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Crowdshipping and Same‐day Delivery: Employing In‐store Customers to Deliver Online Orders

Citations

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Cited by:

  1. Du, Jianhui & Zhang, Zhiqin & Wang, Xu & Lau, Hoong Chuin, 2023. "A hierarchical optimization approach for dynamic pickup and delivery problem with LIFO constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
  2. Rouven Schur & Kai Winheller, 2025. "Optimizing last-mile delivery: a dynamic compensation strategy for occasional drivers," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(4), pages 1075-1132, December.
  3. Chen, Xinwei & Wang, Tong & Thomas, Barrett W. & Ulmer, Marlin W., 2023. "Same-day delivery with fair customer service," European Journal of Operational Research, Elsevier, vol. 308(2), pages 738-751.
  4. Yu, Vincent F. & Jodiawan, Panca & Redi, A.A.N. Perwira, 2022. "Crowd-shipping problem with time windows, transshipment nodes, and delivery options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  5. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2024. "Compensation guarantees in crowdsourced delivery: Impact on platform and driver welfare," Omega, Elsevier, vol. 122(C).
  6. Di Puglia Pugliese, Luigi & Ferone, Daniele & Macrina, Giusy & Festa, Paola & Guerriero, Francesca, 2023. "The crowd-shipping with penalty cost function and uncertain travel times," Omega, Elsevier, vol. 115(C).
  7. Auad, Ramon & Erera, Alan & Savelsbergh, Martin, 2023. "Courier satisfaction in rapid delivery systems using dynamic operating regions," Omega, Elsevier, vol. 121(C).
  8. Rosemonde Ausseil & Jennifer A. Pazour & Marlin W. Ulmer, 2022. "Supplier Menus for Dynamic Matching in Peer-to-Peer Transportation Platforms," Transportation Science, INFORMS, vol. 56(5), pages 1304-1326, September.
  9. Stoia, Sara & Laganà, Demetrio & Ohlmann, Jeffrey W., 2025. "Dynamic pickup-and-delivery for collaborative platforms with time-dependent travel and crowdshipping," European Journal of Operational Research, Elsevier, vol. 322(1), pages 70-84.
  10. Arslan, Alp & Kılcı, Fırat & Cheng, Shih-Fen & Misra, Archan, 2026. "Choice-based crowdshipping for next-day delivery services: A dynamic task display problem," European Journal of Operational Research, Elsevier, vol. 328(1), pages 336-348.
  11. Martin Savelsbergh & Marlin W. Ulmer, 2024. "Challenges and opportunities in crowdsourced delivery planning and operations—an update," Annals of Operations Research, Springer, vol. 343(2), pages 639-661, December.
  12. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
  13. dos Santos, André Gustavo & Viana, Ana & Pedroso, João Pedro, 2022. "2-echelon lastmile delivery with lockers and occasional couriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
  14. Zhou, Dianqing & Rasouli, Soora & Wong, Melvin, 2026. "Understanding crowd-shipping acceptance: A hierarchical latent class personality-attitude hybrid choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 205(C).
  15. Cebeci, Merve Seher & Tapia, Rodrigo Javier & Kroesen, Maarten & de Bok, Michiel & Tavasszy, Lóránt, 2023. "The effect of trust on the choice for crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
  16. Chen, Xinwei & Ulmer, Marlin W. & Thomas, Barrett W., 2022. "Deep Q-learning for same-day delivery with vehicles and drones," European Journal of Operational Research, Elsevier, vol. 298(3), pages 939-952.
  17. Annarita De Maio & Jeffrey W. Ohlmann & Sara Stoia & Francesca Vocaturo, 2025. "Analysis of in-store crowdshipping in a stochastic dynamic pickup-and-delivery system," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 33(3), pages 1149-1170, September.
  18. Ausseil, Rosemonde & Ulmer, Marlin W. & Pazour, Jennifer A., 2024. "Online acceptance probability approximation in peer-to-peer transportation," Omega, Elsevier, vol. 123(C).
  19. Alnaggar, Aliaa & Bhatt, Sahil, 2026. "Fleet size planning in crowdsourced delivery: Balancing service level and driver utilization," Omega, Elsevier, vol. 139(C).
  20. Nieto-Isaza, Santiago & Fontaine, Pirmin & Minner, Stefan, 2022. "The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery: A Benders decomposition approach," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 62-79.
