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Time Evolution Analysis of Riders’ Preference Attention and Satisfaction on Real-Time Crowdsourcing Logistics Platform

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  • Yi Zhang
  • Dan Li
  • Shengren Liu

Abstract

This study examines the evolutionary trends in preference focus and satisfaction among real-time crowdsourced logistics platform riders (hereafter referred to as riders) in China since the outbreak of the COVID-19 pandemic. By analyzing real-time comments from 5,652 riders and applying the Latent Dirichlet Allocation (LDA) model to identify riders’ preferences and calculate their attention levels, combined with riders’ actual ratings to infer satisfaction levels (ranging from very dissatisfied to satisfied), this research for the first time explores the changing patterns of riders’ preferences and their attention and satisfaction trends in the pandemic context from a long-term dynamic perspective. The findings reveal that riders prioritize interaction quality; the range of fluctuation in average attention levels is large when high and small when low; attention to platform management, system utility, and rider relationships is on the rise, whereas interest in other preferences is declining; there is a significant correlation between rider attention and platform policies; and social media and related public opinion influence riders’ preferences. These insights are instrumental for the platform to adjust the policy direction duly and meet the core demands of riders according to the limited priority.

Suggested Citation

  • Yi Zhang & Dan Li & Shengren Liu, 2024. "Time Evolution Analysis of Riders’ Preference Attention and Satisfaction on Real-Time Crowdsourcing Logistics Platform," SAGE Open, , vol. 14(3), pages 21582440241, August.
    • Handle: RePEc:sae:sagope:v:14:y:2024:i:3:p:21582440241271145
    DOI: 10.1177/21582440241271145
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    1. Ihsan Ullah & Muhammad Khan & Dilshodjon Alidjonovich Rakhmonov & Kalonov Mukhiddin Bakhritdinovich & Julija Jacquemod & Junghan Bae, 2023. "Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises," Logistics, MDPI, vol. 7(3), pages 1-22, July.
    2. Muhammad Khan & Gohar Saleem Parvaiz & Alisher Tohirovich Dedahanov & Odiljon Sobirovich Abdurazzakov & Dilshodjon Alidjonovich Rakhmonov, 2022. "The Impact of Technologies of Traceability and Transparency in Supply Chains," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    3. Diya Li & Harshita Chaudhary & Zhe Zhang, 2020. "Modeling Spatiotemporal Pattern of Depressive Symptoms Caused by COVID-19 Using Social Media Data Mining," IJERPH, MDPI, vol. 17(14), pages 1-23, July.
    4. Friedland, Julian & Balkin, David B., 2023. "When gig workers become essential: Leveraging customer moral self-awareness beyond COVID-19," Business Horizons, Elsevier, vol. 66(2), pages 181-190.
    5. Wang, Yuanyuan & Chi, Yuanying & Xu, Jin-Hua & Yuan, Yongke, 2022. "Consumers’ attitudes and their effects on electric vehicle sales and charging infrastructure construction: An empirical study in China," Energy Policy, Elsevier, vol. 165(C).
    6. Chen, Mu-Chen & Hsu, Chia-Lin & Huang, Chun-Han, 2021. "Applying the Kano model to investigate the quality of transportation services at mega events," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
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