Scheduling heterogeneous delivery tasks on a mixed logistics platform

Zhen, Lu; Tan, Zheyi; Wang, Shuaian; Lyu, Junyan

doi:10.1016/j.ejor.2021.06.057

Cited by 12 publications

(2 citation statements)

References 59 publications

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“…Research also suggests that CD can provide sustainability benefits by reducing transportation footprints (Paloheimo et al, 2016). The literature also investigates matching and scheduling algorithms, as well as platform designs such as driver menus and driver compensation, that impact the time and cost efficacy of CD models (e.g., Allahviranloo & Baghestani, 2019; Castillo, Bell, et al, 2022; Castillo, Mollenkopf, et al, 2022; Horner et al, 2021; Xiao et al, 2021; Zhen et al, 2022).…”

Section: Last‐mile Logistics Service Quality and Crowdsourcingmentioning

confidence: 99%

Crowdsourced delivery and customer assessments ofe‐LogisticsService Quality: An appraisal theory perspective

Esper

Hofer

et al. 2023

J of Business Logistics

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Thanks to increased technological advancements, retailers have progressively incorporated crowdsourcing into their delivery service portfolios to offer customers an enhanced last-mile delivery experience. Yet, while studies have explored the unique operational attributes of the crowdsourced delivery (CD) model in online retailing, the literature remains scant on how customers respond to the usage of this emerging delivery service. Building on the cognitive appraisal theory and e-Logistics Service Quality (e-LSQ) literatures, this study applies middle-range theorizing to examine differences between customers' appraisals of e-LSQ dimensions of CD and traditional delivery methods, and what types of products being delivered make such differences more pronounced. Our analysis of a large sample of customers' reviews across multiple retailers reveals that customers exhibit higher appraisal levels of timeliness, price, and reliability of delivery services when CD is used. Results also indicate that appraisals are more pronounced for timeliness and price of deliveries of high-turnover products that require minimal time and effort to purchase. Our findings, as such, underscore the power of CD as a tool to enhance customer experience and unveil potential opportunities for effective CD use in customer segmentation strategies.

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Section: Last‐mile Logistics Service Quality and Crowdsourcingmentioning

confidence: 99%

Crowdsourced delivery and customer assessments ofe‐LogisticsService Quality: An appraisal theory perspective

Esper

Hofer

et al. 2023

J of Business Logistics

View full text Add to dashboard Cite

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“…In vehicle routing, multiple depots are a prominent concept (Gouveia et al, 2022;Brandão, 2020;Ramos et al, 2020;Montoya-Torres et al, 2015). Additionally, multi-depot solutions also combine well with new logistics schemes like crowd shipping or mobile depots (Mousavi et al, 2022;Zhen et al, 2022;Hof and Schneider, 2021).…”

Section: Micro-depot Transportationmentioning

confidence: 99%

Integrating Micro-Depot Freight Transport in Existing Public Transport Services

Hörsting

Cleophas

2023

Preprint

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As conventional last-mile transport contributes to traffic congestion and pollution, new approaches to transporting freight in urban areas are needed. Integrating freight deliveries with existing public transport infrastructures, such as light rail, is a promising concept. However, it poses the challenge of offering a high service quality for passengers and freight. In this work, we consider a setting where freight originates from and is transshipped at several public transit stops that serve as micro-depots. These micro-depots have a limited storage capacity. Further, we consider a system that relies on shared vehicles, where a dedicated part of the capacity serves either as room to fasten freight containers or as a standing room for passengers. For this setting, we propose an optimization model that integrates the tactical scheduling of vehicles and the allocation of freight containers to vehicles. To solve realistically-sized instances, we propose an adaptive large neighborhood search heuristic. We use this heuristic to evaluate the system’s sensitivity to the capacity of micro-depots and vehicles in various scenarios.

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