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Urbanization, the corresponding road traffic, and increasing e-grocery markets require efficient and at the same time eco-friendly transport solutions. In contrast to traditional food procurement at local grocery stores, e-grocery, i.e., online ordered goods, are transported directly to end customers. We develop and discuss an optimization approach to assist the planning of e-grocery deliveries in smart cities introducing a new last mile concept for the urban food supply chain. To supply city dwellers with their ordered products, a network of refrigerated grocery lockers is optimized to temporarily store the corresponding goods within urban areas. Customers either collect their orders by themselves or the products are delivered with electric cargo bicycles (ECBs). We propose a multi-echelon optimization model that minimizes the overall costs while consecutively determining optimal grocery locker locations, van routes from a depot to opened lockers, and ECB routes from lockers to customers. With our approach, we present an advanced concept for grocery deliveries in urban areas to shorten last mile distances, enhancing sustainable transportation by avoiding road traffic and emissions. Therefore, the concept is described as a smart transport system.

As resource integration plays a significant part in improving operational efficiency in the last mile delivery industry, there is an increasing popularity for logistics service providers (LSPs) to collaborate with property service companies (PSCs). Based on the evolutionary game theory, considering the dual role of PSCs when collaborating with LSPs, a trilateral evolutionary game model between PSCs, LSPs, and customers (Cs) is established to analyze the strategic choices and explore the influencing factors on the tripartite strategy. The results show that (1) There are optimal profit allocation coefficients and cost-sharing coefficients to cause the system to reach a steady state. (2) The integration cost between LSPs and PSCs and the home delivery cost inhibit the strategic integration of the two enterprises. (3) PSCs are more sensitive to their benefits and costs than LSPs in the process of resource integration. (4) More precisely evaluating their potential loss caused by temporary integration will help the tripartite to make a more scientific choice of strategic behavior. (5) The increase of community premium income helps to improve the enthusiasm of Cs supporting strategic integration. (6) The behavior and decision-making choices of the three game players affect each other in the last mile delivery resource integration. (7) The indirect benefits, such as advertising during their integration, play a positive role. Finally, the MATLAB2020a software is applied to simulate and analyze the impact of key factors on strategy evolution, and we propose several useful suggestions to promote the development of last mile delivery resource integration.

Delivering parcels to collection and delivery points (CDPs) is often seen as a better option compared with home delivery. However, if the demand is inhomogeneous, either the parcel locker utilization or the service level (i.e., the number of parcels that can be delivered) is low. Either situation would reduce the financial viability. This paper compares two options to increase the utilization, namely: (i) modular lockers (i.e., numbers of lockers adjusted periodically depending on demand) and (ii) combining parcel lockers with staffed CDPs. The latter has the advantage of a low investment cost of staffed CDPs and a low cost per parcel of parcel lockers. Secondly, the paper calculates the optimal number of lockers at a staffed CDP, assuming that all parcels are placed in the staffed CDP if the parcel locker is full. This method was applied to data collected by a parcel delivery company in London. The advantage of using real world data over one year is that it includes seasonal and daily changes in the parcel demand. The decision support method accounts for parcels not being picked up by customers on the delivery day, returned deliveries, and the net present value (NPV) of the investment. This paper shows that having enough lockers for 100% of all parcels compared with 80% doubles the number of required parcel lockers because of the inhomogeneity of the demand. In addition, combining fixed lockers with staffed CDPs offers greater financial benefits compared with modular lockers in this case study.

Land efficient last mile delivery concepts are key to reducing the traffic in cities and to minimising its environmental impact. This paper proposes a decision support method that evaluates the autonomous delivery concept and applies it to one year’s worth of real parcel delivery data in London. Deliveries to modular and fixed lockers with autonomous delivery vans and road-based autonomous lockers (RAL) and sidewalk autonomous delivery robots (SADRs) have been simulated. Various types of autonomous delivery van fleets, depot locations, customer modes of transport, parcel demand levels, parcel locker network densities and adjustment frequencies of modular lockers are considered. A routing and scheduling algorithm is used to optimise delivery tours and vehicle choice. The optimisation algorithm finds both the optimal number of collection and delivery points (CDPs) and the delivery concept (e.g., modular lockers, sidewalk autonomous delivery robot) depending on the customer mode chosen. The results show that modular lockers which are adjusted weekly are the best option for the current or higher parcel demand levels and road-autonomous parcel lockers (RAL-R) are the best option at the lowest parcel demand level.

