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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:

Gaussian case-based reasoning for business failure prediction with empirical data in China
Hui Li, Jie Sun
Information Sciences (2008) Vol. 179, Iss. 1-2, pp. 89-108
Closed Access | Times Cited: 97

Showing 1-25 of 97 citing articles:

Machine learning models and bankruptcy prediction
Flávio Barboza, Herbert Kimura, Edward I. Altman
Expert Systems with Applications (2017) Vol. 83, pp. 405-417
Closed Access | Times Cited: 692
A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems
Arash Bahrammirzaee
Neural Computing and Applications (2010) Vol. 19, Iss. 8, pp. 1165-1195
Closed Access | Times Cited: 491
Prediction of financial distress: An empirical study of listed Chinese companies using data mining
Ruibin Geng, Indranil Bose, Xi Chen
European Journal of Operational Research (2014) Vol. 241, Iss. 1, pp. 236-247
Closed Access | Times Cited: 414
Machine Learning in Financial Crisis Prediction: A Survey
Wei-Yang Lin, Ya‐Han Hu, Chih‐Fong Tsai
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) (2011) Vol. 42, Iss. 4, pp. 421-436
Closed Access | Times Cited: 300
A hybrid ANFIS model for business failure prediction utilizing particle swarm optimization and subtractive clustering
Mu‐Yen Chen
Information Sciences (2011) Vol. 220, pp. 180-195
Closed Access | Times Cited: 186
An improved boosting based on feature selection for corporate bankruptcy prediction
Gang Wang, Jian Ma, Shanlin Yang
Expert Systems with Applications (2013) Vol. 41, Iss. 5, pp. 2353-2361
Closed Access | Times Cited: 168
A Deep Learning-Based Approach to Constructing a Domain Sentiment Lexicon: a Case Study in Financial Distress Prediction
Shixuan Li, Wenxuan Shi, Jiancheng Wang, et al.
Information Processing & Management (2021) Vol. 58, Iss. 5, pp. 102673-102673
Closed Access | Times Cited: 78
Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection
Lean Yu, Xiao Yao, Shouyang Wang, et al.
Expert Systems with Applications (2011) Vol. 38, Iss. 12, pp. 15392-15399
Closed Access | Times Cited: 95
Application of Machine Learning Methods to Risk Assessment of Financial Statement Fraud: Evidence from China
Xinping Song, Zhi‐Hua Hu, Jianguo Du, et al.
Journal of Forecasting (2014) Vol. 33, Iss. 8, pp. 611-626
Closed Access | Times Cited: 91
Bankruptcy prediction using Partial Least Squares Logistic Regression
Sami Ben Jabeur
Journal of Retailing and Consumer Services (2017) Vol. 36, pp. 197-202
Closed Access | Times Cited: 85
An insight into the experimental design for credit risk and corporate bankruptcy prediction systems
Vicente García, Ana I. Marqués, J. Salvador Sánchez
Journal of Intelligent Information Systems (2014) Vol. 44, Iss. 1, pp. 159-189
Closed Access | Times Cited: 71
A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms
Yin Shi, Xiaoni Li
Heliyon (2019) Vol. 5, Iss. 12, pp. e02997-e02997
Open Access | Times Cited: 70
Investigation of the Factors Influencing SME Failure as a Function of Its Prevention and Fast Recovery after Failure
Nenad Nikolić, I. Jovanović, Đjordje Nikolić, et al.
Entrepreneurship Research Journal (2018) Vol. 9, Iss. 3
Open Access | Times Cited: 65
Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods
Xiaobo Tang, Shixuan Li, Mingliang Tan, et al.
Journal of Forecasting (2020) Vol. 39, Iss. 5, pp. 769-787
Closed Access | Times Cited: 64
A new random subspace method incorporating sentiment and textual information for financial distress prediction
Gang Wang, Gang Chen, Yan Chu
Electronic Commerce Research and Applications (2018) Vol. 29, pp. 30-49
Closed Access | Times Cited: 59
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
A case-based reasoning driven ensemble learning paradigm for financial distress prediction with missing data
Lean Yu, Mengxin Li
Applied Soft Computing (2023) Vol. 137, pp. 110163-110163
Closed Access | Times Cited: 19
A two-stage case-based reasoning driven classification paradigm for financial distress prediction with missing and imbalanced data
Lean Yu, Mengxin Li, Xiaojun Liu
Expert Systems with Applications (2024) Vol. 249, pp. 123745-123745
Closed Access | Times Cited: 7
Predicting business failure using multiple case-based reasoning combined with support vector machine
Hui Li, Jie Sun
Expert Systems with Applications (2009) Vol. 36, Iss. 6, pp. 10085-10096
Closed Access | Times Cited: 87
HYBRID NEURAL INTELLIGENT SYSTEM TO PREDICT BUSINESS FAILURE IN SMALL-TO-MEDIUM-SIZE ENTERPRISES
L. Borrajo, Bruno Baruque, Emilio Corchado, et al.
International Journal of Neural Systems (2011) Vol. 21, Iss. 04, pp. 277-296
Closed Access | Times Cited: 77
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
Predicting Financial Distress in India: A Deep Learning Approach
Alay Peralungal, Natchimuthu Natchimuthu
Smart innovation, systems and technologies (2025), pp. 587-603
Closed Access
Failure prediction of dotcom companies using neural network–genetic programming hybrids
P. Ravisankar, Vadlamani Ravi, Indranil Bose
Information Sciences (2010) Vol. 180, Iss. 8, pp. 1257-1267
Closed Access | Times Cited: 62
Business failure prediction using hybrid2 case-based reasoning (H2CBR)
Hui Li, Jie Sun
Computers & Operations Research (2009) Vol. 37, Iss. 1, pp. 137-151
Closed Access | Times Cited: 61
A multi-agent system for web-based risk management in small and medium business
Javier Bajo, María L. Borrajo, Juan F. De Paz, et al.
Expert Systems with Applications (2012) Vol. 39, Iss. 8, pp. 6921-6931
Open Access | Times Cited: 52
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