E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography

James Tan, the newly appointed manager at XDE’s micro-fulfilment centre (MFC) serving Sooseo district in Seoul city (South Korea), had been recruited to improve the firm’s operational performance and service level to customers. He had to propose the possible routing of electric cargo bikes (e-bikes)...

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Main Authors: LOW, Joyce, LEE, Byung Kwon
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
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Online Access:https://ink.library.smu.edu.sg/cases_coll_all/496
https://cmp-shop.smu.edu.sg/products/e-bikes-how-best-to-deploy-last-mile-delivery-vehicles-by-geographical-zoning-and-topography?variant=41991963148330
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spelling sg-smu-ink.cases_coll_all-14982024-09-18T08:50:02Z E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography LOW, Joyce LEE, Byung Kwon James Tan, the newly appointed manager at XDE’s micro-fulfilment centre (MFC) serving Sooseo district in Seoul city (South Korea), had been recruited to improve the firm’s operational performance and service level to customers. He had to propose the possible routing of electric cargo bikes (e-bikes) to be deployed such that it would minimise delivery lead-time. By January 2024, battery-operated e-bikes were a promising alternative to trucks for last-mile delivery, as they offered higher accessibility, better last-mile delivery, and were environmentally friendly compared to conventional motorised vehicles that ran on fossil fuels. Since e-bikes took a longer time to travel between delivery points, their use as a last-mile delivery option from MFCs involved careful route planning by delivery service provides, especially in areas that had uneven terrain or steep slopes. Tan wanted to analyse the data to understand the factors that determined the number of e-bikes to be deployed to different districts of the city. Such factors included the difference between distance-based and time-based services, and the implication of MFC re-visiting frequencies based on a reduction in e-bike capacity (be it battery or load capacity). He also wanted to recommend an appropriate service boundary for running e-bikes. Students will be able to use data analytics in operations management for route planning in an MFC, with a focus on operational performance and service level to customers. With an aim to reduce delivery lead-time, students will be able to: - Differentiate between distance- and time-based service - Understand the implication of revisiting MFCs due to reducing e-bike capacity - Determine the number of e-bikes deployed to different areas - Establish an appropriate service boundary for running e-bikes 2024-08-01T07:00:00Z text https://ink.library.smu.edu.sg/cases_coll_all/496 https://cmp-shop.smu.edu.sg/products/e-bikes-how-best-to-deploy-last-mile-delivery-vehicles-by-geographical-zoning-and-topography?variant=41991963148330 Case Collection eng Institutional Knowledge at Singapore Management University Alternative fuel vehicle Business management logistics Operations and Supply Chain Management resource allocation service delivery Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Alternative fuel vehicle
Business management
logistics
Operations and Supply Chain Management
resource allocation
service delivery
Operations and Supply Chain Management
spellingShingle Alternative fuel vehicle
Business management
logistics
Operations and Supply Chain Management
resource allocation
service delivery
Operations and Supply Chain Management
LOW, Joyce
LEE, Byung Kwon
E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
description James Tan, the newly appointed manager at XDE’s micro-fulfilment centre (MFC) serving Sooseo district in Seoul city (South Korea), had been recruited to improve the firm’s operational performance and service level to customers. He had to propose the possible routing of electric cargo bikes (e-bikes) to be deployed such that it would minimise delivery lead-time. By January 2024, battery-operated e-bikes were a promising alternative to trucks for last-mile delivery, as they offered higher accessibility, better last-mile delivery, and were environmentally friendly compared to conventional motorised vehicles that ran on fossil fuels. Since e-bikes took a longer time to travel between delivery points, their use as a last-mile delivery option from MFCs involved careful route planning by delivery service provides, especially in areas that had uneven terrain or steep slopes. Tan wanted to analyse the data to understand the factors that determined the number of e-bikes to be deployed to different districts of the city. Such factors included the difference between distance-based and time-based services, and the implication of MFC re-visiting frequencies based on a reduction in e-bike capacity (be it battery or load capacity). He also wanted to recommend an appropriate service boundary for running e-bikes. Students will be able to use data analytics in operations management for route planning in an MFC, with a focus on operational performance and service level to customers. With an aim to reduce delivery lead-time, students will be able to: - Differentiate between distance- and time-based service - Understand the implication of revisiting MFCs due to reducing e-bike capacity - Determine the number of e-bikes deployed to different areas - Establish an appropriate service boundary for running e-bikes
format text
author LOW, Joyce
LEE, Byung Kwon
author_facet LOW, Joyce
LEE, Byung Kwon
author_sort LOW, Joyce
title E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
title_short E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
title_full E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
title_fullStr E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
title_full_unstemmed E-bikes: How best to deploy last-mile delivery vehicles by geographical zoning and topography
title_sort e-bikes: how best to deploy last-mile delivery vehicles by geographical zoning and topography
publisher Institutional Knowledge at Singapore Management University
publishDate 2024
url https://ink.library.smu.edu.sg/cases_coll_all/496
https://cmp-shop.smu.edu.sg/products/e-bikes-how-best-to-deploy-last-mile-delivery-vehicles-by-geographical-zoning-and-topography?variant=41991963148330
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