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Sustainable Urban Last-Mile Logistics: A Systematic Literature Review

INESC TEC-Institute for Systems and Computer Engineering, Technology and Science, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
School of Engineering, Polytechnic Institute of Porto, Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2285;
Received: 18 November 2022 / Revised: 10 January 2023 / Accepted: 19 January 2023 / Published: 26 January 2023
(This article belongs to the Special Issue Urban Freight Transport and City Logistics)


Globalisation, urbanisation and the recent COVID-19 pandemic has been raising the demand for logistic activities. This change is affecting the entire supply chain, especially the last-mile step. This step is considered the most expensive and ineffective part of the supply chain and a source of negative economic, environmental and social externalities. This article aims to characterise the sustainable urban last-mile logistics research field through a systematic literature review (N = 102). This wide and holistic review was organised into six thematic clusters that identified the main concepts addressed in the different areas of the last-mile research and the existence of 14 solutions, grouped into three types (vehicular, operational, and organisational solutions). The major findings are that there are no ideal last-mile solutions as their limitations should be further explored by considering the so-called “triple bottom line of sustainability”; the integration and combination of multiple last-mile alternative concepts; or by establishing collaboration schemes that minimise the stakeholders’ conflicting interests.

1. Introduction

Globalisation induced significant changes in how consumers and businesses operate, either it being for facilitating trade in different countries or the possibility to buy products without leaving the house. In fact, more European consumers adopt e-commerce practices each year, with 74% of internet users have shopped online in 2021 [1]. With this trend, consumers’ expectations evolve as they begin demanding more from the e-commerce services in terms of customisation and convenience [2].
This change in consumer and business behaviour has been exacerbated by the recent COVID-19 pandemic and consequent restrictions, furthering increasing the acceptance of e-commerce practices [3]. In this dynamic context, businesses aim to identify competitive opportunities over their competitors by offering their customers faster and cheaper delivery options [4].
The impact of all these factors is reflected in the demand for logistic activities, particularly the last-mile, i.e., the last stretch of a parcel delivery service, from the last logistic infrastructure to the recipient’s destination [5]. The last-mile part of the supply chain is considered very ineffective and expensive, accounting for 13–75% of the full supply chain cost [6]. As expected, the last-mile operations also lead to environmental and social externalities such as air and noise pollution, accidents, and road congestion [7].
These impacts are more visible in urban areas where the pressure is high and will continue to increase due to the growing population and consequent urbanisation. About 60% of the world’s population will be living in urban areas by 2030 [8]. Therefore, there is an urgency to mitigate these internal and external costs.
Although changing the last-mile is not easy because of its multidisciplinary nature, the different academic sectors are studying the current problems of the last-mile logistics and exploring innovative solutions to reinvent the industry, thus optimising these problems. In this context, it is crucial to have a wide and holistic overview of this fragmented research area. Thus, the present paper aims to characterise the sustainable urban last-mile logistic research field through a consolidation and analysis of the existing literature.
The remainder of this paper is structured in five sections. Section 2 describes the methodology for the systematic literature review; Section 3 presents the thematic analysis, synthesising the concepts and results of the academic studies; Section 4 presents the discussion and the characterisation of the research area according to the thematic cluster, the research methodologies adopted, and the sustainability dimensions identifying literature gaps and suggesting new research opportunities; Section 5 summarises the article and presents its limitations.

2. Methodology

A systematic literature review is a methodical, replicable and transparent process helpful in analysing the state-of-the-art of a research field [9,10]. The systematic literature review presented in this article was based on the guideline proposed by Denyer & Tranfield [11]. The process followed is illustrated in Figure 1.
The process begins by defining the scope of the systematic review with the definition of the review questions. They are:
  • RQ1: What sustainable last-mile concepts and solutions have been studied in the recent literature?
  • RQ2: What are the drivers and challenges associated with each last-mile solution?
  • RQ3: How can the last-mile research field be characterised?
The second stage aims to search and create a comprehensive list of documents aligned with the review purposes [11]. The database used in this search was the Web of Science, as it contains a vast collection of publications and most of the journals are peer-reviewed [12]. The search query used was:
  • TS=((“sustaina*” OR “green” OR “emission*” OR “impact*” OR “environmen*” OR “pollut*”) AND (“delivery” OR “freight” OR “logistic” OR “shipp*” OR “distribution” OR “last-mile”) AND (“city” OR “urban*” OR “metropolitan area*”) AND (“business model*” OR “B2C” OR “B2B” OR “business-to-consumer” OR “business-to-business” OR “retail*” OR “e-commerce” OR “brick-and-mortar” OR “omnichannel”)).
This search query was directed to the publications’ title, keywords and abstract. The search was conducted between February and March 2022.
In the third stage, two sequential objective screenings were executed in order to only select scientifically and thematically relevant studies. The first screening consisted in the exclusion of articles: (i) published before 2016; (ii) not written in English; (iii) not open access; and (iv) classified with irrelevant Research Areas, for example, Public, Environmental & Occupational Health; Food Science & Technology and Biodiversity & Conservation.
Then, a second screening was applied to this sample. This screening excluded articles: (i) with an average citation number per year less than or equal to two, if published before 2020; (ii) with an average citation number per year less than or equal to one, if published after 2021; and (iii) where the keywords used in the search query appear less than 10 times in its title, keywords or abstract. This screening resulted in the 102 documents reviewed.
Although the search query and keywords were adjusted several times, it is possible that some relevant articles were not included in the review sample, and therefore not analysed. Defining exclusion criteria may have also contributed to this potential limitation.
The following stages, based on a thematic analysis, provide qualitative insights about the studied field. In order to further characterise the studied research field, each publication was classified according to the conceptual theme(s) it approaches; the geographical context of each study i.e., the country or region that each study focuses on or uses as a case study; and the sustainability dimensions (environmental, economic, and social) considered by the authors. Based on previously established classification schemes [13,14], each study was also classified according to the research methodologies adopted (case studies & interviews, modelling, theoretical, and survey).

