Navigating Challenges in Crowdsourced Delivery: A Global Narrative Review
DOI:
https://doi.org/10.61978/logistica.v2i1.1095Keywords:
Crowdsourced Delivery, Last-Mile Logistics, Gig Economy, Sustainability, E-Commerce, Technological Innovation, Public PolicyAbstract
The rise of crowdsourced delivery has transformed last-mile logistics by leveraging gig workers and community resources to meet the growing demands of e-commerce and urbanization. This narrative review aims to synthesize current research on operational efficiency, consumer adoption, workforce dynamics, technological innovation, sustainability, and regulatory challenges. Literature was systematically identified from databases such as Scopus, Web of Science, and Google Scholar using targeted keywords and Boolean operators, with inclusion criteria focusing on peer-reviewed studies between 2010 and 2025. The review highlights that optimization algorithms, including machine learning and reinforcement learning, substantially improve routing and scheduling efficiency. Consumer adoption is strongly influenced by trust, transparency, and usability, while gig workers face challenges of precarious employment, inconsistent compensation, and customer injustice. Technological innovations such as blockchain, smart contracts, digital twins, and hybrid drone-human delivery models enhance transparency, security, and operational responsiveness. Sustainability outcomes are notable, with evidence of reduced emissions and strengthened community-based logistics. Nevertheless, systemic barriers remain, including fragmented regulatory frameworks, uneven technological readiness, and unresolved labor protections. These findings underscore the urgency of policy interventions to ensure fair labor standards, incentivize sustainable practices, and strengthen digital infrastructure. Future research should expand geographic coverage, investigate worker equity, and adopt interdisciplinary approaches. This review concludes that balancing efficiency, consumer trust, worker rights, and regulatory clarity is essential for developing resilient and sustainable crowdsourced delivery systems.
References
Basık, F., Gedik, B., Ferhatosmanoğlu, H., & Wu, K. (2021). Fair task allocation in crowdsourced delivery. IEEE Transactions on Services Computing, 14(4), 1040-1053. https://doi.org/10.1109/tsc.2018.2854866 DOI: https://doi.org/10.1109/TSC.2018.2854866
Boulos, M., Wilson, J., & Clauson, K. (2018). Geospatial blockchain: promises, challenges, and scenarios in health and healthcare. International Journal of Health Geographics, 17(1). https://doi.org/10.1186/s12942-018-0144-x DOI: https://doi.org/10.1186/s12942-018-0144-x
Castillo, V., Bell, J., Rose, W., & Rodrigues, A. (2017). Crowdsourcing last mile delivery: strategic implications and future research directions. Journal of Business Logistics, 39(1), 7-25. https://doi.org/10.1111/jbl.12173 DOI: https://doi.org/10.1111/jbl.12173
Cebeci, M., Tapia, R., Nadi, A., Bok, M., & Tavasszy, L. (2023). Does crowdshipping of parcels generate new passenger trips? evidence from the Netherlands. Transportation Research Record: Journal of the Transportation Research Board, 2678(6), 360-375. https://doi.org/10.1177/03611981231196149 DOI: https://doi.org/10.1177/03611981231196149
Choi, K., Bedogni, L., & Levorato, M. (2022). Enabling green crowdsourced social delivery networks in urban communities. Sensors, 22(4), 1541. https://doi.org/10.3390/s22041541 DOI: https://doi.org/10.3390/s22041541
Ciobotaru, G., & Chankov, S. (2021). Towards a taxonomy of crowdsourced delivery business models. International Journal of Physical Distribution & Logistics Management, 51(5), 460-485. https://doi.org/10.1108/ijpdlm-10-2019-0326 DOI: https://doi.org/10.1108/IJPDLM-10-2019-0326
Ding, Y., Guo, B., Zheng, L., Lu, M., Zhang, D., Wang, S., … & He, T. (2021). A city-wide crowdsourcing delivery system with reinforcement learning. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 5(3), 1-22. https://doi.org/10.1145/3478117 DOI: https://doi.org/10.1145/3478117
Dötterl, J., Bruns, R., Dunkel, J., & Ossowskí, S. (2020). Evaluating crowdshipping systems with agent-based simulation (pp. 396-411). https://doi.org/10.1007/978-3-030-66412-1_25 DOI: https://doi.org/10.1007/978-3-030-66412-1_25
Fatehi, S., & Wagner, M. (2022). Crowdsourcing last-mile deliveries. Manufacturing & Service Operations Management, 24(2), 791-809. https://doi.org/10.1287/msom.2021.0973 DOI: https://doi.org/10.1287/msom.2021.0973
Guo, X., Jaramillo, Y., Bloemhof‐Ruwaard, J., & Claassen, G. (2019). On integrating crowdsourced delivery in last-mile logistics: a simulation study to quantify its feasibility. Journal of Cleaner Production, 241, 118365. https://doi.org/10.1016/j.jclepro.2019.118365 DOI: https://doi.org/10.1016/j.jclepro.2019.118365
Karakikes, I., & Nathanail, E. (2022). Assessing the impacts of crowdshipping using public transport: a case study in a middle-sized Greek city. Future Transportation, 2(1), 55-83. https://doi.org/10.3390/futuretransp2010004 DOI: https://doi.org/10.3390/futuretransp2010004
Kendrišić, M. (2025). Exploring the potential for introducing crowdsourced e-health services. Health Informatics Journal, 31(3). https://doi.org/10.1177/14604582251356208 DOI: https://doi.org/10.1177/14604582251356208
