Open Access
Issue
E3S Web of Conf.
Volume 469, 2023
The International Conference on Energy and Green Computing (ICEGC’2023)
Article Number 00026
Number of page(s) 17
DOI https://doi.org/10.1051/e3sconf/202346900026
Published online 20 December 2023
  1. M. Jaller, A. Pahwa, Evaluating the environmental impacts of online shopping: A behavioral and transportation approach, Transportation Research Part D: Transport and Environment. 80 (2020) 102223. https://doi.org/10.1016/j.trd.2020.102223. [CrossRef] [Google Scholar]
  2. A. Seghezzi, R. Mangiaracina, A. Tumino, A. Perego, ‘Pony express’ crowdsourcing logistics for last-mile delivery in B2C e-commerce: an economic analysis, International Journal of Logistics Research and Applications. 24 (2021) 456–472. https://doi.org/10.1080/13675567.2020.1766428. [CrossRef] [Google Scholar]
  3. M. Li, J. Weng, A. Yang, W. Lu, Y. Zhang, L. Hou, J.-N. Liu, Y. Xiang, R.H. Deng, CrowdBC: A Blockchain-Based Decentralized Framework for Crowdsourcing, IEEE Transactions on Parallel and Distributed Systems. 30 (2019) 1251–1266. https://doi.org/10.1109/TPDS.2018.2881735. [Google Scholar]
  4. K. Zhang, J.J. Escribano Macias, D. Paccagnan, P. Angeloudis, The Competition and Inefficiency in Urban Road Last-Mile Delivery, in: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 2022: pp. 1473–1481. [Google Scholar]
  5. E. Pourrahmani, M. Jaller, Crowdshipping in last mile deliveries: Operational challenges and research opportunities, Socio-Economic Planning Sciences. 78 (2021) 101063. https://doi.org/10.1016/j.seps.2021.101063. [CrossRef] [Google Scholar]
  6. A. Zutshi, A. Grilo, T. Nodehi, The value proposition of blockchain technologies and its impact on Digital Platforms, Computers & Industrial Engineering. 155 (2021) 107187. https://doi.org/10.1016/j.cie.2021.107187. [CrossRef] [Google Scholar]
  7. H.R. Hasan, K. Salah, Proof of Delivery of Digital Assets Using Blockchain and Smart Contracts, IEEE Access. 6 (2018) 65439–65448. https://doi.org/10.1109/ACCESS.2018.2876971. [CrossRef] [Google Scholar]
  8. V. Carbone, A. Rouquet, C. Roussat, The Rise of Crowd Logistics: A New Way to Co-Create Logistics Value, Journal of Business Logistics. 38 (2017) 238–252. https://doi.org/10.1111/jbl.12164. [CrossRef] [Google Scholar]
  9. G. Ciobotaru, S. Chankov, Towards a taxonomy of crowdsourced delivery business models, International Journal of Physical Distribution & Logistics Management. 51 (2021) 460–485. https://doi.org/10.1108/IJPDLM-10-2019-0326. [CrossRef] [Google Scholar]
  10. R. Mangiaracina, A. Perego, A. Seghezzi, A. Tumino, Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review, International Journal of Physical Distribution & Logistics Management. 49 (2019) 901–920. https://doi.org/10.1108/IJPDLM-02-2019-0048. [CrossRef] [Google Scholar]
  11. V.E. Castillo, J.E. Bell, W.J. Rose, A.M. Rodrigues, Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions, Journal of Business Logistics. 39 (2018) 7–25. https://doi.org/10.1111/jbl.12173. [CrossRef] [Google Scholar]
  12. M.D. Simoni, E. Marcucci, V. Gatta, C.G. Claudel, Potential last-mile impacts of crowdshipping services: a simulation-based evaluation, Transportation. 47 (2020) 1933– 1954. https://doi.org/10.1007/s11116-019-10028-4. [CrossRef] [Google Scholar]
  13. Y. Wang, D. Zhang, Q. Liu, F. Shen, L.H. Lee, Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions, Transportation Research Part E: Logistics and Transportation Review. 93 (2016) 279–293. https://doi.org/10.1016/j.tre.2016.06.002. [CrossRef] [Google Scholar]
  14. A. Sampaio, M. Savelsbergh, L.P. Veelenturf, T. Van Woensel, Delivery systems with crowd-sourced drivers: A pickup and delivery problem with transfers, Networks. 76 (2020) 232–255. https://doi.org/10.1002/net.21963. [CrossRef] [Google Scholar]
  15. A.G. Naclerio, P. De Giovanni, Blockchain, logistics and omnichannel for last mile and performance, The International Journal of Logistics Management. 33 (2022) 663–686. https://doi.org/10.1108/IJLM-08-2021-0415. [CrossRef] [Google Scholar]
  16. Y. Gong, S. van Engelenburg, M. Janssen, A Reference Architecture for Blockchain-Based Crowdsourcing Platforms, Journal of Theoretical and Applied Electronic Commerce Research. 16 (2021) 937–958. https://doi.org/10.3390/jtaer16040053. [CrossRef] [Google Scholar]
  17. K. Navendan, H. Wicaksono, O. Fatahi Valilai, Enhancement of Crowd Logistics Model in an E-Commerce Scenario Using Blockchain-Based Decentralized Application, in: M. Freitag, A. Kinra, H. Kotzab, N. Megow (Eds.), Dynamics in Logistics, Springer International Publishing, Cham, 2022: pp. 26–37. https://doi.org/10.1007/978-3-031-05359-7_3. [CrossRef] [Google Scholar]
  18. S.E. Moudaa, Y. Ibrahim, M. Kadadha, R. Mizouni, H. Otrok, S. Singh, PackChain: Toward a Blockchain-based Management Platform for Last-mile Delivery, in: 2022 International Wireless Communications and Mobile Computing (IWCMC), 2022: pp. 919–924. https://doi.org/10.1109/IWCMC55113.2022.9825043. [Google Scholar]
  19. ERC-721: Non-Fungible Token Standard, Ethereum Improvement Proposals. (n.d.). https://eips.ethereum.org/EIPS/eip-721 (accessed July 21, 2023). [Google Scholar]
  20. H. Buldeo Rai, S. Verlinde, C. Macharis, Who is interested in a crowdsourced last mile? A segmentation of attitudinal profiles, Travel Behaviour and Society. 22 (2021) 22–31. https://doi.org/10.1016/j.tbs.2020.08.004. [CrossRef] [Google Scholar]
  21. H.G. Lee, T.H. Clark, Impacts of the Electronic Marketplace on Transaction Cost and Market Structure, International Journal of Electronic Commerce. 1 (1996) 127–149. https://doi.org/10.1080/10864415.1996.11518279. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.