Recently, e-grocery has captured the interest of both academia and industry as it shows great opportunities and many challenges at the same time. E-grocery sector has been significantly boosted by COVID-19 and consumer buying behaviours underwent a change that will remain long after the pandemic. E-grocery market is currently going through a phase of consolidation. However, there are evidence of the inherent structural challenges of the sector. Expectations are increasing, with consumers gravitating towards faster home delivery options. A wide study on the matter enlightened two main points: the crucial role of home delivery, both in terms of effectiveness and criticalities, and an evident literature gap regarding the role of collaborations with third-party logistics providers, which are spreading in the sector as a possible measure to meet customer needs. Therefore, this work aims at investigating third-party logistics services in conjunction with home delivery, by focusing on the concept of on-demand vehicles. An analytical approach is adopted and an optimization model, that combines on-demand fleet composition with a vehicle routing problem with time windows, is built. This work investigates how an optimization model can support the design of a home delivery fleet conjunctly with delivery routings and schedules, by exploiting the on-demand vehicles concept. Plus, it shows how this concept can support economic and environmental sustainability and improve flexibility and effectiveness for retailers. Moreover, it emerges that environmental sustainability goals can play a significant role for the results. In fact, high attention is given to environmental impact, which has a central role in this study. As a result, this work contributes to academic literature and industry by providing a critical analysis and a tool itself that can support the adoption of more sustainable home delivery strategies.
Recentemente, l'e-grocery ha catturato l'interesse sia del mondo accademico che dell'industria, poiché presenta grandi opportunità e criticità allo stesso tempo. Il settore dell'e-grocery ha subito una notevole crescita durante la pandemia di COVID-19 e i comportamenti d'acquisto dei consumatori hanno subito un cambiamento permanente. Attualmente, il mercato dell'e-grocery sta attraversando una fase di consolidamento. Tuttavia, ci sono evidenze di criticità strutturali intrinseche nel settore. Le aspettative dei consumatori stanno aumentando, in particolare riguardo a opzioni di consegna a domicilio più veloci. Uno studio approfondito sull’argomento ha evidenziato due punti principali: il ruolo cruciale della consegna a domicilio, sia in termini di efficacia che di criticità, e una evidente lacuna nella letteratura riguardo al ruolo delle collaborazioni con fornitori di servizi logistici, che si stanno diffondendo nel settore. Pertanto, questo lavoro mira a investigare il ruolo di servizi logistici di terze parti in congiunzione con la consegna a domicilio, concentrandosi sul concetto di veicoli on-demand. Viene adottato un approccio analitico e viene costruito un modello di ottimizzazione che combina un problema di composizione della flotta on-demand con un problema di Vehicle Routing Problem with Time Windows. Questo lavoro indaga su come un modello di ottimizzazione possa supportare la progettazione di una flotta di consegna a domicilio insieme a itinerari e programmi di consegna, sfruttando il concetto di veicoli on-demand. Inoltre, mostra come questo concetto possa supportare la sostenibilità economica e ambientale e migliorare la flessibilità e l'efficacia dei rivenditori. Infine, emerge che gli obiettivi di sostenibilità ambientale possono avere un impatto significativo sui risultati. Infatti, viene data grande attenzione all'impatto ambientale, che assume un ruolo centrale in questo studio. Di conseguenza, questo lavoro contribuisce alla letteratura accademica e all'industria fornendo un'analisi critica e uno strumento che può supportare l'adozione di strategie di consegna a domicilio più sostenibili.
Sustainability in e-grocery last mile delivery: an optimization model considering on-demand delivery vehicles
Tudisco, Vittoria
2022/2023
Abstract
Recently, e-grocery has captured the interest of both academia and industry as it shows great opportunities and many challenges at the same time. E-grocery sector has been significantly boosted by COVID-19 and consumer buying behaviours underwent a change that will remain long after the pandemic. E-grocery market is currently going through a phase of consolidation. However, there are evidence of the inherent structural challenges of the sector. Expectations are increasing, with consumers gravitating towards faster home delivery options. A wide study on the matter enlightened two main points: the crucial role of home delivery, both in terms of effectiveness and criticalities, and an evident literature gap regarding the role of collaborations with third-party logistics providers, which are spreading in the sector as a possible measure to meet customer needs. Therefore, this work aims at investigating third-party logistics services in conjunction with home delivery, by focusing on the concept of on-demand vehicles. An analytical approach is adopted and an optimization model, that combines on-demand fleet composition with a vehicle routing problem with time windows, is built. This work investigates how an optimization model can support the design of a home delivery fleet conjunctly with delivery routings and schedules, by exploiting the on-demand vehicles concept. Plus, it shows how this concept can support economic and environmental sustainability and improve flexibility and effectiveness for retailers. Moreover, it emerges that environmental sustainability goals can play a significant role for the results. In fact, high attention is given to environmental impact, which has a central role in this study. As a result, this work contributes to academic literature and industry by providing a critical analysis and a tool itself that can support the adoption of more sustainable home delivery strategies.| File | Dimensione | Formato | |
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2023_12_Tudisco_Tesi_01.pdf
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https://hdl.handle.net/10589/215032