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...

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Main Authors: Jie Yin, Yahua Bi, Xiang-Min Zheng, Ruey-Chyn Tsaur
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8805389/
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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
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