Hui Li

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Jie SunProfessor of Zhejiang Normal UniversityVerified email at zjnu.cn
Sai LiangCollege of Tourism and Service Management, Nankai UniversityVerified email at nankai.edu.cn
Hamido FujitaIwate Prefectural UniversityVerified email at acm.org
Jian-Wu BiNankai UniversityVerified email at nankai.edu.cn
Jian WuProfessor, Shanghai Maritime UniversityVerified email at zjnu.cn
Hojjat AdeliThe Ohio State UniversityVerified email at osu.edu
Dongdong WuNankai University, Jiangnan University, Lamar University (Visiting scholar))Verified email at stu.jiangnan.edu.cn
Young-Chan LeeProfessor of Business Analytics, Dongguk UniversityVerified email at dongguk.ac.kr
Lean YuAcademy of Mathematics and Systems Science, CAS; School of Economics and Management, BUCTVerified email at amss.ac.cn
Zhi-Ping FanNortheastern UniversityVerified email at mail.neu.edu.cn
Yuhong WangJiangnan UniversityVerified email at jiangnan.edu.cn
Markus SchuckertUniversity of New HampshireVerified email at unh.edu
Xianwei LiuHarbin Institute of TechnologyVerified email at hit.edu.cn
Diego AndinaUniversidad Politécnica de Madrid (UPM). Full Professor.Verified email at upm.es
Rob LawUniversity of MacauVerified email at um.edu.mo
Tafazal KumailCollege of Tourism and Service Management, Nankai University, Tianjin, ChinaVerified email at nankai.edu.cn
Muhammad ZahidProfessor/Dean/Principal Bahria Business School, Bahria University, PakistanVerified email at bahria.edu.pk
Kazi SohagAssociate Professor, Graduate School of Economics and Management, Ural Federal UniversityVerified email at urfu.ru
Dr. Wajahat AliCollege of Business and Public Management, Wenzhou-Kean University, ChinaVerified email at kean.edu
Zhibin LinProfessor in Marketing, Durham UniversityVerified email at durham.ac.uk

Hui Li

Distinguished Young Professor of Nankai University. Former Professor of Zhejiang Normal University

Verified email at zjnu.edu.cn - Homepage

Tourism Coroprate Management and Governance Tourism Big Data Mining & Decision Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches J Sun, H Li, QH Huang, KY He Knowledge-Based Systems 57, 41-56, 2014	448	2014
Imbalanced enterprise credit evaluation with DTE-SBD: Decision tree ensemble based on SMOTE and bagging with differentiated sampling rates J Sun, J Lang, H Fujita, H Li Information Sciences 425, 76-91, 2018	354	2018
Data mining method for listed companies’ financial distress prediction J Sun, H Li Knowledge-Based Systems 21 (1), 1-5, 2008	251	2008
Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting J Sun, H Li, H Fujita, B Fu, W Ai Information Fusion 54, 128-144, 2020	246	2020
Ranking-order case-based reasoning for financial distress prediction H Li, J Sun Knowledge-Based Systems 21 (8), 868-878, 2008	196	2008
Predicting business failure using classification and regression tree: An empirical comparison with popular classical statistical methods and top classification mining methods H Li, J Sun, J Wu Expert Systems with Applications 37 (8), 5895-5904, 2010	194	2010
Financial distress prediction using support vector machines: Ensemble vs individual J Sun, H Li Applied Soft Computing, 2012	182	2012
Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble J Sun, H Fujita, P Chen, H Li Knowledge-Based Systems 120, 4-14, 2017	179	2017
AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies J Sun, M Jia, H Li Expert systems with applications 38 (8), 9305-9312, 2011	144	2011
Listed companies’ financial distress prediction based on weighted majority voting combination of multiple classifiers J Sun, H Li Expert Systems with Applications 35 (3), 818-827, 2008	136	2008
Financial distress early warning based on group decision making J Sun, H Li Computers & operations research 36 (3), 885-906, 2009	135	2009
Predicting business failure using multiple case-based reasoning combined with support vector machine H Li, J Sun Expert Systems with Applications 36 (6), 10085-10096, 2009	129	2009
Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples–Evidence from the Chinese hotel industry H Li, J Sun Tourism Management 33 (3), 622-634, 2012	126	2012
Daily tourism volume forecasting for tourist attractions JW Bi, Y Liu, H Li Annals of Tourism Research 83, 102923, 2020	124	2020
Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction H Li, H Adeli, J Sun, JG Han Computers & Operations Research 38 (2), 409-419, 2011	124	2011
The induced continuous ordered weighted geometric operators and their application in group decision making J Wu, JC Li, H Li, WQ Duan Computers & Industrial Engineering 56 (4), 1545-1552, 2009	124	2009
Gaussian case-based reasoning for business failure prediction with empirical data in China H Li, J Sun Information Sciences 179 (1-2), 89-108, 2009	124	2009
Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors H Li, J Sun, BL Sun Expert Systems with Applications 36 (1), 643-659, 2009	122	2009
To buy or not to buy? The effect of time scarcity and travel experience on tourists' impulse buying C Li, Y Wang, X Lv, H Li Annals of Tourism Research 86, 103083, 2021	86	2021
Majority voting combination of multiple case-based reasoning for financial distress prediction H Li, J Sun Expert Systems with Applications 36 (3), 4363-4373, 2009	86	2009

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