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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:

Prediction of bankruptcy using support vector machines: an application to bank bankruptcy
Birsen Eygi Erdoğan
Journal of Statistical Computation and Simulation (2012) Vol. 83, Iss. 8, pp. 1543-1555
Closed Access | Times Cited: 76

Showing 1-25 of 76 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: 257
Predicting failure in the U.S. banking sector: An extreme gradient boosting approach
Pedro Carmona, Francisco Climent, Alexandre Momparler
International Review of Economics & Finance (2018) Vol. 61, pp. 304-323
Closed Access | Times Cited: 239
Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks
Félix J. López‐Iturriaga, Iván Pastor Sanz
Expert Systems with Applications (2014) Vol. 42, Iss. 6, pp. 2857-2869
Closed Access | Times Cited: 188
Anticipating bank distress in the Eurozone: An Extreme Gradient Boosting approach
Francisco Climent, Alexandre Momparler, Pedro Carmona
Journal of Business Research (2018) Vol. 101, pp. 885-896
Closed Access | Times Cited: 130
Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction
Vicente García, Ana I. Marqués, J. Salvador Sánchez
Information Fusion (2018) Vol. 47, pp. 88-101
Open Access | Times Cited: 118
A new perspective of performance comparison among machine learning algorithms for financial distress prediction
Yu‐Pei Huang, Meng-Feng Yen
Applied Soft Computing (2019) Vol. 83, pp. 105663-105663
Closed Access | Times Cited: 116
AdaBoost based bankruptcy forecasting of Korean construction companies
Junyoung Heo, Jin-Yong Yang
Applied Soft Computing (2014) Vol. 24, pp. 494-499
Closed Access | Times Cited: 107
Forecasting bank failures and stress testing: A machine learning approach
Periklis Gogas, Théophilos Papadimitriou, Άννα Αγραπετίδου
International Journal of Forecasting (2018) Vol. 34, Iss. 3, pp. 440-455
Closed Access | Times Cited: 90
Bankruptcy Prediction Using Deep Learning Approach Based on Borderline SMOTE
Salima Smiti, Makram Soui
Information Systems Frontiers (2020) Vol. 22, Iss. 5, pp. 1067-1083
Closed Access | Times Cited: 90
Support Vector Machine Methods and Artificial Neural Networks Used for the Development of Bankruptcy Prediction Models and their Comparison
Jakub Horák, Jaromír Vrbka, Petr Šuleř
Journal of risk and financial management (2020) Vol. 13, Iss. 3, pp. 60-60
Open Access | Times Cited: 74
No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure
Pedro Carmona, Aladdin Dwekat, Zeena Mardawi
Research in International Business and Finance (2022) Vol. 61, pp. 101649-101649
Open Access | Times Cited: 55
Financial distress prediction using the hybrid associative memory with translation
L. Cleofas-Sánchez, Vicente García, Ana I. Marqués, et al.
Applied Soft Computing (2016) Vol. 44, pp. 144-152
Open Access | Times Cited: 76
Ensemble learning with label proportions for bankruptcy prediction
Zhensong Chen, Wei Chen, Yong Shi
Expert Systems with Applications (2019) Vol. 146, pp. 113155-113155
Closed Access | Times Cited: 75
A Survey on Machine Learning and Statistical Techniques in Bankruptcy Prediction
Sunitha Devi, Y. Radhika
International Journal of Machine Learning and Computing (2018) Vol. 8, Iss. 2, pp. 133-139
Open Access | Times Cited: 65
A Race for Long Horizon Bankruptcy Prediction
Edward I. Altman, Małgorzata Iwanicz‐Drozdowska, Erkki K. Laitinen, et al.
Applied Economics (2020) Vol. 52, Iss. 37, pp. 4092-4111
Open Access | Times Cited: 53
A conservative approach for online credit scoring
Afshin Ashofteh, Jorge Miguel Bravo
Expert Systems with Applications (2021) Vol. 176, pp. 114835-114835
Open Access | Times Cited: 44
Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis
Zhiyong Li, Feng Chen, Ying Tang
Annals of Operations Research (2022) Vol. 315, Iss. 1, pp. 279-315
Open Access | Times Cited: 29
Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries
Katarína Valašková, Dominika Gajdosikova, Jaroslav Belás
Oeconomia Copernicana (2023) Vol. 14, Iss. 1, pp. 253-293
Open Access | Times Cited: 20
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: 7
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: 7
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: 39
Data depth based support vector machines for predicting corporate bankruptcy
Sung-Do Kim, Byeong Min Mun, Suk Joo Bae
Applied Intelligence (2017) Vol. 48, Iss. 3, pp. 791-804
Closed Access | Times Cited: 44
Bankruptcy Prediction Using Stacked Auto-Encoders
Makram Soui, Salima Smiti, Mohamed Wiem Mkaouer, et al.
Applied Artificial Intelligence (2019) Vol. 34, Iss. 1, pp. 80-100
Closed Access | Times Cited: 37
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks
Wendong Bi, Bingbing Xu, Xiaoqian Sun, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 2712-2720
Open Access | Times Cited: 22
Cognitive Modelling of Bankruptcy Risk: A Comparative Analysis of Machine Learning Models to Predict the Bankruptcy
Jahirul Islam, Sabuj Saha, Mahadi Hasan, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 4
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