3. Results

A co-occurrence analysis helped to identify and cluster the most relevant concepts discussed in the articles. This analysis was based on the capabilities of the VOSviewer software in clustering the articles’ keywords. The result depicted in Figure 2 suggested the six thematic clusters present in the literature sample:
Supply chain & channels (red cluster): contains keywords associated with urban supply chains and different commerce channels;
Delivery methods & attributes (violet cluster): maps the relation between alternative delivery methods and their location and the different perspectives involved;
Innovative vehicles (blue cluster): groups terms related to the adoption of alternative vehicles such as cargo bikes or electric vehicles;
Logistic infrastructures & schemes (yellow cluster): fundamentally related to logistic infrastructures like the Urban Consolidation Centre (UCC) and the associated delivery schemes;
Operational optimisation (red cluster): groups keywords related to operational optimisation such as routing, time windows and efficiency;
Emerging business models (green cluster): aggregates keywords related to innovative business models such as those based on collaboration, sharing economy or crowdsourcing, where the involvement of stakeholders is fundamental.
Figure 2. Co-occurrence map of the literature.
Figure 2. Co-occurrence map of the literature.
Sustainability 15 02285 g002

3.1. Supply Chain & Channels

The characteristics and activities of the supply chain, especially the last segment of it, are studied by different authors. Loiseau et al. [15] compared the environmental performance of different food supply chains, and concluded that a very short supply chain where sales happen directly on the production site has more negative impacts than a national long supply chain or a short supply chain where sales happen via online or via a retailer. de Oliveira et al. [16] and Aljohani & Thompson [17] studied the last-mile delivery practices of freight carriers and found that light commercial vehicles are the most used type of vehicle. Aljohani & Thompson [17] further found out that these vehicles deliver to more than 65 stops per day, and that vehicles operate with about half of the full load capacity, mainly because of the time needed for “placing and readjusting” the parcels and the uncertain availability of on-street loading spaces. Comparable results were presented by Allen et al. [4] and Bates et al. [18] that identified that 34% of the mileage performed by company-owned light commercial vehicles is in the goods transport segment, and there are 37 stops per round, 95% of these being at the kerbside, causing conflicts and infringements. In fact, 62% of the total round time, the vehicle is parked at the kerbside while the driver unloads, sorts and delivers the parcels by foot.
Other researchers opted to develop tools and methods to deepen the knowledge and understanding of the supply chain. Sanchez-Diaz [19] proposed a method for quantifying freight transport trips. The method was applied to examine the freight needs and ordering behaviour of different sectors, allowing to conclude that the retail non-perishable goods sector generated the most freight trips, surpassing other sectors such as the food, the perishable or the public services commercial sectors. Cardenas et al. [20] developed a calculation tool that estimates the associated external costs (congestion, accident, noise, air pollution and climate change) based on the travelled kilometres, and concluded that, although urban areas generate more external costs, rural areas have higher external costs per parcel, due to their low customer geographical density. A causal loop model to understand how external costs are generated was proposed by Hidayatno et al. [21]. Their model depicts that factors like GDP, e-commerce orders, freight volume, logistics transport utilisation, CO2 emissions, traffic congestion, transport costs and packaging are all related through reinforcement feedback loops.
The parcel’s packaging was also highlighted by some authors. Zhang et al. [22] found that a significant share of all waste generated by food delivery services originated from excessive and disposable packaging solutions, while Escursell et al. [23] suggested using cellulose-based materials, 3D printing, or adopting reusable shipping packages as more environmentally conscious packaging alternatives. 3D printing is also pointed out as a solution for reducing packaging waste by Taniguchi et al. [24].
The way that COVID-19 impacted the delivery activities of the supply chain was examined by Villa & Monzon [25] and Milewski & Milewska [26]. According to these authors, the lockdown led to a significant increase in e-commerce orders transported, that in turn, resulted in higher CO2 emissions, but negligible when considering the global reduction. They further pointed out that the demand growth caused by the lockdown increased the efficiency of delivery operations [26].
Besides the COVID-19 pandemic and the challenges mentioned in the last subsections, other factors impacting city logistics are highlighted in the literature. Savelsbergh & Van Woensel [27] identified as factors the population growth and urbanisation, e-commerce growth, the desire for speed, the sharing economy, climate change and sustainability. Bosona [28] added the factor of globalisation as it facilitates good’s trading around the world, increasing the transport distance, and factors related to geographical difficulties and the historical context of the cities. Complementary, Arvianto et al. [29] found out that fleet increment and inadequate loading/unloading spaces are predominantly challenges in developing countries. In contrast, education deficiency, regulation, the emergence of new business models, and network accessibility and capacity are developed countries problems. Urban growth, environmental challenges and traffic congestion are common challenges in both types of economies. Boysen et al. [30] included the ageing workforce is challenging innovation in physically demanding activities such as parcel delivery, while Allen et al. [4] added as the seasonal demand peaks. De Marco et al. [31] analysed and classified European city logistics measures identifying the level of pollution, the diffusion of e-commerce and GDP as important drivers of city logistics measures.
The way that the research community examines these challenges is also discussed. In a literature review, Viu-Roig & Alvarez-Palau [32] classified articles based on the type of impact covered, and concluded that the environmental impact is the dimension most frequently dealt with, followed by the social and the economic impacts. The technological impact is the least considered dimension but is frequently entailed with the other three dimensions. A similar review was conducted by Olsson et al. [14] that yielded disparate conclusions, as economic sustainability is the most covered dimension, followed by environmental sustainability and social sustainability. In a different tone, Feichtinger & Gronalt [33] developed a systematic literature review to identify the factors used for environmental impact assessments. The authors found that the most included factor is the modal split, while the most commonly used way to measure the environmental effects is GHG and CO2 emissions.
The comparison of the various channels according to its impacts or the consumers’ opinions is a topic frequently studied. Shahmohammadi et al. [34] compared shopping models in terms of GHG footprints and concluded that online shopping supported by physical stores reduces the GHG footprints when compared with traditional shopping, while online shopping not supported by physical store has the higher GHG emissions rate. The authors further showed that pure online shopping platforms could significantly reduce their GHG footprint by replacing delivery vans with electric cargo bikes, and by locating their logistical infrastructures closer to their customers. Bjorgen et al. [35] concluded that home deliveries render more environmental benefits than brick-and-mortar, because of fewer trips and reduced car use.
Examining the consumer’s preferences is another way used by academics to differentiate the existing commerce channel modalities. Gatta et al. [36] and de Oliveira et al. [37] studied consumers’ preferences on channel choices and concluded that home delivery is the preferred mode over “click and pick” and brick-and-mortar. A different approach to compare these channels was followed by Lim et al. [5], as they reviewed and compared the commerce channel models, concluding that push-centric models (e.g., home delivery) favour time convenience over physical convenience; pull-centric models (e.g., brick-and-mortar store) prioritise order response time, order visibility, and product returnability performance; and hybrid models (e.g., parcel lockers) prioritise physical over time convenience.
An emerging commerce channel modality mentioned in the literature is omnichannel, i.e., reaching customers through various means of marketing and distribution channels [27]. According to Savelsbergh & Van Woensel [27] omnichannel may enhance the customer experience and increase the customer base, but introduces additional operational complexity for the organisations. Further findings by Bosona [28] identified as challenges associated with this strategy: the fragmentation of online orders, increased complexity of order fulfilment and high associated cost. Wang et al. [38] added that the consumers do not perceive the current omnichannel system as a “seamless” system.
Table 1 summarises this cluster showing that various authors focus on the different aspects of the supply chain, from examining the current practices and challenges, to comparing traditional and novel channels.

