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Bibliometric analysis of sharing economy logistics and crowd logistics

Author

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  • Laurence Saglietto

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

Abstract

Purpose This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options? Design/methodology/approach Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field. Findings The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment. Research limitations/implications The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc. Originality/value Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

Suggested Citation

  • Laurence Saglietto, 2021. "Bibliometric analysis of sharing economy logistics and crowd logistics," Post-Print halshs-03562657, HAL.
    • Handle: RePEc:hal:journl:halshs-03562657
    DOI: 10.1108/IJCS-07-2020-0014
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03562657
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    References listed on IDEAS

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    1. Bruno Durand & Hakim Akeb & Btissam Moncef, 2018. "Building a collaborative solution in dense urban city settings to enhance parcel delivery: An effective crowd model in Paris [L'élaboration d'une solution collaborative de livraisons urbaines en vu," Post-Print hal-01781155, HAL.
    2. Scavarda, Manuel & Seok, Hyesung & Puranik, Anurag S. & Nof, Shimon Y., 2015. "Adaptive direct/indirect delivery decision protocol by collaborative negotiation among manufacturers, distributors, and retailers," International Journal of Production Economics, Elsevier, vol. 167(C), pages 232-245.
    3. Robert J. David & Shin‐Kap Han, 2004. "A systematic assessment of the empirical support for transaction cost economics," Strategic Management Journal, Wiley Blackwell, vol. 25(1), pages 39-58, January.
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    Cited by:

    1. Joash Mageto, 2022. "Current and Future Trends of Information Technology and Sustainability in Logistics Outsourcing," Sustainability, MDPI, vol. 14(13), pages 1-27, June.

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