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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:

The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
Shusheng Ding, Tianxiang Cui, Anthony Graham Bellotti, et al.
International Review of Financial Analysis (2023) Vol. 90, pp. 102851-102851
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
Tianxiang Cui, Nanjiang Du, Xiaoying Yang, et al.
Technological Forecasting and Social Change (2023) Vol. 198, pp. 122944-122944
Open Access | Times Cited: 20
Predicting M&A targets using news sentiment and topic detection
Petr Hájek, Roberto Henriques
Technological Forecasting and Social Change (2024) Vol. 201, pp. 123270-123270
Open Access | Times Cited: 6
Resampling Techniques Study on Class Imbalance Problem in Credit Risk Prediction
Zixue Zhao, Tianxiang Cui, Shusheng Ding, et al.
Mathematics (2024) Vol. 12, Iss. 5, pp. 701-701
Open Access | Times Cited: 6
Practical forecasting of risk boundaries for industrial metals and critical minerals via statistical machine learning techniques
Insu Choi, Woo Chang Kim
International Review of Financial Analysis (2024) Vol. 94, pp. 103252-103252
Closed Access | Times Cited: 6
Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework
Ruize Gao, Shaoze Cui, Yu Wang, et al.
Financial Innovation (2025) Vol. 11, Iss. 1
Open Access
What makes companies zombie? Detecting the most important zombification feature using tree-based machine learning
Rayenda Khresna Brahmana
Expert Systems with Applications (2025), pp. 126538-126538
Open Access
An Ensemble Model Minimising Misjudgment Cost: Empirical Evidence From Chinese Listed Companies
Kunpeng Yuan, Mohammad Zoynul Abedin, Petr Hájek
International Journal of Finance & Economics (2025)
Open Access
Advancing financial risk management: A transparent framework for effective fraud detection
Wenjuan Li, Xinghua Liu, Junqi Su, et al.
Finance research letters (2025), pp. 106865-106865
Open Access
A novel method for corn futures price prediction integrating decomposition, denoising, feature selection and hybrid networks
Chen Yi
Annals of Operations Research (2025)
Closed Access
Financial Distress Early Warning for Chinese Enterprises from a Systemic Risk Perspective: Based on the Adaptive Weighted XGBoost-Bagging Model
Wensheng Wang, Zhiliang Liang
Systems (2024) Vol. 12, Iss. 2, pp. 65-65
Open Access | Times Cited: 3
İşletmelerin Finansal Başarısızlık Riskine Sermaye Yapısının Etkisi: KOBİ Sanayi Endeksi
Pınar Avci
Politik Ekonomik Kuram (2024) Vol. 8, Iss. 1, pp. 174-188
Open Access | Times Cited: 2
Corporate Reputation, Available Slack, And Financial Distress Risk
Aminatuzzuhro Aminatuzzuhro, Trisa Indrawati, Nurul Fitriani
Jurnal Akuntansi (2024) Vol. 28, Iss. 1, pp. 125-146
Open Access | Times Cited: 1
The financial health of a company and the risk of its default: Back to the future
Francesco Dainelli, Gianmarco Bet, Eugenio Fabrizi
International Review of Financial Analysis (2024) Vol. 95, pp. 103449-103449
Open Access | Times Cited: 1
Balancing Techniques for Advanced Financial Distress Detection Using Artificial Intelligence
Dovilė Kuizinienė, Tomas Krilavičius
Electronics (2024) Vol. 13, Iss. 8, pp. 1596-1596
Open Access
Financial distress prediction using an improved particle swarm optimization wrapper feature selection method and tree boosting ensemble
Jiaming Liu, Zihang Wang
Journal of the Operational Research Society (2024), pp. 1-24
Closed Access
Cardinality and Bounding Constrained Portfolio Optimization Using Safe Reinforcement Learning
Y. M. Li, Nanjiang Du, Xingke Song, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 17, pp. 1-8
Closed Access
An End-to-end Framework for Few-shot Millimeter-wave Radar-based Hand Gesture Recognition
Yulin Ye, Tianxiang Cui, Shisheng Guo, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 27, pp. 1-8
Closed Access
Class Imbalance Bayesian Model Averaging for Consumer Loan Default Prediction: The Role of Soft Credit Information
Futian Weng, Miao Zhu, Mike Buckle, et al.
Research in International Business and Finance (2024), pp. 102722-102722
Open Access
An explainable framework based on counterfactual explanations for multi-class financial distress prediction of small and medium enterprises
Rie Kubota Ando, Yuji Kawamata, Tetsuya Takeda, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 2269-2274
Closed Access
Analysis of Enterprise Financial Risk Early Warning Model Based on the Evidence Theory and Whitening Weight Function
Tianjiao Zhang, Q Chen, X L Zhu
Scientific Programming (2024) Vol. 2024, Iss. 1
Open Access
Government Accounting Reform, Fiscal Transparency, and Local Government Debt: Evidence from China
Xihong Wan, Min Guo, Ping Jiang, et al.
(2024)
Closed Access
Evolution-Assisted Deep Reinforcement Learning for Fast Charging Station Coordinated Operation
Xiaoying Yang, Yujing Gu, Fuhua Jia, et al.
2022 IEEE Congress on Evolutionary Computation (CEC) (2024), pp. 1-9
Closed Access
Financial distress prediction with annual reports-based deep textual feature extraction: A hybrid approach
Jiaming Liu, Ming Jia
Information Sciences (2024) Vol. 686, pp. 121318-121318
Closed Access
Mitigating Financial Distress by Engaging in Digital Transformation: The Moderating Role of Life Cycles
Jianbo Zhang, Yandan Yu, Zhen Wei, et al.
Systems (2024) Vol. 12, Iss. 12, pp. 513-513
Open Access
Predicting financial distress in TSX-listed firms using machine learning algorithms
Mark Lokanan, Sana Ramzan
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access
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