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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:

Spatial-temporal forecasting of tourism demand
Yang Yang, Honglei Zhang
Annals of Tourism Research (2019) Vol. 75, pp. 106-119
Closed Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

Forecasting tourism demand with multisource big data
Hengyun Li, Mingming Hu, Gang Li
Annals of Tourism Research (2020) Vol. 83, pp. 102912-102912
Open Access | Times Cited: 181
Tourism Demand Forecasting: A Decomposed Deep Learning Approach
Yishuo Zhang, Gang Li, Birgit Muskat, et al.
Journal of Travel Research (2020) Vol. 60, Iss. 5, pp. 981-997
Open Access | Times Cited: 118
Machine Learning in Internet Search Query Selection for Tourism Forecasting
Xin Li, Hengyun Li, Bing Pan, et al.
Journal of Travel Research (2020) Vol. 60, Iss. 6, pp. 1213-1231
Open Access | Times Cited: 81
Forecasting international tourism demand: a local spatiotemporal model
Xiaoying Jiao, Gang Li, Jason Li Chen
Annals of Tourism Research (2020) Vol. 83, pp. 102937-102937
Open Access | Times Cited: 73
Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?
Yang Yang, Yawen Fan, Lan Jiang, et al.
Annals of Tourism Research (2022) Vol. 93, pp. 103365-103365
Closed Access | Times Cited: 49
Tourism demand forecasting with spatiotemporal features
Cheng Li, Weimin Zheng, Peng Ge
Annals of Tourism Research (2022) Vol. 94, pp. 103384-103384
Closed Access | Times Cited: 38
Forecasting hourly attraction tourist volume with search engine and social media data for decision support
Gang Xue, Shifeng Liu, Long Ren, et al.
Information Processing & Management (2023) Vol. 60, Iss. 4, pp. 103399-103399
Closed Access | Times Cited: 26
Enhancing tourism demand forecasting with a transformer-based framework
Xin Li, Yechi Xu, Rob Law, et al.
Annals of Tourism Research (2024) Vol. 107, pp. 103791-103791
Open Access | Times Cited: 10
Modeling Airbnb demand to New York City while employing spatial panel data at the listing level
Ulrich Gunter, İrem Önder, Bozana Zekan
Tourism Management (2019) Vol. 77, pp. 104000-104000
Closed Access | Times Cited: 62
Multi-attraction, hourly tourism demand forecasting
Weimin Zheng, Liyao Huang, Zhibin Lin
Annals of Tourism Research (2021) Vol. 90, pp. 103271-103271
Open Access | Times Cited: 46
Analysis of spatial patterns and driving factors of provincial tourism demand in China
Xuankai Ma, Zhaoping Yang, Jianghua Zheng
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 32
A graph-attention based spatial-temporal learning framework for tourism demand forecasting
Binggui Zhou, Yunxuan Dong, Guanghua Yang, et al.
Knowledge-Based Systems (2023) Vol. 263, pp. 110275-110275
Closed Access | Times Cited: 16
Tourism demand forecasting using complex network theory
Weimin Zheng, Jianqiang Li, Cheng Li
Asia Pacific Journal of Tourism Research (2024) Vol. 29, Iss. 3, pp. 302-320
Closed Access | Times Cited: 6
Forecasting daily attraction demand using big data from search engines and social media
Tian Feng-jun, Yang Yang, Zhenxing Mao, et al.
International Journal of Contemporary Hospitality Management (2021) Vol. 33, Iss. 6, pp. 1950-1976
Closed Access | Times Cited: 37
Novel deep learning approach for forecasting daily hotel demand with agglomeration effect
Liyao Huang, Weimin Zheng
International Journal of Hospitality Management (2021) Vol. 98, pp. 103038-103038
Closed Access | Times Cited: 36
Visitor flow spillover effects on attraction demand: A spatial econometric model with multisource data
Yoo Ri Kim, Anyu Liu, Jason L. Stienmetz, et al.
Tourism Management (2021) Vol. 88, pp. 104432-104432
Open Access | Times Cited: 36
Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model
Haodong Sun, Yang Yang, Yanyan Chen, et al.
Information Technology & Tourism (2023) Vol. 25, Iss. 2, pp. 205-233
Open Access | Times Cited: 15
Forecasting daily tourism demand with multiple factors
Shilin Xu, Yang Liu, Chun Jin
Annals of Tourism Research (2023) Vol. 103, pp. 103675-103675
Closed Access | Times Cited: 15
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
The Olive Grove Landscape as a Tourist Resource in Andalucía: Oleotourism
Ma Genoveva Dancausa Millán, Javier Sánchez-Rivas García, María Genoveva Millán Vázquez de la Torre
Land (2023) Vol. 12, Iss. 8, pp. 1507-1507
Open Access | Times Cited: 13
A survey on spatio-temporal series prediction with deep learning: taxonomy, applications, and future directions
Feiyan Sun, Wenning Hao, Ao Zou, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 17, pp. 9919-9943
Closed Access | Times Cited: 4
Forecasting tourism demand: Developing a general nesting spatiotemporal model
Xiaoying Jiao, Jason Li Chen, Gang Li
Annals of Tourism Research (2021) Vol. 90, pp. 103277-103277
Open Access | Times Cited: 28
Exploring the influence of natural and cultural environments on tourism demand: a spatial analysis
W Gu, Zhongzhu Chu, Xin Li
Asia Pacific Journal of Tourism Research (2024) Vol. 29, Iss. 4, pp. 440-460
Closed Access | Times Cited: 3
Ex Ante Tourism Forecasting Assessment
Anyu Liu, Vera Shanshan Lin, Gang Li, et al.
Journal of Travel Research (2020) Vol. 61, Iss. 1, pp. 64-75
Open Access | Times Cited: 30
Collaborative forecasting of tourism demand for multiple tourist attractions with spatial dependence: A combined deep learning model
Jian-Wu Bi, Tianyu Han, Yanbo Yao
Tourism Economics (2023) Vol. 30, Iss. 2, pp. 361-388
Closed Access | Times Cited: 10
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