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Exploring the interaction and choice behavior of organization and individuals in the crowd logistics

Author

Listed:
  • Yuwei Yan

    (Taishan University)

  • Xiaomeng Ma

    (Shenzhen University)

  • Yi Song

    (Center for Assessment and Development Research of Real Estate)

  • Ajay Kumar

    (AIM Research Center On Artificial Intelligence in Value Creation, EMLYON Business School)

  • Ruixian Yang

    (Zhengzhou University)

Abstract

With the increasingly wide use of sensor-embedded smartphones, we envision that there will be many crowdsourced logistic companies to acquire logistics service from a large population of carriers. They form a two-side competition market, where crowdsources compete for the limited logistics service and carriers compete for the compensation from crowdsourced logistic company. Each crowdsourced logistic company has to select an “optimal” delivery compensation that can attract enough service providers. Each carrier has to decide which crowdsourced logistic company to join in, while a congested company may resulted in a low reward. In this paper, we present a game theoretic study of such a two-side competition market. To be more practical, we consider the bounded rationality of service providers. We formulate the dynamics behavior of service providers as an evolutionary game, and take two key factors (company’s analytics ability and service providers’ evaluation) under smart environment in our model, and then present a simulation model for the implementation of evolution process. Through this work, we can understand the dynamic evolution of the medium-sized crowd logistics market under smart environment and crowdsourced logistic company can adjust their strategy to optimal their profit.

Suggested Citation

  • Yuwei Yan & Xiaomeng Ma & Yi Song & Ajay Kumar & Ruixian Yang, 2023. "Exploring the interaction and choice behavior of organization and individuals in the crowd logistics," Annals of Operations Research, Springer, vol. 320(2), pages 1021-1040, January.
    • Handle: RePEc:spr:annopr:v:320:y:2023:i:2:d:10.1007_s10479-021-04070-8
    DOI: 10.1007/s10479-021-04070-8
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    References listed on IDEAS

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    1. Devari, Aashwinikumar & Nikolaev, Alexander G. & He, Qing, 2017. "Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 105-122.
    2. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2021. "Crowdsourced delivery: A review of platforms and academic literature," Omega, Elsevier, vol. 98(C).
    3. Bach, Christian W. & Perea, Andrés, 2020. "Generalized Nash equilibrium without common belief in rationality," Economics Letters, Elsevier, vol. 186(C).
    4. Zhiyuan Yu & Muhammad Hafeez & Lihan Liu & Muhammad Tariq Mahmood & Hong Wu, 2019. "Evaluating the Minor Coarse Cereals Product Crowdfunding Platform through Evolutionary Game Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    5. Ionica Oncioiu & Ovidiu Constantin Bunget & Mirela Cătălina Türkeș & Sorinel Căpușneanu & Dan Ioan Topor & Attila Szora Tamaș & Ileana-Sorina Rakoș & Mihaela Ștefan Hint, 2019. "The Impact of Big Data Analytics on Company Performance in Supply Chain Management," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
    6. Bashari, Masoud & Akbarzadeh-T, Mohammad-R., 2020. "Controlling opinions in Deffuant model by reconfiguring the network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    7. Chongyi Zhong & Hui Yang & Zixin Liu & Juanyong Wu, 2020. "Stability of Replicator Dynamics with Bounded Continuously Distributed Time Delay," Mathematics, MDPI, vol. 8(3), pages 1-12, March.
    8. Yi Song & Bin Hu & Zhihan Lv, 2018. "A computational analysis of capital chain rupture in e-commerce enterprise," Electronic Commerce Research, Springer, vol. 18(2), pages 257-276, June.
    9. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
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