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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Fine-grained tourism demand forecasting: A decomposition ensemble deep learning model
Jian-Wu Bi, Tianyu Han, Yanbo Yao
Tourism Economics (2023) Vol. 29, Iss. 7, pp. 1736-1763
Closed Access | Times Cited: 9

Showing 9 citing articles:

Machine learning applied to tourism: A systematic review
José Carlos Sancho Núñez, Juan A. Gómez‐Pulido, Rafael Robina Ramírez
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 7
Forecasting tourism demand with a novel robust decomposition and ensemble framework
Xin Li, Xu Zhang, Chengyuan Zhang, et al.
Expert Systems with Applications (2023) Vol. 236, pp. 121388-121388
Closed Access | Times Cited: 14
Digital financial inclusion and domestic tourism demand: Through the lens of spatial spillover
Yanzhao Li, Ju’e Guo, Wenjun Zhu
Tourism Economics (2024) Vol. 30, Iss. 7, pp. 1680-1703
Closed Access | Times Cited: 4
Incorporating grey relational analysis into decomposition ensemble models for forecasting air passenger demand
Yi‐Chung Hu, Geng Wu, Jung‐Fa Tsai
Grey Systems Theory and Application (2025)
Closed Access
Multi-dimensional perceptual recognition of tourist destination using deep learning model and geographic information system
Shengtian Zhang, Yongbo Li, Xiaoxia Song, et al.
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0318846-e0318846
Open Access
Intra‐City Tourism Flow Forecasting: A Novel Deep Learning Model
Weimin Zheng, Xin Guo, Jianqiang Li
International Journal of Tourism Research (2025) Vol. 27, Iss. 2
Closed Access
Doing shipping well with predictions: machine learning-based port congestion analysis
Yizhou Zhang, Zhenqing Su, Jiankun Li, et al.
Maritime Policy & Management (2025), pp. 1-22
Closed Access
Tourism forecasting: A dynamic spatiotemporal model
Ming Pan, Zhixue Liao, Z. Wang, et al.
Annals of Tourism Research (2024) Vol. 110, pp. 103871-103871
Closed Access | Times Cited: 2
Forecasting Visitor Arrivals at Tourist Attractions: A Time Series Framework with the N-BEATS for Sustainable Tourism
Ke Xu, Junli Zhang, Junhao Huang, et al.
Sustainability (2024) Vol. 16, Iss. 18, pp. 8227-8227
Open Access
Tourism forecast combination using weighting schemes with flow information among component models
Yi‐Chung Hu
Applied Soft Computing (2024), pp. 112498-112498
Closed Access
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