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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:

Modeling and Forecasting Regional Tourism Demand Using the Bayesian Global Vector Autoregressive (BGVAR) Model
A. George Assaf, Gang Li, Haiyan Song, et al.
Journal of Travel Research (2018) Vol. 58, Iss. 3, pp. 383-397
Open Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting
Haiyan Song, Richard T.R. Qiu, Jinah Park
Annals of Tourism Research (2019) Vol. 75, pp. 338-362
Open Access | Times Cited: 402
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 and the COVID-19 pandemic: an LSTM approach
Efstathios Polyzos, Aristeidis Samitas, Anastasia Spyridou
Tourism Recreation Research (2020) Vol. 46, Iss. 2, pp. 175-187
Closed Access | Times Cited: 176
Bayesian BILSTM approach for tourism demand forecasting
Anurag Kulshrestha, Venkataraghavan Krishnaswamy, Mayank Sharma
Annals of Tourism Research (2020) Vol. 83, pp. 102925-102925
Closed Access | Times Cited: 170
Daily tourism volume forecasting for tourist attractions
Jian-Wu Bi, Yang Liu, Hui Li
Annals of Tourism Research (2020) Vol. 83, pp. 102923-102923
Closed Access | Times Cited: 134
Improving Tourist Arrival Prediction: A Big Data and Artificial Neural Network Approach
Wolfram Höpken, Tobias Eberle, Matthias Fuchs, et al.
Journal of Travel Research (2020) Vol. 60, Iss. 5, pp. 998-1017
Closed Access | Times Cited: 118
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
Tourism demand forecasting with time series imaging: A deep learning model
Jian-Wu Bi, Hui Li, Zhi‐Ping Fan
Annals of Tourism Research (2021) Vol. 90, pp. 103255-103255
Closed Access | Times Cited: 90
Forecasting Tourism Demand with Decomposed Search Cycles
Xin Li, Rob Law
Journal of Travel Research (2019) Vol. 59, Iss. 1, pp. 52-68
Closed Access | Times Cited: 88
Using SARIMA–CNN–LSTM approach to forecast daily tourism demand
Kaijian He, Lei Ji, Don Wu, et al.
Journal of Hospitality and Tourism Management (2021) Vol. 49, pp. 25-33
Closed Access | Times Cited: 86
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
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
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
Large Bayesian matrix autoregressions
Joshua C. C. Chan, Yaling Qi
Journal of Econometrics (2025), pp. 105955-105955
Closed Access | Times Cited: 1
Diagnosing and correcting the effects of multicollinearity: Bayesian implications of ridge regression
A. George Assaf, Efthymios G. Tsionas, Αναστάσιος Τασιόπουλος
Tourism Management (2018) Vol. 71, pp. 1-8
Open Access | Times Cited: 68
Forecasting Tourist Daily Arrivals With A Hybrid Sarima–Lstm Approach
Don Wu, Lei Ji, Kaijian He, et al.
Journal of Hospitality & Tourism Research (2020) Vol. 45, Iss. 1, pp. 52-67
Closed Access | Times Cited: 63
Group pooling for deep tourism demand forecasting
Yishuo Zhang, Gang Li, Birgit Muskat, et al.
Annals of Tourism Research (2020) Vol. 82, pp. 102899-102899
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
Forecasting Daily Tourism Demand for Tourist Attractions with Big Data: An Ensemble Deep Learning Method
Jian-Wu Bi, Chunxiao Li, Hong Xu, et al.
Journal of Travel Research (2021) Vol. 61, Iss. 8, pp. 1719-1737
Closed Access | Times Cited: 43
A segmented machine learning modeling approach of social media for predicting occupancy
Apostolos Ampountolas, Mark Legg
International Journal of Contemporary Hospitality Management (2021) Vol. 33, Iss. 6, pp. 2001-2021
Closed Access | Times Cited: 42
Applying Big Data Technologies in Tourism Industry: A Conceptual Analysis
Leonidas Theodorakopoulos, Constantinos Halkiopoulos, Dimitris Papadopoulos
Springer proceedings in business and economics (2023), pp. 337-352
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
Tourism Demand and the COVID-19 Pandemic: An LSTM Approach
Efstathios Polyzos, Aristeidis Samitas, Anastasia Spyridou
SSRN Electronic Journal (2020)
Closed Access | Times Cited: 41
What drives international tourism development in the Belt and Road Initiative?
Chen Ji, Fengming Cui, Tomas Baležentis, et al.
Journal of Destination Marketing & Management (2021) Vol. 19, pp. 100544-100544
Closed Access | Times Cited: 36
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
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