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Consumer Satisfaction Based on Online Reviews of Fresh Food E-commerce Platforms: Take YuanShengXian Store As an Example
Research Article | Published: 9 January 2024
IECE Transactions on Social Statistics and Computing Volume 1, Issue 1, 2024: 19-25
Volume 1, Issue 1, IECE Transactions on Social Statistics and Computing
Volume 1, Issue 1, 2024
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Guojie Xie
Guojie Xie
Guangzhou University,China
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IECE Transactions on Social Statistics and Computing, Volume 1, Issue 1, 2024: 19-25

Free to Read | Research Article | 9 January 2024
Consumer Satisfaction Based on Online Reviews of Fresh Food E-commerce Platforms: Take YuanShengXian Store As an Example
by
Jiayu Pan Jiayu Pan 1 *
1 School of Digital Economic and Management, Software Engineering Institute of Guangzhou, Guangzhou 510000, China
* Corresponding Author: Jiayu Pan, [email protected]
DOI: 10.62762/TSSC.2024.433223
Received: 31 December 2024, Accepted: 8 January 2024, Published: 9 January 2024  
Cited by: 1  (Source: Web of Science) , 1  (Source: Google Scholar)
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Abstract
Online reviews are a vital tool for both businesses and customers to understand each other's requirements and to learn about the features and quality of products. This paper uses word frequency statistics and semantic network analysis to analyze the factors affecting consumer satisfaction into five categories: service, quality, logistics, packaging, and price. The research object is text reviews of various products from YuanShengXian's flagship store. The analysis yields a consumer sentiment evaluation for each influencing factor. The theoretical framework of the new e-commerce satisfaction assessment is further enhanced and improved by this study, which also serves as a guide for the enterprise's development plan and improvement strategy.
Graphical Abstract
Consumer Satisfaction Based on Online Reviews of Fresh Food E-commerce Platforms: Take YuanShengXian Store As an Example
Keywords
Yuanshengxian Store
Fresh Food E-commerce
Online reviews
Consumer satisfaction
References
  1. Aimei Consulting. 2022 china fresh food e-commerce operation big data and development prospect research report. https://www.iimedia.cn/c400/84894.html
    [Google Scholar]
  2. Su, X. (2012). Research on factors influencing the usefulness of b2c online reviews–taking amazon.com as an example. Hubei: Zhongnan University for Nationalities.
    [Google Scholar]
  3. Lei, H. (2017). Extraction of product attributes and visual representation of their emotions based on product reviews of e-commerce websites. Beijing University of Posts and Telecommunications.
    [Google Scholar]
  4. Guoxianda, N., Gao, H., & Yang, X. (2020). Research on online review topic mining based on gaussian lda. Journal of Intelligence, 39(6), 630–639.
    [Google Scholar]
  5. Zheng, L., & Wang, H. (2017). Emotional polarity and intensity analysis of online reviews based on emotional ontology:taking cell phone as an example. Journal of Management Engineering, 31(2), 47–54.
    [Google Scholar]
  6. Maharani, W., Widyantoro, D. H., & Khodra, M. L. (2022). Dynamic aspect-based rating system and visualization. User Modeling and User-Adapted Interaction, 32(1-2), 1–24.
    [Google Scholar]
  7. Hatzivassiloglou, V., & McKeown, K. R. (1997). Predicting the semantic orientation of adjectives. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics (pp. 174–181). Madrid, Spain: Morgan Kaufmann Publishers / ACL.
    [Google Scholar]
  8. Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: findings from an internet social networking site. Journal of Marketing, 73(5), 90–102.
    [Google Scholar]
  9. Zhang, W. (2015). A review of domestic research on customer satisfaction-analysis based on china knowledge network literature from 2000-2014. Research on Business Economy (31), 66–68.
    [Google Scholar]
  10. Li, B., & Cheng, L. (2013). Study on vehicle scheduling problem based on customer satisfaction. Logistics Technology, 32(23), 253–254+272.
    [Google Scholar]
  11. Wang, Y., & Zeng, F. (2004). Customer satisfaction measurement based on entropy value method. Business Research (22), 11–13.
    [Google Scholar]
  12. Pei, F., Tang, W., & Kuitong, H. (2006). A review of customer satisfaction research and application. World Standardization and Quality Management (10), 4–7.
    [Google Scholar]
  13. Xu, Z., & Wei, B. (2001). Empirical analysis of customer satisfaction index in the united states. World Standardization and Quality Management (10), 16–17.
    [Google Scholar]
  14. Hill, N., & Alexander, J. (2017). The handbook of customer satisfaction and loyalty measurement. Routledge.
    [Google Scholar]
  15. Wang, X., Wang, N., Song, W., Wang, M., & Zhang, M. (2022). Research on factors influencing consumer satisfaction and countermeasures in fresh food e-commerce. Investment and Entrepreneurship, 33(18), 124–126.
    [Google Scholar]
  16. Liu, G. (2022). The status quo and trend of fresh food e-commerce development in the context of new retail. China Market (18), 169–171.
    [Google Scholar]
Cite This Article
APA Style
Pan, J. (2024). Consumer Satisfaction Based on Online Reviewsof Fresh Food E-commerce Platforms: Take YuanShengXian Store As an Example. IECE Transactions on Social Statistics andComputing, 1(1), 19–25. https://doi.org/10.62762/TSSC.2024.433223
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