Kervola, H., Kallionpää, E., & Liimatainen, H. (2022). Delivering goods using a baby pram: the sustainability of last-mile logistics business models. Sustainability, 14(21), 14031. https://doi.org/10.3390/su142114031 DOI: https://doi.org/10.3390/su142114031
Koh, L., Peh, Y., Wang, X., & Yuen, K. (2023). Adoption of online crowdsourced logistics during the pandemic: a consumer-based approach. The International Journal of Logistics Management, 35(2), 531-556. https://doi.org/10.1108/ijlm-05-2022-0213 DOI: https://doi.org/10.1108/IJLM-05-2022-0213
Lee, S., Chang, H., & Cho, M. (2022). Applying the sociotechnical systems theory to crowdsourcing food delivery platforms: the perspective of crowdsourced workers. International Journal of Contemporary Hospitality Management, 34(7), 2450-2471. https://doi.org/10.1108/ijchm-10-2021-1286 DOI: https://doi.org/10.1108/IJCHM-10-2021-1286
Li, L., & Li, G. (2024). Cross-platform logistics collaboration: the impact of a self-built delivery service. Journal of Theoretical and Applied Electronic Commerce Research, 20(1), 3. https://doi.org/10.3390/jtaer20010003 DOI: https://doi.org/10.3390/jtaer20010003
Li, Y. (2025). Crowdsourcing delivery for fresh agricultural products in China—exploring the factors influencing individual participation. Frontiers in Sustainable Food Systems, 9. https://doi.org/10.3389/fsufs.2025.1486669 DOI: https://doi.org/10.3389/fsufs.2025.1486669
Liu, Y., Cai, L., Wang, X., & Tan, X. (2025). Customer-directed counterproductive work behavior of gig workers in crowdsourced delivery: a perspective on customer injustice. Systems, 13(4), 246. https://doi.org/10.3390/systems13040246 DOI: https://doi.org/10.3390/systems13040246
Nadime, K., Benhra, J., Benabbou, R., & Mouatassim, S. (2023). Automating attended home deliveries with smart contracts: a blockchain-based solution for e-commerce logistics. E3S Web of Conferences, 469, 00026. https://doi.org/10.1051/e3sconf/202346900026 DOI: https://doi.org/10.1051/e3sconf/202346900026
Pahwa, A., & Jaller, M. (2023). Assessing last-mile distribution resilience under demand disruptions. Transportation Research Part E: Logistics and Transportation Review, 172, 103066. https://doi.org/10.1016/j.tre.2023.103066 DOI: https://doi.org/10.1016/j.tre.2023.103066
Pan, Y., Gao, J., Duan, J., Shi, J., Guo, B., Liang, Y., … & Hu, Y. (2024). Pioneering cooperative air-ground instant delivery using UAVs and crowdsourced couriers. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 8(4), 1-26. https://doi.org/10.1145/3699722 DOI: https://doi.org/10.1145/3699722
Punel, A., Ermagun, A., & Stathopoulos, A. (2019). Push and pull factors in adopting a crowdsourced delivery system. Transportation Research Record: Journal of the Transportation Research Board, 2673(7), 529-540. https://doi.org/10.1177/0361198119842127 DOI: https://doi.org/10.1177/0361198119842127
Sampaio, A., Savelsbergh, M., Veelenturf, L., & Woensel, T. (2020). Delivery systems with crowd‐sourced drivers: a pickup and delivery problem with transfers. Networks, 76(2), 232-255. https://doi.org/10.1002/net.21963 DOI: https://doi.org/10.1002/net.21963
Savelsbergh, M., & Ulmer, M. (2024). Challenges and opportunities in crowdsourced delivery planning and operations—an update. Annals of Operations Research, 343(2), 639-661. https://doi.org/10.1007/s10479-024-06249-1 DOI: https://doi.org/10.1007/s10479-024-06249-1
Seghezzi, A., Mangiaracina, R., Tumino, A., & Perego, A. (2020). ‘Pony express’ crowdsourcing logistics for last-mile delivery in B2C e-commerce: an economic analysis. International Journal of Logistics Research and Applications, 24(5), 456-472. https://doi.org/10.1080/13675567.2020.1766428 DOI: https://doi.org/10.1080/13675567.2020.1766428
Ta, H., Esper, T., Hofer, A., & Sodero, A. (2023). Crowdsourced delivery and customer assessments of e‐logistics service quality: an appraisal theory perspective. Journal of Business Logistics, 44(3), 345-368. https://doi.org/10.1111/jbl.12327 DOI: https://doi.org/10.1111/jbl.12327
Ta, H., Esper, T., Hofer, A., & Sodero, A. (2024). Reconceptualizing e‐logistics service quality (e‐LSQ) in emerging contexts: the case of crowdsourced delivery. Journal of Business Logistics, 46(1). https://doi.org/10.1111/jbl.12401 DOI: https://doi.org/10.1111/jbl.12401
Yang, Y., Zhang, Y., Zhao, S., & Liu, S. (2025). Pricing strategy for crowdsourced delivery service platform considering demand heterogeneity: subscription or pay-per-transaction. Asia-Pacific Journal of Operational Research, 42(01). https://doi.org/10.1142/s0217595925400019 DOI: https://doi.org/10.1142/S0217595925400019
Zhen, L., Wu, Y., Wang, S., & Yi, W. (2021). Crowdsourcing mode evaluation for parcel delivery service platforms. International Journal of Production Economics, 235, 108067. https://doi.org/10.1016/j.ijpe.2021.108067 DOI: https://doi.org/10.1016/j.ijpe.2021.108067
Zhao, B., & Luo, S. (2023). The old conflict in the new economy? Courier resistance on outsourcing platforms in China. The China Quarterly, 258, 495-512. https://doi.org/10.1017/s0305741023001467 DOI: https://doi.org/10.1017/S0305741023001467

