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Online and omnichannel retail developments placed logistics at the front-end of consumers’ purchase journeys. Particularly the last mile of the supply chain increasingly affects consumer satisfaction, while its financial and environmental impact is critical. “Crowd logistics” is introduced as a promising solution. As consumers are increasingly driving innovation and initiatives in the last mile, it is important to know their preferences and perceptions. Our objective is to identify which type of consumer is interested in a crowdsourced last mile and which particular crowd logistics services are considered interesting. To this end, we set up a survey among a sample of one-thousand consumers that represent the Belgian population. The survey is analysed using descriptive statistics and two-step cluster analysis. Analysis shows that consumers support neighbour relays and delivery by retailers’ employees, but general interest is low. A cluster analysis identifies four attitudinal profiles. One segment, labelled the “trailblazers”, are most likely to adopt crowdsourced last mile services: they strongly prefer delivery at home and rely on their community of neighbours when a delivery fails. They are more interested in last mile innovations and sustainability enhancements. The research contributes by taking a consumer perspective on the last mile and by including three types of services and four types of crowd. Three recommendations for retailers are formulated, to focus on a crowdsourcing solution that combines collection and delivery among their employees’ local network, to target consumers that fit the identified profile and to accentuate crowd logistics’ quality of enhancing information transparency.

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.

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.

Nowadays, online retailers are offering a variety of delivery options consisting of varying combinations of delivery attributes. This study investigates how consumers value these delivery attributes (e.g., delivery speed, time slot, daytime/evening delivery, delivery date, and delivery fee) when selecting a delivery option for their online purchases. Mental accounting theory is used to frame the research and to suggest how mental accounts for money, time, and convenience influence consumer preferences for online delivery options. Specifically, the results of a conjoint analysis show that the most important attribute in shaping consumer preferences is the delivery fee, followed by nonprice delivery attributes. For individual attributes, significant differences are found in consumer preferences between gender and income groups. Cluster analysis reveals three consumer segments that show distinct preference structures: We identify a "price‐oriented," a "time‐ and convenience‐oriented," and a "value‐for‐money‐oriented" consumer segment. This study has practical implications for online retailers when implementing suitable delivery strategies and designing effective delivery options to maximize consumer satisfaction.

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.

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 generalized vehicle routing problem with time windows (GVRPTW) is defined on a directed graph G = ( V , A ) where the vertex set V is partitioned into clusters. One cluster contains only the depot, where is located a homogeneous fleet of vehicles, each with a limited capacity. The other clusters represent customers. A demand is associated with each cluster. Inside a cluster, the vertices represent the possible locations of the customer. A time window is associated with each vertex, during which the visit must take place if the vertex is visited. The objective is to find a set of routes such that the total traveling cost is minimized, exactly one vertex per cluster is visited, and all the capacity and time constraints are respected. This paper presents a set covering formulation for the GVRPTW which is used to provide a column generation based heuristic to solve it. The proposed solving method combines several components including a construction heuristic, a route optimization procedure, local search operators and the generation of negative reduced cost routes. Experimental results on benchmark instances show that the proposed algorithm is efficient and high-quality solutions for instances with up to 120 clusters are obtained within short computation times.

Research background: Artificial intelligence is a term that is now known to almost everyone and is among the trends and innovations of Industry 4.0 for 2020. It is a much-discussed topic in the field of technology. Artificial intelligence and machine training are the driving forces across different industries. In many cases, artificial intelligence helps people in their work and simplifies it or even completely replaces the human workforce. Purpose of the article: The purpose of the article is to state how artificial intelligence can affect and solve existing problems in last mile delivery. For example, inefficiency is a major problem with last mile delivery because the last section of delivery usually involves a number of short-distance stops. However, a long waiting time for the customer to deliver the goods or incorrect allocation of resources and vehicles to the required areas can also be a problem. And it is artificial intelligence that should help solve such problems. Methods: Comparison, Empirical and retrospective analysis are used within the analysis of different modes of last-mile delivery. Findings & Value added: The research results shows the ways in which artificial intelligence can help solve problems in last mile delivery. Examples include The Vehicle Routing optimization (VRO), which aims to calculate the most optimal delivery route or artificial intelligence technology, which is used to interpret various events, manage data, and apply predictive intelligence.

