Agent-based simulations of China inbound tourism network

Jinfeng Wu, Xingang Wang, Bing Pan

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Based on the results of a large-scale survey, we construct an agent-based network model for the China independent inbound tourism system and, by the approach of numerical simulation, investigate the responses of the tourist behaviors to perturbations in different scenarios, including the closure of a tourism city, the opening of a new port city in western China, and the increase of the tourism attractiveness of a specific city. Numerical results show that: (1) the closure of a single city in general will affect the tourist visitations of many other cities and, comparing to the non-port cities, the overall visitation volume of the system is more influenced by closing a port city; (2) the opening of a new port city in western China will attract more tourists to the western cities, but has a negligible impact on either the overall visitation volume or the imbalanced tourist distribution; and (3) the increase of the tourism attractiveness of a non-port (port) city normally increases (decreases) the overall visitation volume, yet there are exceptions due to the spillover effect. Furthermore, by increasing the tourism attractiveness of a few cities simultaneously, we investigate also the strategy of multiple-city-upgrade in tourism development. We find that the overall tourist volume is better improved by upgrading important non-port cities that are geographically distant from each other. The study reveals the rich dynamic inherent in complex tourism network, and the findings could be helpful to the development and management of China inbound tourism.

Original languageEnglish (US)
Article number12325
JournalScientific reports
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2019

All Science Journal Classification (ASJC) codes

  • General

Fingerprint

Dive into the research topics of 'Agent-based simulations of China inbound tourism network'. Together they form a unique fingerprint.

Cite this