Collaboration in the last mile: Evidence from grocery deliveries

Aktas, Emel, Bourlakis, Michael and Zissis, Dimitris ORCID: https://orcid.org/0000-0002-6957-3494 (2021) Collaboration in the last mile: Evidence from grocery deliveries. International Journal of Logistics Research and Applications, 24 (3). pp. 227-241. ISSN 1367-5567

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Abstract

The grocery sector has transitioned into an omnichannel operating mode, allowing consumers to buy online and have their order delivered to their chosen address. The last mile delivery service leads to avoidable inefficiencies such as low asset utilisation and repeated trips to nearby neighbourhoods, increasing vehicle emissions, traffic, and operational costs. Combining historical order and delivery data of an online grocery retailer with secondary data publicly available on other retailers, we employ Monte Carlo simulation to estimate grocery home delivery demand per 1-hour time windows. We use the simulation output as an input to daily vehicle routing problem instances under independent and collaborative last mile delivery operation to estimate the impact of collaboration. Our analyses show distance savings of around 17% and route reduction of around 22%. These results can support policies incentivising vehicle and infrastructure sharing settings and decoupling the last mile delivery from the core grocery retail services.

Item Type: Article
Uncontrolled Keywords: collaboration,monte carlo simulation,uk grocery sector,e-commerce,last mile delivery,vehicle routing,capacity,transport,search,model,vehicle-routing problem,food,information systems,control and systems engineering,management information systems,computer science applications,management science and operations research ,/dk/atira/pure/subjectarea/asjc/1700/1710
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 06 Mar 2020 08:58
Last Modified: 22 Oct 2022 05:55
URI: https://ueaeprints.uea.ac.uk/id/eprint/74457
DOI: 10.1080/13675567.2020.1740660

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