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When Are Deliveries Profitable?: Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas

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When Are Deliveries Profitable? Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas. / Cleophas, Catherine; Ehmke, Jan Fabian.
In: Business and Information Systems Engineering, Vol. 6, No. 3, 01.06.2014, p. 153-163.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Cleophas C, Ehmke JF. When Are Deliveries Profitable? Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas. Business and Information Systems Engineering. 2014 Jun 1;6(3):153-163. Epub 2014 Apr 16. doi: 10.1007/s12599-014-0321-9

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@article{8ba7b6f26b014f1ab0eac1ec32fd0568,
title = "When Are Deliveries Profitable?: Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas",
abstract = "The paper aims to optimize the final part of a firm{\textquoteright}s value chain with regard to attended last-mile deliveries. It is assumed that to be profitable, ecommerce businesses need to maximize the overall value of fulfilled orders (rather than their number), while also limiting costs of delivery. To do so, it is essential to decide which delivery requests to accept and which time windows to offer to which consumers. This is especially relevant for attended deliveries, as delivery fees usually cannot fully compensate costs of delivery given tight delivery time windows. The literature review shows that existing order acceptance techniques often ignore either the order value or the expected costs of delivery. The paper presents an iterative solution approach: after calculating an approximate transport capacity based on forecasted expected delivery requests and a cost-minimizing routing, actual delivery requests are accepted or rejected aiming to maximize the overall value of orders given the computed transport capacity. With the final set of accepted requests, the routing solution is updated to minimize costs of delivery. The presented solution approach combines well-known methods from revenue management and time-dependent vehicle routing. In a computational study for a German metropolitan area, the potential and the limits of value-based demand fulfillment as well as its sensitivity regarding forecast accuracy and demand composition are investigated.",
keywords = "City logistics, Demand fulfillment, Revenue management, Simulation, Vehicle routing",
author = "Catherine Cleophas and Ehmke, {Jan Fabian}",
year = "2014",
month = jun,
day = "1",
doi = "10.1007/s12599-014-0321-9",
language = "English",
volume = "6",
pages = "153--163",
journal = "Business and Information Systems Engineering",
issn = "1867-0202",
publisher = "Springer Gabler",
number = "3",

}

RIS

TY - JOUR

T1 - When Are Deliveries Profitable?

T2 - Considering Order Value and Transport Capacity in Demand Fulfillment for Last-Mile Deliveries in Metropolitan Areas

AU - Cleophas, Catherine

AU - Ehmke, Jan Fabian

PY - 2014/6/1

Y1 - 2014/6/1

N2 - The paper aims to optimize the final part of a firm’s value chain with regard to attended last-mile deliveries. It is assumed that to be profitable, ecommerce businesses need to maximize the overall value of fulfilled orders (rather than their number), while also limiting costs of delivery. To do so, it is essential to decide which delivery requests to accept and which time windows to offer to which consumers. This is especially relevant for attended deliveries, as delivery fees usually cannot fully compensate costs of delivery given tight delivery time windows. The literature review shows that existing order acceptance techniques often ignore either the order value or the expected costs of delivery. The paper presents an iterative solution approach: after calculating an approximate transport capacity based on forecasted expected delivery requests and a cost-minimizing routing, actual delivery requests are accepted or rejected aiming to maximize the overall value of orders given the computed transport capacity. With the final set of accepted requests, the routing solution is updated to minimize costs of delivery. The presented solution approach combines well-known methods from revenue management and time-dependent vehicle routing. In a computational study for a German metropolitan area, the potential and the limits of value-based demand fulfillment as well as its sensitivity regarding forecast accuracy and demand composition are investigated.

AB - The paper aims to optimize the final part of a firm’s value chain with regard to attended last-mile deliveries. It is assumed that to be profitable, ecommerce businesses need to maximize the overall value of fulfilled orders (rather than their number), while also limiting costs of delivery. To do so, it is essential to decide which delivery requests to accept and which time windows to offer to which consumers. This is especially relevant for attended deliveries, as delivery fees usually cannot fully compensate costs of delivery given tight delivery time windows. The literature review shows that existing order acceptance techniques often ignore either the order value or the expected costs of delivery. The paper presents an iterative solution approach: after calculating an approximate transport capacity based on forecasted expected delivery requests and a cost-minimizing routing, actual delivery requests are accepted or rejected aiming to maximize the overall value of orders given the computed transport capacity. With the final set of accepted requests, the routing solution is updated to minimize costs of delivery. The presented solution approach combines well-known methods from revenue management and time-dependent vehicle routing. In a computational study for a German metropolitan area, the potential and the limits of value-based demand fulfillment as well as its sensitivity regarding forecast accuracy and demand composition are investigated.

KW - City logistics

KW - Demand fulfillment

KW - Revenue management

KW - Simulation

KW - Vehicle routing

U2 - 10.1007/s12599-014-0321-9

DO - 10.1007/s12599-014-0321-9

M3 - Journal article

VL - 6

SP - 153

EP - 163

JO - Business and Information Systems Engineering

JF - Business and Information Systems Engineering

SN - 1867-0202

IS - 3

ER -