Tourist Flows and Multi-Destination Trips
A Network Analysis
Bibliographic Data
| ID | 12974607 |
|---|---|
| Authors | Chen Yong (0000-0001-5485-531X, HES-SO University of Applied Sciences and Arts Western Switzerland, corresponding author) |
| Year | 2024 |
| Volume | 21 |
| Issue | 1 |
| Pages | 49-68 |
| Publication date | 2024-02-04 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of China Tourism Research (JOURNAL) |
| Journal identifiers | ISSN: 1938-8160 • E-ISSN: 1938-8179 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/19388160.2024.2309505 |
| OpenAlex | W4391521998 |
| Language | EN |
| References cited | 27 |
Conventional approaches to modeling multi-destination trips are either based on trade-offs between one single destination and multiple destinations or on a sequence of destinations in a linear manner. These approaches are inadequate to capture the manifestation of multi-destination trips as a network at the aggregate level. Hence, built upon network analytical frameworks, this study adopted a directed network to model multi-destination trips. Using a visitor profile survey of Hong Kong, we found that the networks of multi-destination trips for both leisure and business travelers have several interesting properties, such as high densities, high clustering coefficients, and short diameters. High-degree nodes represent either destinations or origins in the leisure network, but they have a dual role as both destinations and origins in the business network. Network sparsity has a significant impact on the topology of the leisure network, but the impact is negligible on the business network
Advertising · Business · Economic geography · Geography · Tourism · Transport engineering · TRIPS architecture · Computer Science · Digital Marketing and Social Media · Diverse Aspects of Tourism Research · Engineering · Wine Industry and Tourism · Marketing
Networks, Crowds, and Markets
Multilayer networks
On random graphs. I.
The structure and dynamics of multilayer networks
Collective dynamics of ‘small-world’ networks
Emergence of Scaling in Random Networks
Representing tourists’ heterogeneous choices of destination and travel party with an integrated latent class and nested logit model
Modeling Sequential Tourist Flows
Conceptualization of multi-destination pleasure trips
Main destination ratios
Social and Economic Networks
Movement Patterns of Tourists within a Destination
A chaos approach to tourism
A Network Analysis of Tourism Research
| Citation velocity | historical |
|---|---|
| Highly cited | No |