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.

To work well and be sustainable, seed systems have to offer a range of crops and varieties of good quality seed and these products have to reach farmers, no matter how remote or poor they may be. Formal seed sector interventions alone are not delivering the crop portfolio or achieving the social and geographic breadth needed, and the paper argues for focus on informal seed channels and particularly on traders who move &lsquo, potential seed&rsquo, (informal or local seed) even to high stress areas. This paper provides the first in-depth analysis on potential seed trader types and actions, drawing on data collected on 287 traders working in 10 African countries. The research delves into four themes: the types and hierarchies of traders, the technical ways traders manage seed using 11 core practices, the price differential of +50% of potential (local) seed over grain, and the pivotal roles which traders play in remote and crisis contexts. Traders are the backbone of smallholder seed security and need to be engaged, not ignored, in development and relief efforts. An action framework for leveraging seed trader skills is presented, with the paper addressing possible legal and donor constraints for engaging such market actors more fully.

Freight carriers experience major challenges while operating in highly dense inner-city areas. Timely deliveries are crucial for the success of businesses and for the long-term economic growth of metropolitan areas. Previous freight studies have paid little attention to the characteristics of freight movements in a highly dense urban context. Accordingly, this study sought to quantify the operational practices for freight carriers that deliver light parcels to inner-city business receivers. Direct insights were collected using semistructured interviews and an online survey with freight carriers in Melbourne, Australia. The intent was to describe the delivery trips and vehicle types involved in this unique segment. An assessment of operational challenges to the efficiency of freight carriers is presented in the study. In general, freight deliveries to inner-city receivers are characterised by underutilised transport capacity along with a large number of delivery stops. The findings shed light on the challenges that couriers encounter in congested inner-city areas.

Rapid technological developments in autonomous unmanned aerial vehicles (UAV or drones) and an evolving legislation may soon open the way for their large-scale implementation in the last mile delivery of products. The use of drones could drastically decrease labour costs and has been hyped as a potential disruptor to the parcel delivery industry. Online retailers and delivery companies such as Amazon, are already filing up patents for the development of multi-level fulfilment centres for unmanned aerial vehicles or “drone-beehives” that would allow the deployment of this technology within built environment. A substantial amount of research has been carried out in the last years on the potential use of drones for parcel delivery, principally in the area of logistic optimisation. However, little is known about the potential market and economic viability of such services in Europe. This paper presents a modelling framework using EU-wide high-resolution population and land-use data to estimate the potential optimal location of drone-beehives based on economic viability criterion. It estimates the potential number of EU28 citizens that could potentially benefit from last mile-drone delivery services under four scenarios. The performed analyses indicates that under the scenario considered as the most technologically realistic, up to 7% of EU citizens could get access to such services. When considering technological improvements scenarios, the share reaches 30%. Furthermore, results suggest that due to the differences in population and land-use patterns in the different Member States, the potential drone coverage across Europe could be very heterogeneous, with the UK, Germany, Italy and France appearing as the most likely countries where drone-beehives may have the most efficient development.

Despite the huge growth in online purchases, e-grocery (i.e. ordering grocery online) was still limited in scope in Italy so far. More recently, its growth has been substantial and 2020 witnessed a huge increase due to COVID-19-related mobility restrictions. In principle, e-grocery could reduce the number of shopping trips, yet an exponential increase in shipping and deliveries could have a negative impact on the environment. In order to explore the willingness to e-grocery, and delivery preferences (self-delivery, home delivered grocery or collected in a specific place) - and estimate their market shares - a stated preference survey was carried in Rome and Milan. Respondents were asked about their grocery shopping habits and to choose among different shopping and delivery options. Discrete choice modelling allows investigating preference heterogeneity and estimating willingness to pay measures. Main results indicate that respondents, characterised by distinct socio-economic, attitudinal, and geographical elements, react differently to attribute variations for alternative grocery shopping channels. Scenario simulations can help in defining successful business-strategies and possible solutions to external costs. Under this respect, results suggest that the best strategy to increase e-grocery shares in the two cities should be non-monetary, but rather aimed at expanding the product range available online.

