User Experience Improvement Design of Shopping Mall Based on Crowd Classification Research

  • Chufan Jin
  • Jiamin Jiang
  • Dian Zhu
  • Xi Chen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 972)


With the rising of the e-commerce, consumers nowadays prefer to shop online out of its efficiency, flexibility and abundance of choice. That is to say, hundreds of traditional offline shopping malls are now going through the imperative urgency of transformation. This paper uses a variety of research methods and classifies the people in the malls based on their needs. Secondly, this paper proposes several design strategies for different groups, meanwhile summarizes the effective ways of user experience improvements. In general, this research is dedicated to suggesting mighty directions for the transformation of offline shopping malls.


User experience Shopping mall design Crowd classification research 


  1. 1.
    Norman, D.: User-Centered System Design: New Perspectives on Human-Computer Interaction. Hillsdale, NewJersey (1986)CrossRefGoogle Scholar
  2. 2.
    Forlizzi, J., Ford, S.: The building blocks of experience: an early framework for interaction designers. In: Proceedings of the 2000 Conference on Designing Interactive Systems, New York, pp. 419–423 (2000)Google Scholar
  3. 3.
    Garrett, J.J.: Elements of User Experience. Mechanical Industry Press, Beijing (2007)Google Scholar
  4. 4.
    Li, C.: 76 Experience Points for User Experience (2007). www.reacet.eom
  5. 5.
    Spool, J.M., et al.: Website Usability: A Designer Guide, User Interface Engineering, NorthAndover, USA (1997)Google Scholar
  6. 6.
    Rubinoff, R.: How to quantify the user experience. http://www.sitepoint.corn/article/quantify-user-experience/. Accessed 21 May 2004
  7. 7.
    Linong, D.: Design and Research. Publishing House of Electronics Industry, Beijing (2016)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Chufan Jin
    • 1
  • Jiamin Jiang
    • 1
  • Dian Zhu
    • 1
  • Xi Chen
    • 1
  1. 1.ShanghaiPeople’s Republic of China

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