E-grocery is becoming more and more popular, involving both pure e-commerce players and physical stores in its development and sales. As a consequence, the last mile delivery model has been heavily modified, with ambiguous final impact on the environment. This paper identifies the key elements germane to e-grocery (demand and supply), discusses e-grocery development and investigates the challenges ahead. In more detail, it presents the results of a stated preference survey on consumers’ channel choices for the grocery market. The survey was carried out in Shanghai (China) in order to investigate different purchase attributes, such as product and delivery service price, product range, lead time, time window and travel time. The paper identifies heterogeneous reactions to alternative service configurations, which allows to estimate market shares for e-grocery, with the in-store option as a reference. Policy implications and operational solutions to improve the sustainability of this renewed last mile delivery model are thus proposed.

The paper proposes an evaluation method providing decision support for policymakers in regard to the land consumption of transport activities. Due to the increasing pressure on vehicle parking, traffic jams and the housing crisis in large cities, it is important to use road space effectively. The primary objective of this paper is to review and evaluate the published research about the time-area concept, as well as proposing an evaluation method for the time-area requirements of vehicles used in last mile delivery such as pedestrian porters, bicycles, cargo bikes, sidewalk autonomous delivery robots (SADRs) and delivery vans. The time-area concept measures the size of an area occupied during a transport activity and the duration for which it is occupied for standing, as well as moving transport units. While most of the research applies the time-area concept to compare various modes of transport used to move people around a city, this paper focusses on moving parcels and evaluates the effect that operating strategies and policy changes have on the time-area requirements of a single mode of transport. The study builds on a real trip data set of parcel deliveries in London.

The last mile delivery service is an important part in the logistics service process of express enterprises. How to select a suitable logistics service mode for last mile delivery to maximize the delivery service capacity and minimize delivery service cost is a noteworthy problem, but studies on this problem are still lacking. In this paper, we first analyze three potential logistics service modes for last mile delivery, i.e., self-run mode, outsourcing mode, and alliance mode, and then propose a selection framework of logistics service mode for last mile delivery based on a two-dimensional matrix decision model according to the two dimensions of delivery service cost advantage and delivery service capability advantage. Next, we give the calculation formulas for the delivery service cost and delivery service capability. Furthermore, we propose a method for logistics service mode selection for last mile delivery according to delivery service costs and delivery service capabilities of three potential logistics service mode. Finally, we show the feasibility and effectiveness of the proposed method by a case analysis.

Last mile delivery is an important part in the logistics service process of express enterprises since it can directly contact with the customer and affect customer satisfaction. How to select a suitable logistics service mode for last mile delivery with the objectives of lower delivery service cost and higher customer satisfaction is a noteworthy research topic. In this paper, we focus on the analysis method for logistics service mode selection for last mile delivery considering customer utility and delivery service cost. First, we conduct the market survey of customer needs and discuss the market segmentation, and then we propose a customer utility value calculation model based on utility theory. Next, we propose a delivery quantity prediction method based on the time series prediction and customer selection probability calculation. Furthermore, we construct a cost accounting model to determine the delivery service cost. On this basis, we show the selection of the suitable logistics service mode for last mile delivery according to the analysis results of customer utility and delivery service cost. Finally, we show the feasibility and effectiveness of the proposed method by a case analysis.

Sustainable transportation is one of the major concerns in cities. This concern involves all type of movements motivated by different goals (mobility of citizens, transportation of goods and parcels, etc.). The main goal of this work is to provide an intelligent approach for Sustainable Last Mile Delivery, by reducing (or even deleting) the need of dedicated logistic moves (by cars, and/or trucks). The method attempts to reduce the number of movements originated by the parcels delivery by taking advantage of the citizens&rsquo, movements. In this way our proposal follows a crowdsourcing approach, in which the citizens that moves in the city, because of their own needs, become temporal deliverers. The technology behind our approach relays on Multi-agent System techniques and complex network-based algorithms for optimizing sustainable delivery routes. These artificial intelligent approaches help to reduce the complexity of the scenario providing an efficient way to integrate the citizens&rsquo, routes that can be executed using the different transportation means and networks available in the city (public system, private transportation, eco-vehicles sharing systems, etc.). A complex network-based algorithm is used for computing and proposing an optimized Sustainable Last Mile Delivery route to the crowd. Moreover, the executed tests show the feasibility of the proposed solution, together with a high reduction of the CO 2 emission coming from the delivery trucks that, in the case studies, are no longer needed for delivery.