3.2. Delivery Methods & Attributes

The study of how deliveries occur is an important topic and has been studied from different perspectives, from proposing alternative methods to examining the consumers’ perspective. Parcel lockers, pick-up points and similar collection and delivery points (CDP) are examples of alternative delivery solutions. Parcel lockers consist of unattended small lockers where parcels are delivered to and stored until the consumer collects them. This solution is widely discussed in the academic literature, as well as being highly implemented [39]. In their work, Savelsbergh & Van Woensel [27] considered this type of solution an opportunity to mitigate the negative effects of direct-to-consumer (attended) deliveries. Some of those adverse effects discussed in the literature are delivery failures and consequent repeated deliveries, and return deliveries, which exacerbate other externalities [4,28].
A key point for the viability of parcel lockers is their location. Lachapelle et al. [40] found that these lockers are frequently placed in commercial streets, sites with abundant parking, and near the post office or shopping centres. They also concluded that most are placed in safe sites and that should be placed more frequently in gas stations or shopping centres, so they can be combined with different purposes. Similar results were drawn by de Oliveira et al. [41] as they concluded that supermarkets and shopping centres are located in high-income areas and in less costly locations for investors, thus making them more economically attractive, whereas post offices, gas stations and drugstores are located in highly populated areas, thus could serve almost the entire city population and stimulate active transportation modes. Kedia et al. [42] added that, although not the preferred location for CDPs dairies (i.e., small convenience stores) could motivate consumers to walk or cycle to collect their parcels, as they are densely located and operate for longer hours.
The location of parcel lockers is also studied based on consumers’ preferences. Researches in Poland [43], Brazil [37] and New Zealand [42] showed that consumers’ preferable locations are in commercial outlets such as shopping centres or supermarkets, mainly because they are part of their daily commute. According to Pronello et al. [44], Italian decision-makers also prefer parcel lockers located inside strategic sites like supermarkets.
Several authors examine consumers’ acceptance and priorities towards parcel lockers. The results of these studies shows that there is general acceptance and willingness to use these alternative delivery methods among New Zealanders [42], Italian [45], Polish [43,46], Brazilian [37] and German [47] consumers. Italian consumers are willing to pay more if the parcel locker is close to their home and has 24 h accessibility [45]. The 24 h accessibility was even identified as the most attractive criteria in Poland [43,46], being prioritised over the price, the location and the delivery speed. Moroz & Polkowski [46] additionally concluded that environmental reasons were the least considered criteria for choosing parcel lockers. A similar study in Brazil returned alternative results by stating that the most important criterion is the traceability of the parcel, followed by the flexible delivery time and reduced cost. Moreover, this study stated that, although home delivery is the preferred option for parcel delivery, the use of parcel lockers is an option with high potential demand [37].
The acceptance and willingness-to-pay towards a customer-driven central last-mile micro-depot model, that acts as a consolidation centre that delivers parcels to the consumers, and as a collection point where consumers pick up the parcels were studied by Hagen & Scheel-Kopeinig [47]. The results showed that consumers would be interested in using it but not paying for it, making the micro-depot not economically viable on its own. A similar model was proposed by Rosenberg et al. [48], which introduced a conceptual shared micro-depot, driven by multiple logistics service providers. Based on existing initiatives, the authors proposed adding auxiliary business models to the micro-depot, such as providing charging stations for electric cars. They stated that the shared micro-depot solution mostly has advantages (e.g., reduction of monetary costs for all parties, noise, GHG and air pollutant emissions) but could have disadvantages (e.g., movement complexity, accidents trackability), and needs stakeholder’s involvement for public acceptance.
Besides the opinion of consumers, the other city actors’ feedback is considered by Russo & Comi [49], Kijewska et al. [50] and Pronello et al. [44]. The first pair [49] interviewed retailers/receivers, and transport and logistics operators to show that most stakeholders have a more positive perspective on measures related to pick-up points like parcel lockers than on measures related to environmental-friendly vehicles or UCCs. In a multi-criteria evaluation of measures for sustainable urban freight transport from the perspective of logistical operators, Kijewska et al. [50] concluded that measures related to alternative delivery systems such as parcel lockers are perceived as positive in terms of implementation possibility and impact on the environment. Pronello et al. [44] found that retailers and most of the large goods transport operators are not interested in the service, but small goods transport operators and the decision-makers see it as efficient.
