Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China
With tourism development in China, the influx of tourists in popular tourist attractions has become more frequent. However, space cannot accommodate such a large influx of tourists. Through empirical testing, this research identified 23 variables that influence the safety of tourists in crowded spac...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8805389/ |
id |
doaj-c2c01d1e95204a048e444612e57188fa |
---|---|
record_format |
Article |
spelling |
doaj-c2c01d1e95204a048e444612e57188fa2021-03-30T00:03:44ZengIEEEIEEE Access2169-35362019-01-01711902611904010.1109/ACCESS.2019.29362458805389Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in ChinaJie Yin0https://orcid.org/0000-0002-2266-8672Yahua Bi1Xiang-Min Zheng2Ruey-Chyn Tsaur3College of Tourism, Huaqiao University, Quanzhou, ChinaDepartment of Tourism and Convention, Pusan National University, Busan, South KoreaCollege of Tourism, Huaqiao University, Quanzhou, ChinaDepartment of Management Sciences, Tamkang University, New Taipei City, TaiwanWith tourism development in China, the influx of tourists in popular tourist attractions has become more frequent. However, space cannot accommodate such a large influx of tourists. Through empirical testing, this research identified 23 variables that influence the safety of tourists in crowded spaces. We divided 23 variables into three factors: pressure factors, state factors, and crowd management actions. Based on the data collected, this study proposes a system model that includes a feedback mechanism to evaluate the safety of highly aggregated tourist crowds (HATCs) and identify moments requiring security warnings. System simulation results showed that the safety level of HATCs presented a complex process of change in different situations. Thus, management can take corrective actions. We tested this model by simulating different crowding conditions and assessing the safety level of tourists. Different warning plans were proposed based on the simulated security level.https://ieeexplore.ieee.org/document/8805389/Highly aggregated tourist crowdssafety evaluatedstatus simulationearly warningsystem dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jie Yin Yahua Bi Xiang-Min Zheng Ruey-Chyn Tsaur |
spellingShingle |
Jie Yin Yahua Bi Xiang-Min Zheng Ruey-Chyn Tsaur Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China IEEE Access Highly aggregated tourist crowds safety evaluated status simulation early warning system dynamics |
author_facet |
Jie Yin Yahua Bi Xiang-Min Zheng Ruey-Chyn Tsaur |
author_sort |
Jie Yin |
title |
Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China |
title_short |
Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China |
title_full |
Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China |
title_fullStr |
Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China |
title_full_unstemmed |
Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China |
title_sort |
safety forecasting and early warning of highly aggregated tourist crowds in china |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
With tourism development in China, the influx of tourists in popular tourist attractions has become more frequent. However, space cannot accommodate such a large influx of tourists. Through empirical testing, this research identified 23 variables that influence the safety of tourists in crowded spaces. We divided 23 variables into three factors: pressure factors, state factors, and crowd management actions. Based on the data collected, this study proposes a system model that includes a feedback mechanism to evaluate the safety of highly aggregated tourist crowds (HATCs) and identify moments requiring security warnings. System simulation results showed that the safety level of HATCs presented a complex process of change in different situations. Thus, management can take corrective actions. We tested this model by simulating different crowding conditions and assessing the safety level of tourists. Different warning plans were proposed based on the simulated security level. |
topic |
Highly aggregated tourist crowds safety evaluated status simulation early warning system dynamics |
url |
https://ieeexplore.ieee.org/document/8805389/ |
work_keys_str_mv |
AT jieyin safetyforecastingandearlywarningofhighlyaggregatedtouristcrowdsinchina AT yahuabi safetyforecastingandearlywarningofhighlyaggregatedtouristcrowdsinchina AT xiangminzheng safetyforecastingandearlywarningofhighlyaggregatedtouristcrowdsinchina AT rueychyntsaur safetyforecastingandearlywarningofhighlyaggregatedtouristcrowdsinchina |
_version_ |
1724188700661776384 |