  21. Martin W.P Savelsbergh & Marlin W. Ulmer, 2022. "Challenges and opportunities in crowdsourced delivery planning and operations," 4OR, Springer, vol. 20(1), pages 1-21, March.
  22. Xiao, Haohan & Xu, Min & Wang, Shuaian, 2023. "Crowd-shipping as a Service: Game-based operating strategy design and analysis," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
  23. Zhao, Yanlu & Alfandari, Laurent & Archetti, Claudia, 2025. "Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force," European Journal of Operational Research, Elsevier, vol. 323(1), pages 139-152.
  24. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
  25. Abdollahi, Mohammad & Yang, Xinan & Nasri, Moncef Ilies & Fairbank, Michael, 2023. "Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders," European Journal of Operational Research, Elsevier, vol. 309(2), pages 704-718.
  26. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
  27. Boysen, Nils & Emde, Simon & Schwerdfeger, Stefan, 2022. "Crowdshipping by employees of distribution centers: Optimization approaches for matching supply and demand," European Journal of Operational Research, Elsevier, vol. 296(2), pages 539-556.
  28. Garcia-Herrera, Alisson & Serrano-Hernandez, Adrian & Faulin, Javier, 2025. "Understanding the dynamics of crowdshipping in last-mile distribution within urban mobility: A comprehensive framework," Socio-Economic Planning Sciences, Elsevier, vol. 101(C).
  29. Ghaderi, Hadi & Zhang, Lele & Tsai, Pei-Wei & Woo, Jihoon, 2022. "Crowdsourced last-mile delivery with parcel lockers," International Journal of Production Economics, Elsevier, vol. 251(C).
  30. Li, Qilong & Xiao, Haohan & Xu, Min & Qu, Ting, 2024. "Investigating the impact of late deliveries on the operations of the crowd-shipping platform: A mean-variance analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
  31. Zhou, Bingjie & Zhang, Yu & Baldacci, Roberto & Tang, Jiafu, 2026. "The service-centric Vehicle Routing Problem with Crowdshipping," European Journal of Operational Research, Elsevier, vol. 331(2), pages 495-519.
  32. Tao, Jiawei & Dai, Hongyan & Chen, Weiwei & Jiang, Hai, 2023. "The value of personalized dispatch in O2O on-demand delivery services," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1022-1035.
  33. Paradiso, Rosario & Roberti, Roberto & Ulmer, Marlin, 2025. "Lookahead scenario relaxation for dynamic time window assignment in service routing," Transportation Research Part B: Methodological, Elsevier, vol. 192(C).
  34. Wang, Li & Xu, Min & Qin, Hu, 2023. "Joint optimization of parcel allocation and crowd routing for crowdsourced last-mile delivery," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 111-135.
  35. Shanyong Wang & Shiqiang Li & Haonan He & Qi Zhou, 2025. "Flexible supply-demand matching mechanism for C2B crowdsourcing logistics platforms with heterogeneous environment-inclined merchants," Annals of Operations Research, Springer, vol. 355(2), pages 1457-1481, December.
  36. Hou, Ting & Zhang, Wen, 2021. "Optimal two-stage elimination contests for crowdsourcing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
  37. Silva, Marco & Pedroso, João Pedro & Viana, Ana, 2023. "Stochastic crowd shipping last-mile delivery with correlated marginals and probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 307(1), pages 249-265.
  38. Vivaldini, Mauro & Vivaldini, Leticia Ribeiro, 2025. "Reflection on faster and faster deliveries: Possible social changes arising from logistical immediacy," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
  39. Marco Silva & João Pedro Pedroso, 2022. "Deep Reinforcement Learning for Crowdshipping Last-Mile Delivery with Endogenous Uncertainty," Mathematics, MDPI, vol. 10(20), pages 1-23, October.
  40. Zehtabian, Shohre & Larsen, Christian & Wøhlk, Sanne, 2022. "Estimation of the arrival time of deliveries by occasional drivers in a crowd-shipping setting," European Journal of Operational Research, Elsevier, vol. 303(2), pages 616-632.
  41. Mancini, Simona & Ulmer, Marlin W. & Gansterer, Margaretha, 2025. "Dynamic assignment of delivery order bundles to in-store customers," Omega, Elsevier, vol. 133(C).
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