Other parcel delivery alternatives, classified by Boysen et al. [30] as being emerging concepts, are the reception boxes in a consumer’s home or an Amazon project for smart door locks that allow the deliverer to open the front door of a home with a smartphone app. Another possibility is to deliver into the trunks of private cars. In this area, multiple partnerships have been established between the automobile, logistics and e-commerce sectors [27,30]. Delivering to the consumer’s workplace could be a solution for reducing failed home deliveries [4]. Allen et al. [4] and He & Haasis [39] referred to the solution of mobile depots that can be used as parcel storage facilities as being in the testing and development phase by companies like TNT Express in Brussels.
Some authors opted to compare systems based on parcel lockers against traditional systems. In a simulation study, Milewski & Milewska [26] showed that adopting a parcel locker service can significantly reduce the fuel consumption per parcel, mainly because the number of parcels delivered increases when compared with traditional home delivery. Alves et al. [51] simulated different delivery and re-delivery schemes, concluding that the scenario where parcels lockers were used the most, led to reduced trip length and higher fuel, time, and external costs savings; more parcels delivered without re-delivery; higher profits and lower costs for customers. Arnold et al. [52] simulated and compared two different novel B2C delivery initiatives (parcel lockers and cargo bikes) against traditional home delivery. The results showed that using parcel lockers decreases operational costs at the expense of more (potential) external costs. Because the opposite occurs in the cargo bike scenario, the authors suggested an integration of both modalities. Similar results were obtained by Zhang et al. [53] for the parcel locker scenario.
A common concern pointed out by these researches is that the parcel locker solution might imply additional traffic generated by the customers’ travel to these points, contributing to the external effects of last-mile delivery. However, according to some authors, these effects could be mitigated by implementing a wide network of parcel lockers near frequently visited places, so that the customers do not generate dedicated trips to these points, and to encourage customers to reach them using active modes [46,51,53]
Because delivery activities occur predominantly during the day (when customers are not at home), impacts like traffic congestion or failed deliveries are exacerbated [54]. Therefore, some authors studied the shift towards deliveries in different periods. Lazarevic et al. [55] proposed a 24/7 delivery service and compared its impact versus a traditional service. By surveying consumers and organisations, and by applying simulation tools, the authors concluded that there is considerable interest in the service and that it could lead to lower diesel consumption and a consequent decrement in CO2 emissions. Mousavi et al. [54] conducted a pilot for an off-peak delivery program i.e., parcels are delivered during the evening and overnight hours, that revealed faster delivery speed, zero noise complaints, and lower GHG and other air pollutants emissions. However, service times increased in the off-peak hours at the retail stores because it coincides with other activities.
de Oliveira & de Oliveira [56] took a different approach to assess the off-peak delivery alternative by surveying stakeholders’ preferences and perceptions regarding different city logistics solutions. The authors discovered that off-peak delivery was perceived as efficient by residents and administrators, but as not efficient by carriers and retailers. In another study, de Oliveira et al. [16], corroborated the retailers’ stance toward off-peak delivery. Different results were listed by Kijewska et al. [50], whose evaluation of logistical operators’ opinions showed that alternative delivery systems like night deliveries are considered positive, as they view it as a solution with high implementation possibility and high environmental benefits. However, the practical implementation of this solution may not be that easy according to the findings of De Marco et al. [31], as they found that night delivery was not implemented in most studied European cities.
Several authors focused on examining the delivery attributes associated with delivery services like parcel lockers or home delivery [36,37,57,58]. Caspersen & Navrud [57] concluded that consumers accept slower deliveries in return for less polluting methods, and prioritise the parcel’s traceability over the delivery time, delays or emissions. In Brazil, sociodemographic characteristics such as age or income, and the product purchased influence which attributes are prioritised in home delivery, according to Dias et al. [58]. Another Brazil-based study [37] stated that information and traceability of the parcel, followed by flexible delivery time and reduced cost are the most important criteria for consumers, while factors like product price and range, and service cost are more important when choosing the channel than travel time, lead time or time window to Shanghai consumers [36].
Table 2 summarises the studies in this cluster.

