Exploring the Potential Impact of Crowdshipping Using Public Transport in Singapore

Because of increased urbanization and a rise in e-commerce activities, the demand for freight transport in cities is growing. E-retailers and logistics companies face the challenge of making timely, cost-effective, and reliable deliveries. To address this problem, the concept of crowdshipping has ga...

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Published inTransportation research record Vol. 2677; no. 2; pp. 173 - 189
Main Authors Zhang, Meijing, Cheah, Lynette, Courcoubetis, Costas
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.02.2023
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Abstract Because of increased urbanization and a rise in e-commerce activities, the demand for freight transport in cities is growing. E-retailers and logistics companies face the challenge of making timely, cost-effective, and reliable deliveries. To address this problem, the concept of crowdshipping has gained interest. Crowdshipping enlists members of the public to pick up and drop off parcels, ideally en route to their pre-committed destination. Individuals, such as commuters using public transport, can be engaged to fulfill deliveries as “crowdshippers.” This research explores the potential impact of crowdshipping using public transport in a congested city, focusing on Singapore as a case study. First, an online survey was conducted to investigate the willingness of transit passengers to act as crowdshippers. Then, a parcel allocation model was developed to match parcels with public bus journeys. In the case of there not being enough crowdshippers available, the remaining parcels will be delivered using the carrier’s delivery vans, which are subject to a vehicle routing problem. Using real-world data, we compared the performance of an e-commerce carrier with and without crowdshipping. The results show that crowdshipping can reduce vehicle kilometers traveled and associated air emissions by up to 17%. The carrier’s delivery cost can be reduced by up to 29% per parcel. These savings can be realized even if crowdshipping is limited to off-peak travel hours only. In a congested city with an extensive transit system, crowdshipping using public transport has the potential to be a sustainable means of moving goods in urban areas.
AbstractList Because of increased urbanization and a rise in e-commerce activities, the demand for freight transport in cities is growing. E-retailers and logistics companies face the challenge of making timely, cost-effective, and reliable deliveries. To address this problem, the concept of crowdshipping has gained interest. Crowdshipping enlists members of the public to pick up and drop off parcels, ideally en route to their pre-committed destination. Individuals, such as commuters using public transport, can be engaged to fulfill deliveries as “crowdshippers.” This research explores the potential impact of crowdshipping using public transport in a congested city, focusing on Singapore as a case study. First, an online survey was conducted to investigate the willingness of transit passengers to act as crowdshippers. Then, a parcel allocation model was developed to match parcels with public bus journeys. In the case of there not being enough crowdshippers available, the remaining parcels will be delivered using the carrier’s delivery vans, which are subject to a vehicle routing problem. Using real-world data, we compared the performance of an e-commerce carrier with and without crowdshipping. The results show that crowdshipping can reduce vehicle kilometers traveled and associated air emissions by up to 17%. The carrier’s delivery cost can be reduced by up to 29% per parcel. These savings can be realized even if crowdshipping is limited to off-peak travel hours only. In a congested city with an extensive transit system, crowdshipping using public transport has the potential to be a sustainable means of moving goods in urban areas.
Author Cheah, Lynette
Zhang, Meijing
Courcoubetis, Costas
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Issue 2
Keywords delivery
planning and logistics
freight systems
urban freight transport
logistics
model/modeling
distribution
Language English
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