Ticket prices and revenue levels of tourist attractions in China: Spatial differentiation between prefectural units

Wang, Ting; Pu, Wu; Ge, Quansheng; Ning, Zhizhong

doi:10.1016/j.tourman.2020.104214

Cited by 24 publications

(12 citation statements)

References 20 publications

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“…The survey revealed that some aspects of the park require improvement: price reasonableness, park services, activities and events, and artificial attractions. Average ticket price in a region has been found to be negatively correlated with its GDP ( Wang et al, 2021 ). Tourism development has shifted Zhangjiajie from an underdeveloped county to a tourism-oriented prefecture-level city ( Zuo & Huang, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…With the ticket, tourists can also visit three other scenic districts within the Wulingyuan scenic area, and the ticket is valid for four days. In 2017, the average ticket price of China's National 5A Level Scenic Area was 13.7 USD, and that of natural landscape attractions was 5.7 USD ( Wang et al, 2021 ), both much lower than ZNFP's price. Consequently, it is important to understand whether visitor satisfaction could be negatively affected by the high ticket price.…”

Section: Introductionmentioning

confidence: 92%

“…Tourist satisfaction with the ticket price, which is an important factor that influences travel choice ( Wang, Wu, Ge, & Ning, 2021 ), has not been examined for ZNFP. Zhang et al (2009) found that there were negative comments from visitors about the entrance ticket price and service quality in ZNFP.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Visitor satisfaction and behavioral intentions in nature-based tourism during the COVID-19 pandemic: A case study from Zhangjiajie National Forest Park, China

Cheng

Wang

et al. 2022

International Journal of Geoheritage and Parks

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

See 1 more Smart Citation

Visitor satisfaction and behavioral intentions in nature-based tourism during the COVID-19 pandemic: A case study from Zhangjiajie National Forest Park, China

Cheng

Wang

et al. 2022

International Journal of Geoheritage and Parks

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“…The increase (decrease) of ticket prices may become a key factor for tourists to choose attractions, making the number of tourists at a certain attraction decrease (increase). If this is the case, the regression estimation coefficients obtained by the general linear regression model may be biased [42].…”

Section: Endogeneitymentioning

confidence: 99%

The Impact of the El Niño Southern Oscillation on the Number of Visitors to Natural Attractions: The Moderating Effect of Disposable Personal Income, per Capita GDP and Population

et al. 2021

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Analyzing the impact of El Nilo Southern Oscillation (ENSO) on the number of tourists is essential in realizing the sustainable development of natural scenic spots. From the current research results, research on the effects of ENSO on tourism focuses on the impact of the formation of the natural environment. However, there is a lack of ENSO-related research on the number of people arriving at natural attractions. This paper considers the adjustment effects of personal disposable income, per capita GDP, and population size and constructs a new framework of ENSO’s influence on tourism. This paper builds a system GMM (Gaussian Mixture Model) and analyzes the impact of ENSO on tourist flow by using Google Trend data (big data technology) to obtain annual passenger flow data of 48 natural scenic spots in the United States (mainly national parks and national forests). The empirical results show that the increase in ENSO has led to a significant decrease in visitors to natural attractions in the United States. Moreover, the increase in personal disposable income, per capita GDP, and population size can weaken the relationship between ENSO and the number of tourists. This research expands and enriches the theoretical perspective of ENSO and outdoor tourism.

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“…There have been fruitful research results in the research on tourist attractions at home and abroad. They mainly include the price system of scenic spots (Zhu et al, 2020;Wang et al, 2021), the energy consumption of different types of scenic spots (Hu et al, 2016), the satisfaction of tourists (Ge, 2018;Bai et al, 2019;Liu and Hao, 2020), the spatial behavior of tourists in scenic spots (Wu et al, 2017;Wang et al, 2018), the smart tourism scenic spot system (Zhu and Chen, 2008;Xie et al, 2021), and the spatial structure of scenic spots based on fractal theory (Wu et al, 2013;Li et al, 2018). Domestic scholars' research mainly focuses on the spatial distribution pattern, spatial structure characteristics, and the influencing factors of scenic spots.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the spatial pattern of scenic spots combining optimal scale and deep learning

et al. 2022

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With the development of deep learning and big data technology, artificial neural network methods are used to simulate new areas with high potential to develop tourist attractions. They break through the limitation of the lifespan development of domestic tourist attractions and improve the credibility of results caused by the sample size and scale effect. This study applied the data for 906 scenic spots in Northwest China by a geographic detector model and deep learning technology to explore the dominant factors explaining their spatial distribution under the optimal research spatial scale and to simulate new areas with a high potential for development as tourist attractions. The main conclusions of this study were as follows. 1) The results were more reliable for Northwest China under a research spatial scale of 150 km × 150 km. 2) The leading factors affecting the development of tourist attractions in Northwest China were normalized difference vegetation index (NDVI), distance from the city, population, and transportation accessibility. 3) The results identified areas that are highly suitable for tourist attractions, showed regional maturity in either the natural environment or social development. This study can act as a reference for further exploration and the application of artificial intelligence technology in scenic spots.

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Ticket prices and revenue levels of tourist attractions in China: Spatial differentiation between prefectural units

Cited by 24 publications

References 20 publications

Visitor satisfaction and behavioral intentions in nature-based tourism during the COVID-19 pandemic: A case study from Zhangjiajie National Forest Park, China

Visitor satisfaction and behavioral intentions in nature-based tourism during the COVID-19 pandemic: A case study from Zhangjiajie National Forest Park, China

The Impact of the El Niño Southern Oscillation on the Number of Visitors to Natural Attractions: The Moderating Effect of Disposable Personal Income, per Capita GDP and Population

Simulation of the spatial pattern of scenic spots combining optimal scale and deep learning

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