3.3. Innovative Vehicles

The adoption of alternative vehicles in logistics is a concept well disseminated in the literature. Different authors analyse alternative fuel vehicles like electric vehicles or cargo bikes, but also novel vehicular technologies such as drones or autonomous vehicles (AV). Alternative fuel vehicles are an increasingly important part of the transportation system, with the potential to provide significant benefits [24,27]. Patella et al. [59] and de Oliveira et al. [60] showed that adopting green vehicles in urban logistics has gathered increasing interest, specifically in using vehicles powered by alternative fuels, such as electric vehicles. Multiple authors simulated and compared the performance of electric and traditional logistical trucks using real-life data from the food sector in New York City [61] and Berlin [62]. These authors concluded that adopting electric vehicles significantly reduces energy consumption and GHG emissions. Similar comparative-based studies [63,64,65] further added more evidence that electric vehicles have lower environmental and operational costs than traditional vehicles.
Several authors have discussed the challenges in the adoption of electric vehicles in last-mile operations. Anosike et al. [66] identified that operational barriers like the limited driving range; battery issues such as long recharging times; and cost implications such as a high investment cost are among the types of obstacles most commonly associated with the use of these alternative vehicles, while Bates et al. [18] and Bosona [28] identified as challenges against innovation, the infrastructural and financial complexity of replacing the vehicle fleet with a more sustainable one, namely due to the need for recharging stations and the high fleet acquisition cost. The limited driving range issue is refuted by Martins-Turner et al. [62] that concluded that the electric vehicles’ battery duration suits most operations. A field experiments conducted by Iwan et al. [67] added evidence to the claim that the battery capacity of electric vehicles is suitable for last-mile deliveries. Moreover, Settey et al. [68] showed that electric vehicles’ driving range could be enhanced if they are recharged during loading/unloading.
Cargo bikes are another popular vehicular mode in the literature. Field tests conducted by Nurnberg [69], allowed the author to conclude that cargo bikes can help to decrease congestion, noise and air pollution, but needed adequate road infrastructure and policies, community approval, and have to be adapted to the terrain and tasks. The speed and capacity limitations of cargo bikes, and the need for new road infrastructure are also highlighted by Bosona’s [28] literature review as the main disadvantages associated with cargo bikes. Brotcorne et al. [65] analysed the co-existence of traditional and green vehicles in urban logistics, from a managerial perspective, and concluded that cargo bikes are the vehicular mode associated with higher environmental and operational savings but correspond to a lower number of deliveries per hour.
In a simulation study, Arnold et al. [52] found that cargo bikes resulted in an increase in operational costs but a decrease in external costs when compared to home deliveries using traditional vans. Because the opposite occurs in the parcel locker scenario, the academics suggested an integration of both modalities. Contradicting results by Zhang et al. [53] in Berlin, as the use of cargo bikes decreased both operational and environmental costs.
Some literature reviews showed that emerging vehicular technologies such as drones, autonomous vehicles, and modular vehicles are being studied by multiple researchers [28,59,60]. In particular, Patella et al. [59] classified autonomous vehicles as the most promising and challenging solution for last-mile logistics. However, according to Savelsbergh & Van Woensel [27], their benefits for city logistics, how to effectively employ them, and how to integrate them with traditional vehicles are still unknown. Serrano-Hernandez et al. [70] concluded that residents prefer unmanned aerial vehicles like drones in last-mile operations over cargo bikes or traditional vans. Complementary, in a literature review Bosona’s [28] identified that drone-based delivery implies additional investments such as landing stations, while Savelsbergh & Van Woensel [27] cites Toyota, Amazon and Matternet as examples of companies investing in the use of unmanned aerial vehicles on parcel delivery.
Some of the alternative vehicular technologies were classified according to their academic investigation status and practical implementation status by He & Haasis [39]. Electric vehicles are on a high level of application and research; cargo bikes have received medium academic interest but high practical implementation; and drones, autonomous vehicles or modular vehicles are not highly investigated nor highly implemented. These results converge to the ones drawn by Boysen et al. [30] that classified electric vehicles and cargo bikes as “today’s concept”, drones and small autonomous robots as “near future” concepts, while autonomous vehicles as “farther future” concept. De Marco et al. [31] found that measures related to the adoption of low-emission vehicles are the most implemented type of city logistic measure, being present in more than 50% of the 70 studied European cities. Moreover, according to Arvianto et al. [29], examining novel vehicular technologies like delivery robots, automated vehicles or electric vehicles as innovative solutions for city logistics is more common in developed countries than developing countries.
Table 3 characterises the studies focused on innovative vehicles.

