerated destinations context. Study findings highlight that urban agglomeration tourism emphasizes the interconnectivity and social network relationships. However, research on the destination network of urban agglomerations is limited, especially from the tourism development perspectives. Therefore, the evolution process, structural effects, determinants and dynamic mechanisms of the tourism network in urban agglomerated destination are among the opportunities for future research. Moreover, the research architecture shows that the network relationship emerges as a new direction for the study of urban agglomeration system to better integrate and harness destinations’ resources and thereby promote sustainable development in urban agglomerated areas.

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Network behavior as driving forces for tourism flows

Cited by 42 publications

References 23 publications

Public Transport Connectivity and Intercity Tourist Flows

Public Transport Connectivity and Intercity Tourist Flows

Using the Network and MCA on Tourist Attractions. The Case of Aeolian Islands, Italy

Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review

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