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http://dx.doi.org/10.9708/jksci.2016.21.11.127

Analysis of Success Factors for Mobile Commerce using Text Mining and PLS Regression  

Kim, Yong-Hwan (Dept. of Software Analysis and Design, SeoulTech)
Kim, Ja-Hee (Graduate School of Public and Information Technology, SeoulTech)
Park, Ji hoon (Isu Petasys Co.)
Lee, Seung-Jun (Dept. of Global Convergence of Industrial Engineering, SeoulTech)
Publication Information
Journal of the Korea Society of Computer and Information / v.21, no.11, 2016 , pp. 127-134 More about this Journal
Abstract
In this paper, we propose factors that influence on the mobile commerce satisfaction conducted by data mining and a PLS regression analysis. We extracted the most frequent words from mobile application reviews in which there are a large number of user's requests. We employed the content analysis to condense the large number of texts. We took a survey with the categories by which data are condensed and specified as factors that influence on the mobile commerce satisfaction. To avoid multicollinearity, we employed a PLS regression analysis instead of using a multiple regression analysis. Discovered factors that are potential consequences of customer satisfaction from direct requests by customers, the result may be an appropriate indicator for the mobile commerce market to improve its services.
Keywords
Content Analysis; Data Minning; PLS Regression Analysis; Mobile Commerce;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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