3.4. Logistic Infrastructures & Schemes

Logistic infrastructures are a very important part of any supply chain. One of the most implemented and studied logistic infrastructures is the Urban Consolidation Centre (UCC). The UCC is one of the opportunities for improving city logistics, primarily by consolidating the fragmented deliveries, thus reducing the freight vehicle volume going into cities [27]. De Marco et al. [31] added that UCCs are implemented in 50% of the 70 European cities they studied, making it the second most implemented city logistic measure, only below the adoption of low emission vehicles.
Different studies evaluated the pros and cons associated with the UCC from different perspectives. In a social cost-benefit analysis of an operational UCC conducted, Kin et al. [71] revealed that the UCC initiative has social and environmental benefits, but is not economically viable, mainly due to high initial costs. However, the authors calculated that the UCC becomes financially viable when the dealt volume increases significantly. Similar conclusions were drawn by other authors. van Duin et al. [72] designed an analysis framework to evaluate UCCs, and then applied it to describe three UCC city initiatives. Bristol-Bath UCC and Binnenstad Nijmegen UCC initiatives supported the thesis that, although there are social and environmental benefits, most UCCs are not financially attractive solutions, as they need public subsidies to “break-even” or generate small profits. However, the Regent St. UCC initiative claimed relevant profits. In another study by Bjorklund et al. [73], two of the five European UCC cases analysed are not financially viable. In a survey-based study of online shopping practices, Cherrett et al. [74] suggested that courier vehicle trips could be significantly reduced by using a consolidation scheme paid by university students and that students would respond positively to this service.
The previous authors also identified seven critical factors for viable business models, of which three stand out: scale up the operations, logistics competence and the use of advanced IT and information systems [73]. These authors stressed the importance of local authorities and municipalities engaging in the initiative. The scale of operations as a critical factor is also highlighted by Estrada & Roca-Riu [75] that analytically studied the necessary conditions for sustainable consolidation schemes, and concluded that a minimal retailer density is needed to ensure positive financial status whereas vehicle costs and other site-related parameters have minor impact on the financial viability of UCCs. The authors further found that consolidation strategies could alleviate the negative externalities, as well as provide cost savings for the carriers, as they exceeded the cost of participating in these strategies.
Guerlain et al. [76] showed that implementing consolidation centres in urban areas could improve other sectors, namely the construction sector. They simulated the implementation of this consolidation centre in four European cities and found benefits in terms of congestion, pollutant emissions, vehicle use and load factor. Interestingly, the results demonstrated that three of the four construction sector consolidation centres evaluated have a Payback period equal to 1 i.e., it takes one year to recover the investment cost. An alternative approach was followed by Deng et al. [77] that compared the performance of a UCC and a Peer-to-Peer platform (i.e., a capacity sharing-based platform) and found that the UCC is more profitable and more social-environmental efficient if the carriers’ variable delivery cost and the number of carriers are both sufficiently high.
The perspective of stakeholders towards UCC initiatives is also the basis for some studies, like the ones led by Paddeu [78,79] based on the Bristol-Bath UCC, that pointed out that retailers are very satisfied with the overall service, and that most of them are unaware of what a consolidation centre is or how it works, while some retailers complained about the impossibility to set the delivery time and that some parcels were getting damaged. Russo & Comi [49] found that supply management measures like the implementation of UCCs are associated with average low benefits by the stakeholders. In Brazil, the UCC is perceived as efficient by carriers and administrators [56], and stakeholders consider criteria like the availability of parking spots, the use of technology or the service level more important in UCC planning in historical cities than insecurity, noise or traffic congestion [80].
In a research aimed at identifying the drivers and barriers associated with a UCC by analysing the perspective of retailers operating in the city of Bristol (with a UCC) and the city of Cagliari (without a UCC), the authors identified as drivers, aspects like the time savings or the pro-environmental principles, and as barriers, factors like the competitiveness or the public subsidies’ dependence [81]. Johansson & Bjorklund [82] indicate that the most important driver to convince retailers to participate in UCCs is the possibility to outsource some services and thus gain economic advantages.
Hagen & Scheel-Kopeinig [47] and Rosenberg et al. [48] studied the viability of a micro-depot that acts as a consolidation centre and as a parcel collection point. The first academics found that, although consumers would be willing to use it, the micro-depot would not be economically viable because consumers would not pay for it, while the second authors remarked that the shared micro-depot solution that they proposed would have economic viability and social and environmental benefits, but could increase operational complexity.
Another pivotal urban infrastructure is freight loading/unloading parking spaces, an infrastructure particularly challenging to change in order to adapt to the increasing freight volume and changing distribution systems [28]. In fact, Dalla Chiara & Cheah [83] considered arrival rates, parking duration, queue waiting time and driver parking location choice to document evidence of congestion at these spots. These infrastructures were studied in the city centres of Poland [50,84], Singapore [83], Brazil [16,56], Italy [44] and multiple European countries [31].
To study these infrastructures, some authors considered the perspective of the main players. Kijewska & Iwan [84] found that inappropriate or unavailable loading/unloading space for delivery vehicles is the biggest obstacle pointed out by retailers, and de Oliveira & de Oliveira [56] found that carriers classify exclusive loading/unloading locations as efficient while carriers, retailers and administrators perceive reservation-based loading/unloading systems as efficient. In another survey, de Oliveira et al. [16] added evidence that most retailers perceive the unavailability of loading/unloading parking areas as an impactful problem, therefore they are willing to accept the regulation of loading and unloading areas. Nevertheless, Pronello et al. [44] point out that, although the loading/unloading bays are perceived by stakeholders as obstacles to efficient delivery operations, their booking is not appreciated as it would increase the complexity of the deliveries. Parallel results obtained by Russo & Comi [49] and Kijewska et al. [50] showed that measures related to infrastructural delivery areas like loading/unloading areas are not considered by most stakeholders as very positive measures when compared to measures related to alternative delivery systems, collaboration schemes or the use of technological systems. With a different approach, De Marco et al. [31] confirmed the lack of interest in parking-related measures such as monitoring, booking or dedicated roadside lay-by areas, as the authors found that this type of measures is implemented in less than 20% of the considered set of 70 European cities.
The most omnipresent urban logistic infrastructure is the road. Therefore, some authors studied exclusive freight lanes or other mobility restrictions as a solution for improving road use. de Oliveira & de Oliveira [56] surveyed stakeholders’ preferences and perceptions and stated that exclusive freight lanes are perceived as efficient by carriers, retailers and administrators. According to de Oliveira et al. [16] most surveyed retailers agree that the restriction of vehicle circulation is a viable solution. Russo & Comi [49] found that stakeholders are interested in limited traffic zones. The pair also found that measures related to environment-friendly vehicles such as using the vehicle environmental performance as an access constraint are perceived as efficient by city users, but not by retailers or logistics operators, contradicting Pronello et al. [44] which presented that using the vehicle’s emissions as a criterion to permit access to limited traffic zones is consensual among stakeholders while using criteria like the loading factor is not. Taniguchi et al. [24] wrote that applying direct road charging measures such as tolls can lead to more efficient utilisation of freight vehicles and avoid the need for additional warehouses. De Marco et al. [31] analysed European city logistics measures and found that low-emission zones are implemented in almost half of the studied cities, while dedicated freight lanes are the least implemented measure.
Hesse [85] and Taniguchi et al. [24] approached the spatial context of logistics, discussing the logistics sprawl problem. This problem can increase the travelled distance due to the lack of affordable logistics infrastructures in central and inner urban areas [4].
The cluster is summarised in Table 4.

