The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Smart logistics based on the internet of things technology: an overview
Open accessAbstract
Smart logistics is an effective way to meet the challenges of fast-changing customer expectations, take opportunities brought by new technologies, and facilitate new business models. This review paper systematically summarises the recent research and applications of smart logistics based on the internet of things (IoT), including smart freight transportation, warehousing, and delivery. A bibliometric analysis based on publications between 2008 and 2019 reveals main technologies and impacts of the research and applications of IoT-based smart logistics and their industrial and geographic distributions. The content analysis demonstrates the role and impact of IoT on smart logistics, reveals challenges of IoT-based smart logistics, and provides research needs for the development of smart logistics. The current challenges include technical problems of radio frequency identification and wireless sensor networks, limited extension and technical capacity of IoT,standardisation issues of IoT, data acquisition and processing issues of IoT, and security and privacy concerns on IoT. There is a strong research need to address the key technical issues of IoT, promote various IoT technologies in logistics practice, and jointly develop advanced information and communications technologies and management systems.
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Cites
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Metadata
- Authors
- Ding, Y., Jin, M., Li, S., & Feng, D.
- Venue
- International Journal of Logistics Research and Applications
- Publisher
- Informa UK Limited
- Published
- 2020-04-24
- Volume
- 24
- Issue
- 4
- Pages
- 323-345
- ISSN
- 1367-5567 (ISSN-L)
- 1469-848X
- OpenAlex
- W3019570724
- Cited by
- 398
- References
- 77
- FWCI
- 28.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Ding, Y., Jin, M., Li, S., & Feng, D. (2021). Smart logistics based on the internet of things technology: an overview. International Journal of Logistics Research and Applications. https://doi.org/10.1080/13675567.2020.1757053
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
