COMBINING WEB MINING AND APPLICATION OF STRUCTURAL EQUATION MODELING IN E-COMMERCE
Abstract
The aim of this study is to develop a solution to collect product information from multiple websites, and then investigate the relationships of various factors that affect customer satisfaction on a product using Structural Equation Modeling (SEM), so that the system can suggest best products which are suitable for customer demands. These relationships were tested using a sample of 100 laptop shoppers from 4 popular electronic stores in HCM city. The result indicates that the satisfaction of customers with a product depends on some important factors such as product configuration, warranty time, post-sale service… which related to both product quality and service quality in general. All the steps involved in evaluating the coefficients of evaluation model are accomplished with the assistance of Statistical Package for the Social Sciences (SPSS), software used for statistical analysis. Implications for store managers and directions for future researches are also discussed.References
[1] Kenny, D. A. and Milan, S. Identification: A non-technical discussion of a technical issue. In Handbook of Structural Equation Modeling (R. Hoyle, ed.). Guilford Press, New York, 2012.
[2] Williams, L. J. Equivalent models: Concepts, problems, alternatives. In Handbook of Structural Equation Modeling (R. Hoyle, ed.). Guilford Press, New York, 2011.
[3] Temme D, Kreis H, Hildebrandt L. A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance, Chapter 31. Springer-Verlag, Berlin, 2010.
[4] Lee, S.-Y., & Song, X.-Y. Maximum likelihood analysis of a general latent ariable model with hierarchically mixed data. Biometrics, 2005, pp 624–636.
[5] Chen, Z., & Dubinsky, A. J. A Conceptual Model of Perceived Customer Value in E-Commerce: A preliminary Investigation. Psychology & Marketing, 20(4), 2004, pp 323-347.
[6] Kwon, O. B., Kim, C., & Lee, E. J. Impact of website information design factors on consumer ratings of web-based auction sites. Behaviour & Information Technology, 21(6), 2002, pp 387-402.
[7] Gefen, D., Straub, D. W., & Boudreau, M. Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4(7), 2002, pp 1-79.
[2] Williams, L. J. Equivalent models: Concepts, problems, alternatives. In Handbook of Structural Equation Modeling (R. Hoyle, ed.). Guilford Press, New York, 2011.
[3] Temme D, Kreis H, Hildebrandt L. A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance, Chapter 31. Springer-Verlag, Berlin, 2010.
[4] Lee, S.-Y., & Song, X.-Y. Maximum likelihood analysis of a general latent ariable model with hierarchically mixed data. Biometrics, 2005, pp 624–636.
[5] Chen, Z., & Dubinsky, A. J. A Conceptual Model of Perceived Customer Value in E-Commerce: A preliminary Investigation. Psychology & Marketing, 20(4), 2004, pp 323-347.
[6] Kwon, O. B., Kim, C., & Lee, E. J. Impact of website information design factors on consumer ratings of web-based auction sites. Behaviour & Information Technology, 21(6), 2002, pp 387-402.
[7] Gefen, D., Straub, D. W., & Boudreau, M. Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4(7), 2002, pp 1-79.
Published
2014-12-17
How to Cite
THUÂN, Nguyễn Đình; ANH, Nguyễn Tuấn; TÙNG, Phan An.
COMBINING WEB MINING AND APPLICATION OF STRUCTURAL EQUATION MODELING IN E-COMMERCE.
JBIS, [S.l.], dec. 2014.
Available at: <https://jbis.ueh.edu.vn/index.php/TSTHQL/article/view/42>. Date accessed: 19 may 2024.
Issue
Section
Bài viết
Keywords
Wed Mining; E-commerce; SEM