3.5. Operational Optimisation

Urban infrastructures like freight parking spaces are intrinsically linked to fleet operations. Some academics study these operations as an optimisation problem. Dalla Chiara et al. [86] designed a random utility model to optimise urban freight parking. Based on simulations, the authors concluded that reducing parking duration, and parking in spaces reserved for passenger vehicles can reduce issues like accidents, congestion, air pollution, delivery costs, and illegal parking. Diana et al. [87] developed a geolocation-based method to optimise urban freight loading and unloading areas’ examination using a clustering algorithm with criteria like the number of vehicles or the street characteristics, aimed at the identification of the most important locations for logistic operations.
Another fleet operation whose optimisation could have a significant impact is vehicle routing. Although measures related to routing or scheduling are among the least implemented measures in Europe [31], and are more relevant in developing countries [29], in the literature, there are different authors focusing on the Vehicle Routing Problem. Rincon-Garcia et al. [88] introduced a time-dependent vehicle routing optimisation model based on a large neighbourhood search algorithm that reduces the number of operating vehicles, as well as the route length and duration. Moreover, the authors found that the cost and the CO2 emissions substantially increase if a time window is imposed. Cerrone et al. [89] demonstrated through a routing optimisation model that applying street crossing penalties does not affect the routes’ cost and total length. Two articles used genetic algorithms to develop models for fleet management optimisation. The model proposed by Yang & Wu [90] optimised the routing of logistical vehicles and showed that the time windows exigencies affect negatively the total route length, while the model proposed by Wang & Bae [91] pointed out that a smaller number of vehicles can decrease the operational costs, but at the cost of an increase of time windows failures.
Different publications have explored the potential that emerging technologies and techniques like the use of emerging data sources, tracking technologies, APIs and mobile applications, or cloud-based technologies have on optimising logistical operations. Savelsbergh & Van Woensel [27] state that digital connectivity, big data and automation can drive city logistics innovations in order to decrease the negative effects on congestion, safety and the environment, while Bosona [28] writes that digitalisation and automation could result in more efficient, flexible and customer-focused supply chains, reducing externalities like delivery failures.
Pan et al. [92] outlined a model based on data mining the electricity consumption of the customers’ residences in order to predict if they are at home. The results revealed that the proposed model could not only reduce the number of failed deliveries, but also the total route length of last-mile operations. Taniguchi et al. [24] contributed by describing other applications of big data systems and decision support systems found in the literature. de la Torre et al. [93] found applications of simulation techniques, machine learning and fuzzy-based methods in the optimisation of supply chains, transportation services, crowdsourcing logistics, autonomous and electric vehicles, among others. The authors concluded that, because of the different sustainability dimensions to be considered, it is unlikely that the transportation system can be improved using a single method.
Different hardware technologies have been used to improve last-mile operations. As concluded by Perboli & Rosano [94], RFID and GPS-based technologies are widely adopted in smart city projects in Europe, whereas ICT-based models, databases and cloud computing are the most used technologies in projects in USA and Canada. Giusti et al. [95] summarised and listed the outcomes of the multimodality transportation project SYNCHRO-NET. This platform is supported by cloud technology and a set of simulation and optimisation software that can improve freight and logistics management in real-time. Noteworthy results are the reduction of the route length and duration, and CO2 emissions.
Hardware is frequently combined with software such as machine learning and simulation models. Gutierrez-Franco et al. [96] proposed a data-and-model-driven framework for vehicle-related operations optimisation. This framework relies on hardware (RFID, GPS); software (e.g., ERP, WMS, GIS); and machine learning, simulation and optimisation models. Reducing the number of vehicles in use, increasing the resource capacity utilisation and reducing the cost of fleet operations are some of the advantages the authors listed. The use of apps and APIs is also the subject of studies. Mkansi et al. [97] assessed the impact that mobile applications can have in the optimisation of e-grocery logistics, namely in managing demand and cooperation between competitors. de Kervenoael et al. [98] examined practices of independent delivery workers, and stated that the combination of internal technological systems such as parcel QR codes, logging data, or tracking technologies, with external applications like Google Maps or WhatsApp could make logistics more sustainable. Munoz-Villamizar et al. [99] proposed a model based on Google API to measure the effects of disruptions in last-mile operations. The model was computationally validated on a set of real data from different cities and allowed the authors to conclude that cities with larger sizes, limited road networks, and high customer concentration zones are more sensitive to disruptions.
With a different approach, Pronello et al. [44] analysed the stakeholders’ need for freight optimisation apps, and concluded that the only valuable information for transport operators is information about traffic disruptions, the status of loading/unloading bays, video surveillance and apps that suggest less polluting routes. A similar approach was followed by Russo & Comi [49], as they found that the city stakeholders expect positive benefits from the use of information and communication technology and intelligent transport systems such as apps for booking delivery bays or traffic management.
Different publications have explored how novel technologies and techniques can optimise last-mile operations like vehicle routing. These are summarised in Table 5, which depicts the geographical context, method and sustainability dimension considered.