The development of rural e-commerce has rapidly driven the development of rural logistics in China. Improving the service quality of the last mile delivery is an important measure to promote the sustainable development of rural e-commerce logistics. However, such work is challenging because the current rural last mile delivery is inefficient and unsustainable and is influenced by a set of interacting factors. It is necessary to explore the relationships among the sustainability influencing factors of rural last mile delivery. A total of 15 sustainability influencing factors are selected. The improved fuzzy analytic hierarchy process (FAHP) is used to assign the weights of the factors and then the interpretative structural model (ISM) is used to determine the hierarchical structure of each factor. The driving force-dependency quadrant graph is constructed by cross-impact matrix multiplication (MICMAC). The research results show that four factors, including &ldquo, convenience of returning goods&rdquo, &ldquo, integrity of goods&rdquo, advance reservation of goods pickup&rdquo, and &ldquo, delivery costs&rdquo, are the most basic factors affecting the sustainability of rural last mile delivery and are the deepest and most indispensable factors. This research provides valuable information for decision makers to develop proactive strategies and reinforcement policies to improve the service quality of rural last mile delivery, which could promote the sustainable development of rural logistics.

Freight carriers, receivers and citizens in the inner-city area suffer the most from issues impacting last mile delivery due to exacerbated traffic congestion, limited parking and unsustainable delivery vehicles. Freight consolidation policies offer a sustainable solution to address these problems. The freight vehicles used in the consolidated deliveries could play a significant role in the sustainability and success of these policies. This paper applies a multi-stakeholder decision support approach to evaluate the suitability and potential of various delivery fleet configurations in addressing the perspectives and requirements of all stakeholders involved in last mile delivery to perform the consolidated delivery in the inner-city area. The Multi-Actor Multi-Criteria Analysis (MAMCA) framework was utilised to assess and rank various delivery configurations involving a combination of eco-friendly delivery vans, trucks and cargobikes based on the objectives of the stakeholders. The weight allocation of the criteria was determined through the Fuzzy Analytic Hierarchy Process (F-AHP) method using responses collected from key actors representing all stakeholder groups in Melbourne, Australia. The multi-stakeholder analysis, which was performed using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method, suggested that the consolidated delivery should be performed using a combination of eco-friendly delivery vans and cargobikes to incorporate the concerns of the societal stakeholders and operational requirements of the business stakeholders. The mono-actor analysis revealed the heterogeneity of the stakeholders&rsquo, preferences and clashing views regarding the optimal delivery fleet. This highlights the importance of incorporating a multi-stakeholder perspective in the planning and selection of suitable urban freight policies. Accordingly, a suitable implementation plan for the consolidated delivery fleet was proposed to reflect the perspectives and requirements of these stakeholders.

In this paper, a review of the recent scientific literature contributions on innovative strategies for last mile logistics, focusing on externalities cost reduction, is presented. Transport is causing problems in urban areas, in particular in freight transport: modern cities need solutions to reduce externalities costs such as congestion, pollution and others, which have increased in the last few years, especially due to the growth of goods delivery. Online sales and globalization lead to new trends in freight transport, and moreover, a larger quantity of goods is expected to be delivered in the next future. In this context, most of the delivered goods end up in the city centers. Last mile logistics is the least efficient stage of the supply chain and comprises up to 28% of the total delivery cost. Therefore, the improvement of last mile logistics and a significant externalities reduction are very important challenges for researchers. New technologies and transport means, innovative techniques and organizational strategies allow handling in a more effective way the last mile delivery in urban areas. Based on the Systematic Literature Review (SLR) method, recent papers that significantly contributed, with original proposals, to the reduction of externalities in urban logistics are identified and analyzed in this work. Furthermore, a classification of the papers dealing with the externality reduction problem is presented. It is consistent with a general formulation proposed to evaluate external costs in urban area. The innovative contributions are classified into five main categories: innovative vehicles, proximity stations or points, collaborative and cooperative urban logistics, optimization of transport management and routing, innovations in public policies and infrastructures. The new paradigm of smart logistics is based on the combination of these concepts and on the proposed innovations.