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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 Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China
Zhao Ming, Zeng Qing-jun, Ming Chung Chang, et al.
Discrete Dynamics in Nature and Society (2021) Vol. 2021, pp. 1-12
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes
Adnan Amin, Awais Adnan, Sajid Anwar
Applied Soft Computing (2023) Vol. 137, pp. 110103-110103
Closed Access | Times Cited: 31
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
Customer churn prediction in telecom sector using machine learning techniques
Sharmila K. Wagh, Aishwarya A. Andhale, Kishor Wagh, et al.
Results in Control and Optimization (2023) Vol. 14, pp. 100342-100342
Open Access | Times Cited: 28
Optimising customer retention: An AI-driven personalised pricing approach
Yasin Ortakcı, Hüseyin Şeker
Computers & Industrial Engineering (2024) Vol. 188, pp. 109920-109920
Closed Access | Times Cited: 6
A Data-Driven Approach with Explainable Artificial Intelligence for Customer Churn Prediction in the Telecommunications Industry
Daniyal Asif, Muhammad Shoaib Arif, Aiman Mukheimer
Results in Engineering (2025), pp. 104629-104629
Open Access
Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach
Omer Bugra Kirgiz, Meltem Kiygi Calli, Sendi Cagliyor, et al.
Telecommunications Policy (2024) Vol. 48, Iss. 8, pp. 102816-102816
Closed Access | Times Cited: 2
Arithmetic Optimization with Deep Learning Enabled Churn Prediction Model for Telecommunication Industries
Vani Haridasan, Kavitha Muthukumaran, K. Hariharanath
Intelligent Automation & Soft Computing (2022) Vol. 35, Iss. 3, pp. 3531-3544
Open Access | Times Cited: 9
Customer Churn Prediction
Lavina Anand Parulekar, Prajkta Shriram Jamsandekar, Sampada Sanjay Parkar, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 2878-2883
Open Access | Times Cited: 1
Prediction of Customer Switching Using Support Vector Machine Method
Abu Tholib, Selfia Hafidatus Sholeha, Qurrotu Aini
(2024) Vol. 1, Iss. 2, pp. 65-72
Closed Access | Times Cited: 1
Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction
Olfat M. Mirza, G. Jose Moses, R. Rajender, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2022) Vol. 73, Iss. 2, pp. 3757-3769
Open Access | Times Cited: 7
A Review of Machine Learning Methods For Predicting Churn in the Telecom Sector
Fatema Akbar Mohamed, Ali K. Al‐Khalifa
(2023)
Closed Access | Times Cited: 4
A Comparative Study for Predicting the Product Type Based on the Characteristics of the Customer Complaint for Orange Jordan Telecommunication Company
Aya Ammous, Yara Alharahsheh, Raneem Qaddoura, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 3
Customer Churn Prediction using Machine Learning
Rama Krishna Peddarapu, Sofia Ameena, Surepally Yashaswini, et al.
2022 6th International Conference on Electronics, Communication and Aerospace Technology (2022), pp. 1035-1040
Closed Access | Times Cited: 5
Customer Churn Prediction Using Apriori Algorithm and Ensemble Learning
Diaa Azzam, Manar Hamed, Nora Kasiem, et al.
(2023), pp. 377-381
Closed Access | Times Cited: 2
Pendekatan Data Science untuk Menemukan Churn Pelanggan pada Sector Perbankan dengan Machine Learning
Amir Mahmud Husein, Mawaddah Harahap
Data Sciences Indonesia (DSI) (2021) Vol. 1, Iss. 1, pp. 8-13
Open Access | Times Cited: 5
Churn Prediction Model Improvement Using Automated Machine Learning with Social Network Parameters
Marin Mandić, Goran Kraljević
Revue d intelligence artificielle (2022) Vol. 36, Iss. 3, pp. 373-379
Open Access | Times Cited: 3
A novel artificial intelligent-based approach for real time prediction of telecom customer’s coming interaction
Reyad Hussien, Mohamed Mahgoub, Shahenda Youssef, et al.
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 33, Iss. 1, pp. 540-540
Open Access
Predicting churn with filter-based techniques and deep learning
Vivian Quek Jia Yi, Ying Han Pang, Lim Zheng You, et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) Vol. 14, Iss. 2, pp. 2135-2135
Open Access
Churn Prediction Model Using EDA
Shivani Sharma, Bipin Kumar, Girisha Narula, et al.
Lecture notes in electrical engineering (2024), pp. 601-614
Closed Access
Data-Driven Decision-Making: Accurate Customer Churn Prediction with Cat-Boost
Bismah Hasan, Zubair Zubair, Shahrukh Ali Shaikh, et al.
Deleted Journal (2024) Vol. 4, Iss. 02
Open Access
Examining Data Needs and Predictive Models for Broadband Take-Up Ratio Estimation through CRISP-DM and Literature Review
Wahyu Haris, Kusuma Atmaja, Arief Ramadhan, et al.
Journal of Logistics Informatics and Service Science (2024)
Open Access
Repurchase Prediction Using Survival Ensembles in CRM Systems for Home Appliance Business
Youngjung Suh
IEEE Access (2024) Vol. 12, pp. 107201-107218
Open Access
Prediksi Customer Churn Pada Bisnis Retail Menggunakan Algoritma Naïve Bayes
Agus Yulianto, Firmansyah Firmansyah
REMIK (Riset dan E-Jurnal Manajemen Informatika Komputer) (2021) Vol. 6, Iss. 1, pp. 41-47
Open Access | Times Cited: 4
Preliminary Results on the use of Artificial Intelligence for Managing Customer Life Cycles
Jim Ahlstrand, Martin Boldt, Anton Borg, et al.
Linköping electronic conference proceedings (2023) Vol. 199, pp. 68-76
Open Access | Times Cited: 1
Customer Churn Prediction Using Weight Average Ensemble Machine Learning Model
I Nyoman Mahayasa Adiputra, Paweena Wanchai
(2023), pp. 90-94
Closed Access | Times Cited: 1
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