Abstract

The current and projected trends of growth in online shopping might change the activity and travel patterns in Christchurch, one of the largest cities in New Zealand. Online shopping might reduce consumers’ shopping trips, but it has substantially increased courier companies’ trips to deliver parcels to the end-consumers because a considerable proportion of parcels are often required to be redelivered due to consumers not being at home during the first delivery attempt. This also adds to the operational cost of courier companies and adverse traffic impacts. To mitigate these issues, collection-and-delivery points (CDPs) have recently been introduced in New Zealand on a trial basis. This study aims to identify the optimal density and locations for establishing CDPs in Christchurch using a modified p-median location-allocation (LA) model. A consumer-centric approach to locating CDPs has been adopted by considering the socio-demographic characteristics of Christchurch’s residents and the distances to/from CDPs. Non-traditional CDP locations (e.g., supermarkets and dairies) were considered as potential candidate facilities and were found to be more suitable as CDPs than traditional post shops. Based on consumers’ shopping pattern, supermarkets appeared to be the most frequently visited and preferred type of facility to be used as CDPs. However, the results of the LA analyses show that dairies are the most accessible locations, and CDPs at dairies located within two kilometres will encourage consumers to walk and cycle to receive their parcels from CDPs. The results suggest the optimal location configuration for each type of facility considered, based on their spatial distribution in the city.

Highlights

  • The worldwide growth in online retail sales has resulted in an increase in the number of parcels that need to be delivered to end-consumers and the number of delivery vehicles [1,2,3,4]

  • Over 10% of home deliveries by a major courier company operating in New Zealand fail during the first attempt [7]

  • Apart from consumers’ data, three types of inputs are typically required in LA modelling; the location of facilities having a potential to serve as collection-and-delivery points (CDPs), the spatially distributed demand, and a measure of distance between facility and demand locations, such as network distance or travel time

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Summary

Introduction

The worldwide growth in online retail sales has resulted in an increase in the number of parcels that need to be delivered to end-consumers and the number of delivery vehicles [1,2,3,4]. Taking a consumer-centric approach to LA modelling, Alvarado and Liu [46] identified country-wide locations for providing the parcel self-collection service (via service point CDPs) at the outlets of a department store chain in the US. They formulated a binary integer programming function aimed at maximising savings, in terms of the transport cost for consumers and service providers, along with a reduction in the CO2 emissions. Be noted that the above problems of people not being allocated to the nearest CDP and not being evenly distributed exist with the mesh block area units, but to a smaller extent than with the postal code area units

Problem Formulation
Consumers’ Characteristics and Model Parameters
Demand Points’ Locations
Candidate Facilities’ Locations
Spatial Distribution of Potential CDP Locations
Road Network and Attributes
Store Owners’ and Courier Companies’ Survey
Findings
Conclusions and Directions for Future Research
Full Text
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