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Shen, Z.-D., & Chen, S. (2022). "Financial distress prediction: A hybrid tracking model approach." Asian Journal of Economics, Business and Accounting, 22(24), 185-192. |
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Suduan Chen. 2019. “An Effective Going Concern Prediction Model for the Sustainability of Enterprises and Capital Market Development.” Applied Economics 51(31):3376-3388. (SSCI) DOI: 10.1080/00036846.2019.1578855. |
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Suduan Chen. 2016. “Detection of Fraudulent Financial Statements Using the Hybrid Data Mining Approach.” SpringerPlus 5:89. DOI: 10.1186/s40064-016-1707-6. (SCIE) |
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Suduan Chen*, Stephen Jhuang. 2018. “Financial Distress Prediction Using Data Mining Techniques.” ICIC Express Letters, Part B: Applications 9(2):131-136. (EI Indexed) |
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Suduan Chen, Zong-De Shen. 2020. “An Effective Enterprise Earnings Management Detection Model for Capital Market Development.” Journal of Economics, Management and Trade 26(4):77-91. |
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Suduan Chen, Zong-De Shen. 2020. “Financial Distress Prediction Using Hybrid Machine Learning Techniques.” Asian Journal of Economics, Business and Accounting 16(2):1-12. |
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Suduan Chen. 2015. “Seasoned Equity Offerings or Capital Deductions? The Reaction of Stock Prices: Evidence from Taiwan.” Emerging Markets Finance and Trade 53(3):644-660 DOI:10.1080/1540496X.2015.1097991 (SSCI) |
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Suduan Chen, Hsu-Feng Hung. 2016. “A Formative Measurement Test of Supplier Evaluation Indicators and Weight Models.” Journal of Testing and Evaluation 44(3). (SCI) |
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Suduan Chen, Zone-de Shen and Yeong-Jia James Goo. 2014. “A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements.” The Scientific World Journal, vol. 2014. Article ID 968712. (SCIE) |
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Suduan Chen and Jimmy Lee. 2015. “Going Concern Prediction Using Data Mining.” ICIC Express Letters, Part B: Applications Vol.6, No.12. (EI) |
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張瑞珍、吳庭斌、陳素緞、張智翔,考量違約相關性之信用風險衡量 ( Measuring Credit Risk with Default Correlation ). 管理學報,vol.32(3),2015年9月出版。(TSSCI) |
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