Predictive Modeling of Transportation Systems in Jiuzhai Valley World Heritage Site, China

Xiaoqing Xu, Rui Yang, Youbo Zhuang, Peter Newman and Derrick Taff

SAGE Open, 2020, vol. 10, issue 2, 2158244020924375

Abstract: Tourist congestion is a significant issue in Jiuzhai Valley World Heritage Site (JVWH). The “demand-driven†approach of alternative transportation system (ATS) has led to the issues related to visitor crowding, visitor safety, and visitor experience quality. JVWH requires a more efficient approach to achieve a suitable tourist distribution while preserving the quality of visitors’ experiences. Accordingly, this study examines descriptive data, which are collected in 2015 regarding visitor use of the ATS in JVWH to spatially model current and future distribution scenarios. Researchers developed four theoretical scenarios by using the computational model which imitate the current ATS system. Imitation results indicate Scenarios 3 and 4, which adjust spot combination and tourist duration are the two most effective methods for balancing tourist distribution, and are, therefore, the most effectively ways to optimize the current ATS system. This research provides a glimpse into potential management strategies for the tourist distribution of JVWH and possibly other parks in China.

Keywords: world heritage site; tourism management; alternative transportation system; predictive modeling; tourist congestion; tourist experience (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/2158244020924375 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:10:y:2020:i:2:p:2158244020924375

DOI: 10.1177/2158244020924375

Access Statistics for this article

More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().