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.

Highlights • Holistic analysis of electric light commercial vehicles for low emission transport. • Total cost of ownership of some electric vehicle variants is already favourable now. • High penetration scenarios decrease CO2 and other emissions by 2030 above 3%. • Electric light commercial vehicles can reduce particulate concentrations by ca. 2%. • Besides fiscal support measures, other policies needed to remove market barriers., Transport emissions need to be drastically decreased in order to put Europe on a path towards a long-term climate neutrality. Commercial transport, and especially last mile delivery is expected to grow because of the rise of e-commerce. In this frame, electric light commercial vehicles (eLCVs) can be a promising low-emission solution. Literature holistically analysing the potential of eLCVs as well as related support policies is sparse. This paper attempts to close this research gap. To this aim, the total cost of ownership (TCO) comparisons for eLCVs and benchmark vehicles are performed and support measures that target the improvement of the eLCV TCO are analysed. Various eLCV deployment scenarios until 2030 are explored and their impact on carbon dioxide (CO2) and other pollutant emissions as well as pollutant concentrations are calculated. It is found that while in several European Union (EU) countries eLCVs are already cost competitive, because of fiscal support, some remaining market barriers need to be overcome to pave the way to mass market deployment of eLCVs. High penetration of eLCVs alone can lead to a reduction of total transport CO2 emissions by more than 3% by 2030. For pollutant emissions, such as nitrogen oxide (NOx) and particulate matter (PM), the reduction would be equal or even higher. In the case of PM, this can translate to reductions in concentrations by nearly 2% in several urban areas by 2030. Carefully designed support policies could help to ensure that the potential of eLCVs as a low-emission alternative is fully leveraged in the EU.

Recently, last mile delivery has emerged as an essential process that greatly affects the opportunity of obtaining delivery service market share due to the rapid increase in the business-to-consumer (B2C) service market. Express delivery companies are investing to expand the capacity of hub terminals to handle increasing delivery volume. As for securing massive delivery quantity by investment, companies must examine the profitability between increasing delivery quantity and price. This study proposes two strategies for a company&rsquo, s decision making regarding the adjustment of market density and price by developing a pricing and collaboration model based on the delivery time of the last mile process. A last mile delivery time function of market density is first derived from genetic algorithm (GA)-based simulation results of traveling salesman problem regarding the market density. The pricing model develops a procedure to determine the optimal price, maximizing the profit based on last mile delivery time function. In addition, a collaboration model, where a multi-objective integer programming problem is developed, is proposed to sustain long-term survival for small and medium-sized companies. In this paper, sensitivity analysis demonstrates the effect of delivery environment on the optimal price and profit. Also, a numerical example presents four different scenarios of the collaboration model to determine the applicability and efficiency of the model. These two proposed models present managerial insights for express delivery companies.

The growth of B2C e-commerce market results in the increase of importance of last mile deliveries in the city area. Due to e-commerce's generic specificity, functioning of the deliveries in e-commerce on B2C market is based on home deliveries. Due to influence on the growing demand for deliveries, which consequently could have the impact on traffic and congestion problem as well as city environment, it is important to look for the alternative measures, which will help to reduce this negative impact. In recent years a very interesting and popular solution became parcel lockers as the efficient last mile delivery system. This paper is focused on the assessment of usability of this measure based on the example of InPost company system.

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.

In this paper a review of recent contributions in scientific literature on the last mile logistics is presented. The increase in freight transport and the actual growing trends are responsible, in the urban areas, of a critical increase of congestion, air pollution, noise and others externalities that involve the major cities in the world. New technologies and organizational strategies allow handling in a more efficient way the last mile delivery in urban areas. Papers that contribute significantly and with original proposal in reducing externalities in urban logistics are analysed in this work.

