## 4 Current Issues of Last Mile Logistics
### Proximity Stations/Points and Hubs  
Using proximity stations or proximity points is a new way to improve the efficiency of LML. This is useful for small- to medium-sized delivery parcels when customers are not at home. Deliverers store parcels at a depot station near a customer's address when home deliveries fail, and customers pick up their products later. In addition, delivery time can be reduced by visiting a proximity point during the night when traffic volume is low [62]. The applications of proximity stations and/or proximity points to LML are aimed, not only to integrate proximity points into existing LML, but also to identify locations for proximity points (see Table 4). Ref. [63] proposed a modular bento-box system to store delivery parcels until customers pick up their deliveries. Shopping malls, central squares, and residential districts were suggested as examples for the possible location of proximity points. Ref. [64] proposed an effective mobile crowd-tasking model that handles many citizens as crowd workers to perform LML. They formulated a proximity station problem in LML as a minimal-cost network flow problem, which minimizes the additional cost \begin{table}
\begin{tabular}{l l l} \hline \hline
**LML-Related Issue** & **Research Finding** & **Reference** \\ \hline Social impact & Crowdsourcing delivery to decrease unemployment & [53] \\ \hline \multirow{7}{*}{Economic impact} & MIP model to address the VRP for crowdsourced drivers & [55] \\  & Total cost reduction by ad-hoc drivers with backup vehicles & [25] \\  & Effectiveness of crowdsourcing last mile delivery & [57] \\  & Delivery cost reduction by a dual-channel logistics system & [18] \\  & Multiple parcel deliveries for each crowdsourced driver & [56] \\  & Acceptability and preferences of crowdshipping attributes characterized depending on \\  & shipment distance & [58] \\  & Potential of crowdsourcing last mile delivery & [54] \\ \hline \multirow{7}{*}{Environmental impact} & Negative impacts of crowdsourcing deliveries on overall & [59] \\  & environmental performance & [54] \\  & Reduced transportation emissions and delivery costs due to the use of social network & [42] \\ \cline{1-1}  & Positive effect of shared mobility on greenhouse gas emissions & [60] \\ \cline{1-1}  & Reduced carbon emissions and delivery distance in urban and suburban areas by a social & [61] \\ \cline{1-1}  & network-enabled package pickup & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: LML-related issues and research findings: Sharing economy. to assign all delivery parcels in pick-own-parcel stations to the most convenient crowd workers. Similarly, Ref. [26] investigated the utilization of parcel locker pickups for LML in the Polish InPost Company system and found that the proper location of parcel lockers was one of the most important factors for delivery efficiency. Hub location problems can be also applied to properly address the location of proximity stations and/or points and to consolidate last mile deliveries across urban areas that can reduce traffic and cut greenhouse gas emissions (see Table 4). Depending on the type of demand allocation for final customers, a last mile hub location problem can be partitioned into single and multiple allocation problems. The single allocation problem assigns every final customer to a single last mile delivery hub, while the multiple allocation problem assigns every final customer to more than one last mile delivery hub. Setting up efficient hub locations for LML can lead to great economic/temporal benefits for both consignors and consignees in delivery costs, quality of delivery services, and environmental impacts [69]. The location of last mile delivery hubs affects both the fixed cost of hub placement and the variable cost of delivery parcels to final customers. Refs. [65,66] respectively proposed a location-routing model to determine multiple last mile delivery hubs based on the total location and delivery vehicle routing costs for each customer's pickup and delivery needs. Ref.