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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:

A Survey on Churn Analysis in Various Business Domains
Jaehyun Ahn, Junsik Hwang, Do-Young Kim, et al.
IEEE Access (2020) Vol. 8, pp. 220816-220839
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners
Awais Manzoor, M. Atif Qureshi, Etain Kidney, et al.
IEEE Access (2024) Vol. 12, pp. 70434-70463
Closed Access | Times Cited: 16
Machine learning based customer churn prediction in home appliance rental business
Youngjung Suh
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 30
Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art
Matthias Bogaert, Lex Delaere
Mathematics (2023) Vol. 11, Iss. 5, pp. 1137-1137
Open Access | Times Cited: 25
Digital marketing analytics: A review of strategies in the age of big data and AI
Rhoda Adura Adeleye, Kehinde Feranmi Awonuga, Onyeka Franca Asuzu, et al.
World Journal of Advanced Research and Reviews (2024) Vol. 21, Iss. 2, pp. 073-084
Open Access | Times Cited: 11
Ensemble-based deep learning techniques for customer churn prediction model
R. Siva Subramanian, B. Yamini, Kothandapani Sudha, et al.
Kybernetes (2024)
Closed Access | Times Cited: 7
Impact of Hyperparameters on Deep Learning Model for Customer Churn Prediction in Telecommunication Sector
Anouar Dalli
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 32
Modeling and prediction of business success: a survey
Divya Gangwani, Xingquan Zhu
Artificial Intelligence Review (2024) Vol. 57, Iss. 2
Open Access | Times Cited: 6
Applying Shifted-Beta-Geometric and Beta-Discrete-Weibull Models for Employee Retention Curve Projection
Evgeny Antipov, Anastasiia A. Gagarskaia, Yulia S. Trofimova, et al.
Operations Research Forum (2025) Vol. 6, Iss. 1
Closed Access
Customer churn prediction for fixed wireless access: The case of a regional internet service provider
Kurt Pflughoeft, Nikolaus T. Butz, Alick Corbley
Telecommunications Policy (2025), pp. 102929-102929
Closed Access
Optimized churn prediction using ensemble-based feature selection via second-order cone programming
Batuhan Ulug, Süreyya Özöğür‐Akyüz
Annals of Operations Research (2025)
Closed Access
Explainable text-based features in predictive models of crowdfunding campaigns
Viktor Pekar, Marina Candi, Ahmad Beltagui, et al.
Annals of Operations Research (2024)
Open Access | Times Cited: 4
Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results

(2024)
Open Access | Times Cited: 4
Improving customer retention in taxi industry using travel data analytics: A churn prediction study
A.L.D. Loureiro, Vera Miguéis, Álvaro Costa, et al.
Journal of Retailing and Consumer Services (2025) Vol. 85, pp. 104288-104288
Open Access
Research on telecom customer churn prediction based on ensemble learning
Yajun Liu, Jingjing Fan, Jianfang Zhang, et al.
Journal of Intelligent Information Systems (2022) Vol. 60, Iss. 3, pp. 759-775
Closed Access | Times Cited: 21
Customer churn prediction for web browsers
Xing Wu, Pan Li, Ming Zhao, et al.
Expert Systems with Applications (2022) Vol. 209, pp. 118177-118177
Open Access | Times Cited: 17
Task Assignment with Worker Churn Prediction in Spatial Crowdsourcing
Ziwei Wang, Yan Zhao, Xuanhao Chen, et al.
(2021), pp. 2070-2079
Closed Access | Times Cited: 22
An Ensemble Model for Predicting Retail Banking Churn in the Youth Segment of Customers
S. Vijayakumar Bharathi, Dhanya Pramod, Ramakrishnan Raman
Data (2022) Vol. 7, Iss. 5, pp. 61-61
Open Access | Times Cited: 15
Fair evaluation of classifier predictive performance based on binary confusion matrix
Amalia Vanacore, Maria Sole Pellegrino, Armando Ciardiello
Computational Statistics (2022) Vol. 39, Iss. 1, pp. 363-383
Open Access | Times Cited: 14
Dynamic Behavior-Based Churn Forecasts in the Insurance Sector
Nagaraju Jajam, Nagendra Panini Challa
Computers, materials & continua/Computers, materials & continua (Print) (2023) Vol. 75, Iss. 1, pp. 977-997
Open Access | Times Cited: 8
Mathematical Modelling and Deep Learning: Innovations in E-Commerce Sentiment Analysis
Et al. Ashish Suresh Awate
Deleted Journal (2024) Vol. 27, Iss. 1, pp. 52-81
Open Access | Times Cited: 2
Prediction of Churning Game Users Based on Social Activity and Churn Graph Neural Networks
You Jung Han, Jihoon Moon, Jiyoung Woo
IEEE Access (2024) Vol. 12, pp. 101971-101984
Open Access | Times Cited: 2
Churn in services – A bibliometric review
Hugo Ribeiro, Belém Barbosa, António Carrizo Moreira, et al.
Cuadernos de Gestión (2022) Vol. 22, Iss. 2, pp. 97-121
Open Access | Times Cited: 9
The Impact of Churn Labelling Rules on Churn Prediction in Telecommunications
Andrej Bugajev, Rima Kriauzienė, Olegas Vasilecas, et al.
Informatica (2022), pp. 247-277
Open Access | Times Cited: 9
A review on Churn Prediction and Customer Segmentation using Machine Learning
Ankita Zadoo, Tanmay Jagtap, Nikhil Khule, et al.
2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON) (2022)
Closed Access | Times Cited: 9
Three-stage churn management framework based on DCN with asymmetric loss
Xiaohuan Wen, Yanhong Wang, Xiaodong Ji, et al.
Expert Systems with Applications (2022) Vol. 207, pp. 117998-117998
Closed Access | Times Cited: 8
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