Tourist attractions in efficiency analysis

Dong, Hai; Liang, Qi-Bin; Peypoch, Nicolás

doi:10.1177/13548166211060190

Cited by 2 publications

(1 citation statement)

References 22 publications

(25 reference statements)

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“…Among the different types of attractions, urban parks, religious and cultural sites, geological relics, and red tourism exhibit better scale efficiency. 26 Since different types of tourist attractions offer different experiences to tourists, consumers’ price perception may also be affected by different types of attractions. 9 It has been observed that the situation plays a significant role in shaping consumers’ perception of prices.…”

Section: Literature Reviewmentioning

confidence: 99%

The Influence of Tourist Attraction Type on Product Price Perception and Neural Mechanism in Tourism Consumption: An ERP Study

Wei,

Lv,

et al. 2023

PRBM

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Background: Tourism consumption is a topic with heated debates in tourism research, and pricing tourism products is a crucial task for tourism managers. Different types of tourist attractions offer different experiences to tourists, which affect their price perceptions and purchase decisions. Methods: This study combined questionnaires and event-related potentials (ERPs) measures to explore the magnitude of psychological conflict and the degree of emotional arousal that consumers experience when faced with different prices of goods in different scenic types. Results:The questionnaire results showed that attraction type influenced consumers' price perceptions and that consumers were willing to pay higher prices for products in attractions. The ERP results implied that in the early stage of cognition, attraction type did not affect consumers' perceptual processing, while price information attracted consumers' cognitive attention. In the late stage of cognition, attraction type, and price information jointly influenced consumers' decision-making, and consumers tended to accept high prices of products in entertainment attractions and cultural attractions, but consumers were more sensitive to the price of products in cultural attractions and less tolerant to price increases. Conclusion:The study elucidated how price information influenced consumers' purchase decisions of tourism products at different stages of the dual-process theory, which can assist tourism managers in devising different pricing strategies and positioning strategies based on the attributes of attractions, to enhance product sales and revenues. This would further the vision of the World Tourism Organization (UNWTO) of "tourism fostering economic development".

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Section: Literature Reviewmentioning

confidence: 99%

The Influence of Tourist Attraction Type on Product Price Perception and Neural Mechanism in Tourism Consumption: An ERP Study

Wei,

Lv,

et al. 2023

PRBM

View full text Add to dashboard Cite

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Research on passenger flow prediction of tourist attractions by integrating differential evolution and GWO optimization

Zhang,

2024

Applied Mathematics and Nonlinear Sciences

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With the rapid development of tourism, the rapid growth in the number of tourists caused by the imbalance of the passenger flow carrying capacity of tourist attractions, tourist crowding, overloading, and other problems caused by the frequent occurrence of safety accidents, to the tourist attractions has caused a huge negative impact. For this reason, this paper constructs a model for predicting passenger flows at tourist attractions based on the GWO algorithm. Optimizing the model involves using a differential evolutionary algorithm following a feature study with the Gray Wolf Optimization (GWO) algorithm. Then, for the problems that are prone to occur in the fusion of the GWO algorithm and DE algorithm for solving nonlinear systems of equations, a combined GWO-DE-SVM model is proposed to realize the accurate prediction of tourist attractions’ passenger flow. On this basis, the prediction effect of the GWO-DE-SVM combination model is examined. The loss values of the model in the training set and test set of this paper are around 0.034 and 0.029, respectively, with the lowest average error of 2.524% among all the models. The passenger flow and the total tourism revenue of W tourist attraction in the coming year are successfully predicted in the practical application, which is estimated to be 681 million and 106.88 million yuan, respectively. Million and 106.88 million yuan are the respective amounts. And two peaks of tourist attractions in W were predicted in May and October. This study provides a scientific basis for the management of scenic spots to prevent tourist crowding.

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Tourist attractions in efficiency analysis

Cited by 2 publications

References 22 publications

The Influence of Tourist Attraction Type on Product Price Perception and Neural Mechanism in Tourism Consumption: An ERP Study

The Influence of Tourist Attraction Type on Product Price Perception and Neural Mechanism in Tourism Consumption: An ERP Study

Research on passenger flow prediction of tourist attractions by integrating differential evolution and GWO optimization

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