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 decade of research on machine learning techniques for predicting employee turnover: A systematic literature review
Mariam Al Akasheh, Esraa Faisal Malik, Omar Hujran, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121794-121794
Closed Access | Times Cited: 16

Showing 16 citing articles:

The importance of positive employee experience and its development through using predictive analytics
Donát Vereb, Zoltán Krajcsák, Anita Kozák
Journal of Modelling in Management (2024)
Closed Access | Times Cited: 4

Construction and application of intelligent human resource management system based on machine learning algorithm
Ping Yang, Jianxin Li
Journal of Computational Methods in Sciences and Engineering (2025)
Closed Access

A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition
Farhad Mortezapour Shiri, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 2984-2984
Open Access

Hybrid machine learning approach for parallel machine scheduling under uncertainty
Aleksandar Stanković, Goran Petrović, Rajko Turudija, et al.
Expert Systems with Applications (2025) Vol. 279, pp. 127427-127427
Closed Access

Who and why will leave me? Utilizing Machine Learning-Based Models to Anticipate and Manage Employee Turnover
Chiara Morelli, Gianluca Fusai, Raffaele Zenti
SSRN Electronic Journal (2024)
Closed Access | Times Cited: 3

Explainable Machine Learning and Graph Neural Network Approaches for Predicting Employee Attrition
Christopher Makanga, Dennis Mukwaba, Clare Linda Agaba, et al.
(2024), pp. 243-255
Closed Access | Times Cited: 2

Medición y comparación del rendimiento de cuatro algoritmos de aprendizaje supervisado para formular modelos predictivos sobre la rotación temprana de personal
Francisco Javier Segura Mojica
ESIC MARKET Economic and Business Journal (2024) Vol. 54, Iss. 2, pp. e318-e318
Open Access | Times Cited: 2

Management of Human Resources 2.0: Applying Machine Learning to the Recruitment and Retention of Talent
Somanchi Hari Krishna, Nivedita Pandey, Thejasvi Sheshadri, et al.
(2024), pp. 1438-1441
Closed Access

Predicting Employee Turnover Through Genetic Algorithm
Vincent Jake Recilla, Mohn Romy A. Enonaria, Reyper John Florida, et al.
(2024), pp. 1383-1391
Closed Access

Salary Prediction with Machine Learning in Teachers Hired from the Region of Cusco Perú
Segundo Canahuire Hilari, Joel Larico Carbajal, Ferdinand Pineda, et al.
Lecture notes in networks and systems (2024), pp. 128-143
Closed Access

Strategic management of employee churn: Leveraging machine learning for sustainable development and competitive advantage in emerging markets
Poorva Agrawal, Seema Ghangale, Bablu Kumar Dhar, et al.
Business Strategy & Development (2024) Vol. 7, Iss. 4
Closed Access

Internal Turnover Intention in Indonesian Government Organization
Ardi Artopo, Salamah Wahyuni
Journal of Open Innovation Technology Market and Complexity (2024), pp. 100433-100433
Open Access

Leveraging Artificial Neural Networks for Mining Nursing Talents in Elderly Care
Huiying Dai, Pooja Solanki
International Journal of Healthcare Information Systems and Informatics (2024) Vol. 19, Iss. 1, pp. 1-14
Open Access

Penentuan Kluster UMKM Sektor Perdagangan dan Perikanan Melalui Pendekatan Metode Clustering Data Mining di Kabupaten Aceh Barat
Arie Saputra, Riski Asnif Sahputra
Jurnal Optimalisasi (2023) Vol. 9, Iss. 2, pp. 173-173
Open Access | Times Cited: 1

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