Volume 5, Issue 1, March 2020, Page: 22-28
A Satisfaction Degree Evaluation Model of Knowledge Payment Platform for College Students in Guangzhou City
Qiansheng Zhang, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Yaxian Chen, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Guoming Wu, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Huahong Chen, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Xiaoya Sun, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Huijuan Zang, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, P. R. China
Received: Feb. 25, 2020;       Accepted: Mar. 24, 2020;       Published: Apr. 14, 2020
DOI: 10.11648/j.ajmcm.20200501.14      View  80      Downloads  47
Abstract
With the rapid development of knowledge information and internet technology, a variety of online knowledge paid products and knowledge payment platforms are widely used by college students. The satisfaction evaluation of knowledge payment platform not only helps college students choose a suitable knowledge payment platform, but also helps the knowledge payment platform improve competitiveness and standardization. This paper collects customer satisfaction data by designing questionnaires and conducting customer satisfaction surveys. Using statistical analysis methods such as descriptive statistics, parameter testing and reliability analysis, the customer satisfaction data are analyzed from different dimensions. Based on American customer satisfaction index (ACSI) and the characteristics of knowledge payment, content quality, technical quality, update frequency and advertising marketing quality are extracted as important factors for satisfaction evaluation. Then, a satisfaction evaluation model of knowledge payment platform is constructed to evaluate the satisfaction degree of college students on the knowledge payment platform by employing factor analysis and multivariable regression analysis. The proposed model can predict the development trend of knowledge payment platforms and provide valuable suggestions for the healthy development and the selection of knowledge payment platforms.
Keywords
Knowledge Payment Platform, Customer Satisfaction Index, Satisfaction Degree Model, Factor Analysis, Multivariable Analysis
To cite this article
Qiansheng Zhang, Yaxian Chen, Guoming Wu, Huahong Chen, Xiaoya Sun, Huijuan Zang, A Satisfaction Degree Evaluation Model of Knowledge Payment Platform for College Students in Guangzhou City, American Journal of Mathematical and Computer Modelling. Vol. 5, No. 1, 2020, pp. 22-28. doi: 10.11648/j.ajmcm.20200501.14
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Media Data, The scale and forecast of knowledge paying users in China from 2015 to 2021. https://data.iimedia.cn/page-category.jsp?nodeid=30406609.
[2]
Media Report, 2018-2019 research and business investment decision analysis report on China's knowledge payment industry, 2019, 1, https://www.iimedia.cn/c400/63439.html.
[3]
Zhang Yangyi, Review of Knowledge Payment on Online Platforms [J], Information Research, 2018, 8: 129-134.
[4]
Yang Shuyi, Comparative Analysis of Chinese and Foreign Knowledge Payment Platforms [J], Information Research, 2019, 6: 83-89.
[5]
Ren baijian, Zhang hairong, Li mingjun, Research on the current situation of user behavior of knowledge payment platform [J], Modern business, 2019, 22: 7-8.
[6]
Zhao Yang, Yuan xiani, Li luqi, et al., The Impact Factors of Users' Paying Behavior for Knowledge on Social Q&A Platform Based on Social Capital Theory [J], Library information knowledge, 2018, 4: 15-23.
[7]
Zhao Yang, Zhou Ruoxin, Yang Bin, A 2020 perspective on “How knowledge contributor characteristics and reputation affect user payment decisions in paid Q&A? An empirical analysis from the perspective of trust theory” [J], Electronic Commerce Research and Applications, 2020, 40.
[8]
Cao Lihe, Research on theoretical model and evaluation system of customer satisfaction [J], Journal of Hubei University of Economics, 2007, 1: 115-119.
[9]
Claes Fornell, Liu jinlan, Kang jian, Bai Yin, American Customer Satisfaction Index [J], Chinese journal of management, 2005, 4: 495-504.
[10]
Vinit Dani, Measuring Customer Satisfaction for F&B Chains in Pune Using ACSI Model [J], Procedia-Social and Behavioral Sciences, 2014, 133: 466-467.
[11]
Song Qinqin, A study on Mooc Learners' Satisfaction in Public Art Education in Colleges and Universities [D], Nanjing University of Posts and Telecommunications, 2019: 9-39.
[12]
Iman Dianat, Pari Adeli, Mohammad Asgari Jafarabadi, Mohammad Ali Karimi, User-centred web design, usability and user satisfaction: The case of online banking websites in Iran [J], Applied Ergonomics, 2019, 81: 2-3.
[13]
She Shihong, Wang Yuting, Empirical research on the correlation between online advertising and online consumption [J], Modern Communication (Journal of Communication University of China), 2008, 40 (10): 135-138.
[14]
Xu Lizhi, Research on the factors affecting the willingness of Zhihu App users to pay [J], Journal of Yanan University, 2019, 38 (03): 23-28.
[15]
Araceli Picón-Berjoyo, Carolina Ruiz-Moreno, Ignacio Castro, A mediating and multigroup analysis of customer loyalty [J], European Management Journal, 2016, 34 (6): 702-703.
[16]
Wang Maobin, Empirical study on the influencing factors of consumers' willingness to purchase knowledge paid products [D], Shandong University, 2018: 19-20.
[17]
Davis, F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 1989, 13, 319-340.
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