M
Mu-Chen Chen
Researcher at National Chiao Tung University
Publications - 101
Citations - 6310
Mu-Chen Chen is an academic researcher from National Chiao Tung University. The author has contributed to research in topics: Supply chain & Service (business). The author has an hindex of 40, co-authored 98 publications receiving 5342 citations. Previous affiliations of Mu-Chen Chen include National Taipei University of Technology.
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Journal ArticleDOI
Credit scoring with a data mining approach based on support vector machines
TL;DR: Experimental results show that SVM is a promising addition to the existing data mining methods and three strategies to construct the hybrid SVM-based credit scoring models are used.
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Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks
Yu Wei,Mu-Chen Chen +1 more
TL;DR: In this article, a hybrid EMD-BPN forecasting approach which combines empirical mode decomposition (EMD) and back-propagation neural networks (BPN) is developed to predict the short-term passenger flow in metro systems.
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The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators
TL;DR: It is found that the service quality is more important than information and system quality in influencing customer satisfaction and purchase intention and the relationship between perceived playfulness and perceived flow is reciprocal.
Journal ArticleDOI
Credit scoring and rejected instances reassigning through evolutionary computation techniques
Mu-Chen Chen,Shih Hsien Huang +1 more
TL;DR: From the computational results, NNs have emerged as a computational tool that is well-matched to the problem of credit classification, and creditors can suggest the conditional acceptance, and further explain the conditions to rejected applicants.
Journal ArticleDOI
Mining changes in customer behavior in retail marketing
TL;DR: This study integrates customer behavioral variables, demographic variables, and transaction database to establish a method of mining changes in customer behavior that can assist managers in developing better marketing strategies.