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.

Last mile deliveries are one of the major effectors of heavy traffic of commercial vehicles in the whole city area. Due to e-commerce's generic specificity, its functioning on B2C market is based on home deliveries. In recent years very interesting and popular solution became the parcel lockers as the efficient last mile delivery system. This paper is focused on the analysis of usability and efficiency of this measure based on the example of Polish InPost Company system. It introduces the results of pilot survey realized in Szczecin (Poland), as well as the general expectations regarding the efficient utilization of this kind of solution.

C-LIEGE “Clean Last mile transport and logistics management for smart and efficient local Governments in Europe” is a STEER Intelligent Energy Europe Programme 2010 project focused on developing integrated framework for energy-efficient urban freight transport demand management and planning. C-LIEGE is conceived as a showcase for good practices and a helping hand for European cities striving for cleaner and sustainable urban freight transport and logistics. C-LIEGE provides solutions for decision makers and professionals in Local Authorities and for freight operators. C-LIEGE empowers a cooperative approach between public and private stakeholders targeted on the reduction of energetic and environmental impacts of freight transport in European cities and regions. C-LIEGE successfully developed and tested freight transport demand-oriented measures and decision supporting tools towards reduction of energy, environmental and economic impacts of freight transport in urban environments. A set of integrated solutions and measures were implemented and tested by the support of newly developed C-LIEGE tools: the Stakeholder Engagement Manual, Good Practice Database, Push and Pull Measures Database, Guideline for the development of Urban Freight Mobility Plan as well as the C-LIEGE Toolbox for the establishment of a City Logistics Manager. Seven pilot experiments in six European countries assessed effectiveness of the C-LIEGE approach: Bulgaria, Italy, Poland, United Kingdom, Germany and Malta. The pilot cities selected and implemented a package of demand-oriented measures such as access fees and time windows restrictions, environmental zones, recognition schemes, freight maps, Freight Quality Partnerships, etc. A total of 35 demand-oriented measures were implemented in the C-LIEGE pilot cities, based upon the C-LIEGE toolbox and guidelines. The C-LIEGE pilot sites have introduced a wide range of measures aimed at reducing the impacts of urban freight transport: Fleet Operator Recognition Scheme (FORS) in Newcastle (UK), introduction of access restrictions for heavier freight vehicles in Montana (Bulgaria), new freight mapping in Leicester (UK) accessible via smart phone, re-routing measures in Stuttgart (Germany) as well as Hal-Tarxien (Malta), the establishment of Freight Quality Partnerships (FQPs) as well as Local Freight Development Plans (LFDPs) in all pilot cities. The results achieved in each C-LIEGE pilot site is summarized as follows: decreasing of CO, CO₂, NOₓ and PM10 emissions (tons/year) generated by freight vehicles (Leicester: 15.3%; Newcastle: 9.5%; Stuttgart: 13.2%; Szczecin: 27.8%; Montana: 11.9%; Hal-Tarxien: 10.6%; Piacenza/Emilia-Romagna: 41.2%/44.4%), decreasing fossil fuel consumption (Leicester: 10.5%; Newcastle: 9.4%; Stuttgart: 13.1%; Szczecin: 27.8%; Montana: 11.9%; Hal-Tarxien: 10.5%; Piacenza/Emilia-Romagna: 1.7%/1.5%), decreasing operating costs for freight carriers (Leicester: 6.5% Newcastle: 5.4%; Stuttgart: 7.4%; Szczecin: 18.2%; Montana: 7.7%; Hal-Tarxien: 9.1%; Piacenza/Emilia-Romagna: 17.5%/20.1%). C-LIEGE finally filled the existing gap in know-how and professionalism in the sector by designing, fine-tuning and delivering the complimentary capabilities of City Logistics Manager. For the first time in Europe, the well-known Mobility Manager whose duties are focused on passenger transport only can be paired with a City Logistics Manager. The author is convinced that the C-LIEGE tools and experiences will be of great value for urban freight transport management and logistics in other European cities and regions.