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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:

Data analytic approach for bankruptcy prediction
Hyunwoo Son, Chongseok Hyun, Dinh‐Van Phan, et al.
Expert Systems with Applications (2019) Vol. 138, pp. 112816-112816
Closed Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

CatBoost model and artificial intelligence techniques for corporate failure prediction
Sami Ben Jabeur, Cheima Gharib, Salma Mefteh‐Wali, et al.
Technological Forecasting and Social Change (2021) Vol. 166, pp. 120658-120658
Closed Access | Times Cited: 252
Financial applications of machine learning: A literature review
Noella Nazareth, Y.V. Reddy
Expert Systems with Applications (2023) Vol. 219, pp. 119640-119640
Closed Access | Times Cited: 107
Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering
Sami Ben Jabeur, Nicolae Stef, Pedro Carmona
Computational Economics (2022) Vol. 61, Iss. 2, pp. 715-741
Closed Access | Times Cited: 101
Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction
Jinxian Zhao, Jamal Ouenniche, Johannes De Smedt
Machine Learning with Applications (2024) Vol. 15, pp. 100527-100527
Open Access | Times Cited: 16
Financial distress prediction using a corrected feature selection measure and gradient boosted decision tree
Hongyi Qian, Baohui Wang, Minghe Yuan, et al.
Expert Systems with Applications (2021) Vol. 190, pp. 116202-116202
Closed Access | Times Cited: 85
Data‐driven modelling methods in sintering process: Current research status and perspectives
Yan Feng, Xinmin Zhang, Chunjie Yang, et al.
The Canadian Journal of Chemical Engineering (2022) Vol. 101, Iss. 8, pp. 4506-4522
Open Access | Times Cited: 55
Optimizing investment portfolios with a sequential ensemble of decision tree-based models and the FBI algorithm for efficient financial analysis
Jui‐Sheng Chou, Ke-En Chen
Applied Soft Computing (2024) Vol. 158, pp. 111550-111550
Closed Access | Times Cited: 9
Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods
Elena Gregová, Katarína Valašková, Peter Adamko, et al.
Sustainability (2020) Vol. 12, Iss. 10, pp. 3954-3954
Open Access | Times Cited: 65
A Hybrid Metaheuristic Method in Training Artificial Neural Network for Bankruptcy Prediction
Abdollah Ansari, Ibrahim Said Ahmad, Azuraliza Abu Bakar, et al.
IEEE Access (2020) Vol. 8, pp. 176640-176650
Open Access | Times Cited: 54
Big data analytics for default prediction using graph theory
Mustafa Yıldırım, Feyza Yıldırım Okay, Suat Özdemi̇r
Expert Systems with Applications (2021) Vol. 176, pp. 114840-114840
Closed Access | Times Cited: 53
A Machine Learning-based DSS for mid and long-term company crisis prediction
Guido Perboli, Ehsan Arabnezhad
Expert Systems with Applications (2021) Vol. 174, pp. 114758-114758
Open Access | Times Cited: 46
Explainability of Machine Learning Models for Bankruptcy Prediction
Min Sue Park, Hwijae Son, Chongseok Hyun, et al.
IEEE Access (2021) Vol. 9, pp. 124887-124899
Open Access | Times Cited: 45
Chinese corporate distress prediction using LASSO: The role of earnings management
Chunyu Li, Chenxin Lou, Dan Luo, et al.
International Review of Financial Analysis (2021) Vol. 76, pp. 101776-101776
Closed Access | Times Cited: 43
Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence
Jurgita Černevičienė, Audrius Kabašinskas
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 36
Impacts of crisis on SME bankruptcy prediction models’ performance
Mário Papík, Lenka Papíková
Expert Systems with Applications (2022) Vol. 214, pp. 119072-119072
Closed Access | Times Cited: 33
Systematic Review of Financial Distress Identification using Artificial Intelligence Methods
Dovilė Kuizinienė, Tomas Krilavičius, Robertas Damaševičius, et al.
Applied Artificial Intelligence (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 31
An innovative machine learning workflow to research China’s systemic financial crisis with SHAP value and Shapley regression
Da Wang, YingXue Zhou
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Tax Default Prediction Using Feature Transformation-Based Machine Learning
Mohammad Zoynul Abedin, Guotai Chi, Mohammed Mohi Uddin, et al.
IEEE Access (2020) Vol. 9, pp. 19864-19881
Open Access | Times Cited: 43
The implication of machine learning for financial solvency prediction: an empirical analysis on public listed companies of Bangladesh
Mohammad Abdullah
Journal of Asian Business and Economic Studies (2021) Vol. 28, Iss. 4, pp. 303-320
Open Access | Times Cited: 40
Company bankruptcy prediction framework based on the most influential features using XGBoost and stacking ensemble learning
Much Aziz Muslim, Yosza Dasril
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2021) Vol. 11, Iss. 6, pp. 5549-5549
Open Access | Times Cited: 38
Machine learning approaches for explaining determinants of the debt financing in heavy-polluting enterprises
Boqiang Lin, Rui Bai
Finance research letters (2021) Vol. 44, pp. 102094-102094
Closed Access | Times Cited: 33
Economic policy uncertainty and bankruptcy filings
Елена Федорова, Svetlana Ledyaeva, Pavel Drogovoz, et al.
International Review of Financial Analysis (2022) Vol. 82, pp. 102174-102174
Open Access | Times Cited: 27
Machine learning techniques in bankruptcy prediction: A systematic literature review
Απόστολος Δασίλας, Anna Rigani
Expert Systems with Applications (2024) Vol. 255, pp. 124761-124761
Closed Access | Times Cited: 5
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Selçuk Demir, Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3273-3290
Open Access | Times Cited: 4
Bootstrap variable selection for corporate distress prediction: evidence from the Chinese manufacturing industry
Shan Li, Yajuan Huang, Kai Xing, et al.
Applied Economics (2024), pp. 1-19
Closed Access | Times Cited: 4
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