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Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform

Received: 16 November 2022     Accepted: 1 December 2022     Published: 8 December 2022
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Abstract

With the Internet and logistics transportation developing rapidly and the popularization of devices like smartphones, online shopping has become an ordinary issue for each of us. No matter what product is needed, such as a refrigerator or just a spoon, could be available as long as we search in the website or application of the e-commerce platform, fill out an address and then pay for the product. While browsing in the e-commerce platform for the goods wanted, it is just as though we are in a large market which involves kinds of products. Consumers need to find what they want. The retailers and the e-commerce platform also need to reach for more potential customers and get more orders more efficiently. This is the reason for the adoption of recommendation algorithms. Although recommendation algorithms have somewhat achieved these in practice, there are still a few problems. This paper mainly described the application status of the intelligent recommendation algorithm of the E-commerce platform and how the cocoon room came into being in such a situation. Then there was an analysis of the cocoon room of the intelligent recommendation algorithm, making consumers feel bored or regret after purchasing and consequently harming the interests of the retailers and the platform itself. Subsequently, solutions to the two kinds of negative moods were proposed. The last is the summary, meaning in practice, and extended study direction of this analysis.

Published in American Journal of Applied Psychology (Volume 11, Issue 6)
DOI 10.11648/j.ajap.20221106.14
Page(s) 167-171
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

E-commerce Platform, Recommendation Algorithm, Cocoon Room, Negativte Moods

References
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[3] Liu. J. L, Li. X. G. (2020) Techniques for Recommendation system: A Survey. J. Computer Science, 47 (7): 47-55.
[4] Byeong Man Kim et al. (2006). A new approach for combining content-based and collaborative filters. J. Intell. Inf. Syst., 27 (1): 79-91.
[5] Kim, BD., Kim, SO. (2001). A new recommender system to combine content-based and collaborative filtering systems. J. Database Mark Cust Strategy Manag 8, 244–252.
[6] Prem Melville, Raymond J. Mooney, Ramadass Nagarajan. (2002). Content-Boosted Collaborative Filtering for Improved Recommendations. J. American Association for Artificial Intelligence, 23: 187-192.
[7] Balabanovic, M., Shoham, Y. (1997). Fab: Content-based, collaborative recommendation. J. Communications of the ACM 40 (3), 66–72.
[8] Menon, S., & Kahn, B. E. (1995). The Impact of Context on Variety Seeking in Product Choices. Journal of Consumer Research, 22 (3), 285.
[9] Zeelenberg, M., Beattie, J., Pligt, J. V. and Vries, N. K. (1996). Consequences of Regret Aversion: Effects of Expected Feedback on Risky Decision Making. J. Organizational Behavior and Human Decision Processes, 65 (2): 148-158.
[10] Zeelenberg, M., van Dijk, W. W., Manstead, A. S. R., and van der Pligt. (1998). The experience of regret and disappointment. J. Cognition and Emotion, 12, 221–230.
[11] Venkatesan, R. and Kumar, V. (2004). A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy. J. Journal of Marketing, 68 (4): 106-125.
[12] Zhu. G. W, Gao. W. L, liu. J. H, li. S. F and Lu. J. F. (2021). Artificial Intelligence Marketing: A Research Review and Prospect. J. Foreign Economics & Management., 43 (07): 86-96.
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[14] Li. X. Q and Zhang. X. X. (2020). People-oriented: Personalized Recommendations in the Era of Artificial Intelligence. J. Journal of Shanghai University of International Business and Economics. 27 (04): 90-99.
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Cite This Article
  • APA Style

    Jingjing Huang. (2022). Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform. American Journal of Applied Psychology, 11(6), 167-171. https://doi.org/10.11648/j.ajap.20221106.14

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    ACS Style

    Jingjing Huang. Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform. Am. J. Appl. Psychol. 2022, 11(6), 167-171. doi: 10.11648/j.ajap.20221106.14

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    AMA Style

    Jingjing Huang. Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform. Am J Appl Psychol. 2022;11(6):167-171. doi: 10.11648/j.ajap.20221106.14

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  • @article{10.11648/j.ajap.20221106.14,
      author = {Jingjing Huang},
      title = {Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform},
      journal = {American Journal of Applied Psychology},
      volume = {11},
      number = {6},
      pages = {167-171},
      doi = {10.11648/j.ajap.20221106.14},
      url = {https://doi.org/10.11648/j.ajap.20221106.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20221106.14},
      abstract = {With the Internet and logistics transportation developing rapidly and the popularization of devices like smartphones, online shopping has become an ordinary issue for each of us. No matter what product is needed, such as a refrigerator or just a spoon, could be available as long as we search in the website or application of the e-commerce platform, fill out an address and then pay for the product. While browsing in the e-commerce platform for the goods wanted, it is just as though we are in a large market which involves kinds of products. Consumers need to find what they want. The retailers and the e-commerce platform also need to reach for more potential customers and get more orders more efficiently. This is the reason for the adoption of recommendation algorithms. Although recommendation algorithms have somewhat achieved these in practice, there are still a few problems. This paper mainly described the application status of the intelligent recommendation algorithm of the E-commerce platform and how the cocoon room came into being in such a situation. Then there was an analysis of the cocoon room of the intelligent recommendation algorithm, making consumers feel bored or regret after purchasing and consequently harming the interests of the retailers and the platform itself. Subsequently, solutions to the two kinds of negative moods were proposed. The last is the summary, meaning in practice, and extended study direction of this analysis.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Influences and Solutions of the Cocoon Room Caused by the Intelligent Recommendation Algorithm of the E-commerce Platform
    AU  - Jingjing Huang
    Y1  - 2022/12/08
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    N1  - https://doi.org/10.11648/j.ajap.20221106.14
    DO  - 10.11648/j.ajap.20221106.14
    T2  - American Journal of Applied Psychology
    JF  - American Journal of Applied Psychology
    JO  - American Journal of Applied Psychology
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    EP  - 171
    PB  - Science Publishing Group
    SN  - 2328-5672
    UR  - https://doi.org/10.11648/j.ajap.20221106.14
    AB  - With the Internet and logistics transportation developing rapidly and the popularization of devices like smartphones, online shopping has become an ordinary issue for each of us. No matter what product is needed, such as a refrigerator or just a spoon, could be available as long as we search in the website or application of the e-commerce platform, fill out an address and then pay for the product. While browsing in the e-commerce platform for the goods wanted, it is just as though we are in a large market which involves kinds of products. Consumers need to find what they want. The retailers and the e-commerce platform also need to reach for more potential customers and get more orders more efficiently. This is the reason for the adoption of recommendation algorithms. Although recommendation algorithms have somewhat achieved these in practice, there are still a few problems. This paper mainly described the application status of the intelligent recommendation algorithm of the E-commerce platform and how the cocoon room came into being in such a situation. Then there was an analysis of the cocoon room of the intelligent recommendation algorithm, making consumers feel bored or regret after purchasing and consequently harming the interests of the retailers and the platform itself. Subsequently, solutions to the two kinds of negative moods were proposed. The last is the summary, meaning in practice, and extended study direction of this analysis.
    VL  - 11
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    ER  - 

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Author Information
  • School of Business Administration, Guizhou University of Finance and Economics, Guiyang, China

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