IDEAS home Printed from https://ideas.repec.org/r/bla/popmgt/v29y2020i9p2153-2174.html
   My bibliography  Save this item

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

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. 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.
  2. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2024. "Compensation guarantees in crowdsourced delivery: Impact on platform and driver welfare," Omega, Elsevier, vol. 122(C).
  3. 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.
  4. 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.
  5. Ausseil, Rosemonde & Ulmer, Marlin W. & Pazour, Jennifer A., 2024. "Online acceptance probability approximation in peer-to-peer transportation," Omega, Elsevier, vol. 123(C).
  6. 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.
  7. 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.
  8. 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.
  9. 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).
  10. 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.
  11. Hou, Ting & Zhang, Wen, 2021. "Optimal two-stage elimination contests for crowdsourcing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
  12. 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.
  13. 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.
  14. 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.
  15. 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).
  16. 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).
  17. 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).
  18. Auad, Ramon & Erera, Alan & Savelsbergh, Martin, 2023. "Courier satisfaction in rapid delivery systems using dynamic operating regions," Omega, Elsevier, vol. 121(C).
  19. 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).
  20. 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).
  21. 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.
  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. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
  24. 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.
  25. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
  26. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.