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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:

Forecasting hotel demand for revenue management using machine learning regression methods
Luís Nobre Pereira, Vítor Cerqueira
Current Issues in Tourism (2021) Vol. 25, Iss. 17, pp. 2733-2750
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Application of machine learning to cluster hotel booking curves for hotel demand forecasting
Luciano Viverit, Cindy Yoonjoung Heo, Luís Nobre Pereira, et al.
International Journal of Hospitality Management (2023) Vol. 111, pp. 103455-103455
Open Access | Times Cited: 28
Tourism and Hospitality Forecasting With Big Data: A Systematic Review of the Literature
Doris Chenguang Wu, Shiteng Zhong, Ji Wu, et al.
Journal of Hospitality & Tourism Research (2024)
Open Access | Times Cited: 13
Leveraging online reviews for hotel demand forecasting: A deep learning approach
Dong Zhang, Baozhuang Niu
Information Processing & Management (2023) Vol. 61, Iss. 1, pp. 103527-103527
Closed Access | Times Cited: 17
Transformer-based probabilistic forecasting of daily hotel demand using web search behaviour
Cristof Rojas, Adam Jatowt
Knowledge-Based Systems (2025), pp. 112966-112966
Closed Access
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
Demand Forecasting for Ensuring Safety and Boosting Operational Efficiency in Hotel Hospitality Using ARIMA Model
Pranjal Kumar, Pratima Ekka
Journal of Hospitality & Tourism Education (2025), pp. 1-15
Closed Access
UTJECAJ DIGITALIZACIJE NA UPRAVLJANJE PRIHODIMA U HOTELIJERSTVU: PREGLED LITERATURE
Sandra Janković, Katarina Poldrugovac, Goran Tudorović
Hotelska kuća (2025), pp. 29-35
Closed Access
Predicting hotel booking cancellations: a comprehensive machine learning approach
Apostolos Ampountolas
Journal of Revenue and Pricing Management (2025)
Closed Access
Check-in to the future: Exploring the impact of contemporary information technologies and artificial intelligence on the hotel industry
Anđelka Štilić, Miloš Ničić, Adis Puška
Turisticko poslovanje (2023), Iss. 31, pp. 5-17
Open Access | Times Cited: 11
Halal tourism demand and firm performance forecasting: new evidence from machine learning
Zunaidah Sulong, Mohammad Abdullah, Mohammad Ashraful Ferdous Chowdhury
Current Issues in Tourism (2022) Vol. 26, Iss. 23, pp. 3765-3781
Closed Access | Times Cited: 18
Forecasting daily tourism volume: a hybrid approach with CEMMDAN and multi-kernel adaptive ensemble
Erlong Zhao, Pei Du, Ernest Young Azaglo, et al.
Current Issues in Tourism (2022) Vol. 26, Iss. 7, pp. 1112-1131
Closed Access | Times Cited: 16
Decoding the future: Proposing an interpretable machine learning model for hotel occupancy forecasting using principal component analysis
Daniele Contessi, Luciano Viverit, Luís Nobre Pereira, et al.
International Journal of Hospitality Management (2024) Vol. 121, pp. 103802-103802
Open Access | Times Cited: 3
Air passenger flow forecasting using nonadditive forecast combination with grey prediction
Yi‐Chung Hu
Journal of Air Transport Management (2023) Vol. 112, pp. 102439-102439
Closed Access | Times Cited: 7
Tourism and uncertainty: a machine learning approach
Athanasia Dimitriadou, Periklis Gogas, Théophilos Papadimitriou
Current Issues in Tourism (2024), pp. 1-21
Open Access | Times Cited: 2
Addressing complex seasonal patterns in hotel forecasting: a comparative study
Apostolos Ampountolas
Journal of Revenue and Pricing Management (2024)
Closed Access | Times Cited: 2
Utilizing textual data from online reviews for daily tourism demand forecasting: A deep learning approach leveraging word embedding techniques
Chuan Zhang, Yu‐Xin Tian, Ao-Yun Hu
Expert Systems with Applications (2024), pp. 125439-125439
Closed Access | Times Cited: 2
Explainable artificial intelligence to improve the resilience of perishable product supply chains by leveraging customer characteristics
Sunil Kumar Jauhar, Susmitha Harinath, Venkataraghavan Krishnaswamy, et al.
Annals of Operations Research (2024)
Open Access | Times Cited: 2
What online review features really matter? An explainable deep learning approach for hotel demand forecasting
Dong Zhang, Chong Wu
Journal of the Association for Information Science and Technology (2023) Vol. 74, Iss. 9, pp. 1100-1117
Closed Access | Times Cited: 5
Predicting daily hotel occupancy: a practical application for independent hotels
Apostolos Ampountolas, Mark Legg
Journal of Revenue and Pricing Management (2023) Vol. 23, Iss. 3, pp. 197-205
Closed Access | Times Cited: 5
Dynamically forecasting the restructuring performance of tourism firms with a similar-scenarios-based modelling framework: the role of investors’ ex-ante attention
Ling-Yang He, Hui Li
Current Issues in Tourism (2024), pp. 1-21
Closed Access | Times Cited: 1
How to deeply understand the voice of the customer? A proposal for a synthesis of techniques for analyzing online reviews in the hospitality industry
Thien Le, Thanh Ho, Van-Ho Nguyen, et al.
Journal of Hospitality and Tourism Insights (2024) Vol. 7, Iss. 3, pp. 1435-1455
Closed Access | Times Cited: 1
Hotel demand forecasting models and methods using artificial intelligence: A systematic literature review
Henrique Henriques, Luís Nobre Pereira
Tourism & Management Studies (2024) Vol. 20, Iss. 3, pp. 39-51
Open Access | Times Cited: 1
How broadband internet shapes household tourism decisions: a double/debiased machine learning-based difference-in-difference approach
Haowen Jia
Journal of Hospitality and Tourism Technology (2024)
Closed Access | Times Cited: 1
FROM TRADITIONAL TO NEW HOTEL REVENUE MANAGEMENT METRICS: AN EXPLORATORY STUDY ON THE POTENTIAL OF NREVPAR AND REVPAC
Detlev Remy, Huey Chern Boo, Shirley Tee
Tourism and hospitality management (2023) Vol. 29, Iss. 2, pp. 221-233
Open Access | Times Cited: 4
Hybrid demand forecasting models: pre-pandemic and pandemic use studies
Andrea Kolková, Petr Rozehnal
Equilibrium Quarterly Journal of Economics and Economic Policy (2022) Vol. 17, Iss. 3, pp. 699-725
Open Access | Times Cited: 6
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