3.6. Emerging Business Models

Emerging business models have been studied and proposed by various authors. These studies are focused on vertical collaboration schemes like crowdsourcing logistics or the combined transportation of people and freight, as well as horizontal collaboration, for instance, two companies sharing assets [100].
Crowdsourcing logistics i.e., the outsourcing of logistic services to a network of people, with benefits for all parties [101], is the emerging initiative most present in the reviewed literature, being classified by Boysen et al. [30] as a “Near future” concept. Several of the crowdsourcing models proposed are based on exploiting public transport systems for the last-mile delivery operations. Chen & Pan [102] designed a system that supports the implementation of a crowdsourcing model using taxi drivers, data mining and algorithms to optimise routing and scheduling of tasks.
Gatta et al. [103] designed a crowdsourcing logistics model where metro passengers deliver parcels using parcel lockers placed inside or near the metro station. This model could lead to environmental benefits, but could only be economically viable if public incentives and subsidies were applied. The same model was used by Gatta et al. [104] to examine the willingness to act as a crowdshipper and to use this delivery service. The results of the study demonstrated that the crowdshippers prioritise the location of the parcel locker over the remuneration per delivery, while the users prefer flexible delivery time windows over cheaper shipping fees or faster shipping time. This study also found that younger people are more willing to work as a crowdshipper and to use this crowdsourcing logistics service.
Seghezzi et al. [105] benchmarked the economic performance of a crowdsourcing system and a traditional express delivery system. The results showed that the average cost per delivery of the crowdsourcing system is lower for any service level, number of workers and vehicle mix except for a “100% foot” model. The authors further concluded that a crowdsourcing initiative generates a source of additional income for the deliverers. Guo et al. [106] proposed a conceptual framework aimed at supporting the integration of crowdsourcing practices into a traditional delivery network. According to these authors, even if an exclusive crowdsourcing system is not able to completely replace the traditional delivery system, the proposed integration could help reduce the economic and environmental last-mile impacts, at the expense of needing a large number of crowdshippers. This need is also pointed out by Savelsbergh & Van Woensel [27], that included crowdsourcing in their list of opportunities for improving city logistics, adding that the compensation for the worker has an impact on the effectiveness of the solution. Bates et al. [18] alerted that this type of initiative could lead to social injustices common with zero-hour contracts, such as low income and lack of benefits or legal support.
Rzesny-Cieplinska & Szmelter-Jarosz [107] contributed to the research field by benchmarking existing crowdsourcing services according to the needs of different stakeholders. The pair concluded that the AmazonFlex initiative had the most valuable characteristics, as the stakeholders associate it with social benefits such as security or creating a local community. Allen et al. [4] stated that, although crowdsourcing is one of the initiatives that can improve last-mile operations by reducing vehicle activity, the emergence of crowdsourcing services by large companies like Uber and Amazon threatens to change the sustainable nature of crowdsourcing logistics and result in dedicated vehicle trips specifically for parcel delivery.
Another “Near future” concept listed by Boysen et al. [30], and considered by Savelsbergh & Van Woensel [27] as having “enormous potential for exciting research” is the combined and integrated transport of people and freight. This solution takes advantage of the public transport infrastructures to deliver parcels and is already being implemented in countries like Switzerland and Japan [24,100].
This initiative is being considered, evaluated and compared by various authors. Villa & Monzon [108] assessed it by proposing a novel model for e-commerce parcel delivery based on the underground metro infrastructure. They compared two scenarios (combining people and goods, and using dedicated trains) with the status-quo scenario (delivery by road transit). The results demonstrated significant reductions in congestion costs, accidents, noise, and air emissions when adopting a metro-based delivery model, in particular, the shared train scenario. Beirigo et al. [109] modelled this integration using mixed-purpose compartmentalised autonomous vehicles. The simulation of various scenarios with different characteristics allowed to conclude that almost every scenario resulted in higher operational profits when compared to a model without people-freight integration. Cheng et al. [110] proposed two delivery methods (utilising the minimum and maximum amount of free capacity of each trip) based on the use of public transportation to move passengers and parcels. Analytical and experimental results showed that it was possible to distribute most packages, in under 1 h in off-peak periods and with little impact on the passenger.
The free capacity of public transport is also studied by Van Duin et al. [111] that conducted a pilot project to study the viability of using public buses to carry parcels and found that this solution led to lower CO2 emissions, the creation of job opportunities and a sustainable business model. Moreover, Taniguchi et al. [24] stated that this initiative could bring benefits for public transport organisations as it can be an additional revenue stream; logistic organisations would benefit by reducing the transport costs and increasing the frequency and reliability of deliveries; and residents would experience less congestion, noise and air pollution. However, this solution involves extra transshipment costs, additional handling equipment and additional labour for loading/unloading and security tasks.
The idea of using the free capacity is also adopted when developing business models based on collaboration and sharing economy principles. Allen et al. [4] and Savelsbergh & Van Woensel [27] stated that fostering operational collaboration between carriers in order to reduce the number of operating vehicles or increase resource utilisation efficiency is one of the solutions to improve the parcel delivery operations, while Bosona [28] stressed the difficulty in addressing the different competing interests of urban freight logistics actors, and the difficulty in establishing coordination between these actors due to the uncertain and dynamic nature of freight operations. Kin et al. [112] simulated the operational feasibility of utilising the free capacity of cargo trucks to supply small independent stores and found that it potentially provides an additional revenue source as well as reduces the travelled distances and lead times, in specific, when adopting a centrally located logistic centre. Also using a simulation-based study, Zissis et al. [113] concluded that a collaboration model based on retailers sharing fleets and using micro hubs around residential areas, could lead to reductions in distance and operation time, by the use of fewer vehicles.
Enochsson et al. [114] explored the topic of sharing economy across different actors, segments and cities, affirming that municipal governments and organisations are, in general, supportive of sharing economy principles, as they could lead to sustainability benefits, as well as being a solution for the last-mile problem. Similarly, Russo & Comi’s [49] assessment of city users, retailers/receivers and logistical operators’ expected outcomes of a set of city logistics measures showed that public-private collaboration measures are expected to produce high benefits.
Table 6 summarises the concepts discussed, the geographical context, the methodological choices and the sustainability dimensions explored in this cluster.

4. Discussion

The literature review constitutes a significant piece of knowledge in the form of a holistic collection of various insights about last-mile research. These range from identifying which last-mile concepts and solutions have emerged in recent years (RQ1) to what are the solutions’ advantages and disadvantages (RQ2). This last insight is an important contribution, as it provides a very practical overview of the different last-mile solutions. The advantages and disadvantages of the main last-mile solutions discussed in the reviewed literature are listed in Table 7.
The characterisation of the research field was deepened by classifying the literature sample according to the conceptual theme, the geographical context, the research methodologies adopted and the sustainability dimension considered by the authors, and therefore answer RQ3. This classification is summarised in Table 8, depicting the number of articles, and the frequency of each type of method and dimension present in each cluster.
Different types of solutions were identified: Vehicular solutions like electric vehicles; Operational solutions like off-peak delivery; and Organisational solutions like the UCC. All types of solutions have advantages that can improve these operations, however, they also have disadvantages, usually related to high financial and infrastructural requirements, or the lack of consensus between stakeholders. This adds evidence for the complexity of the last-mile problem as, although there are many strong solutions, there is not a perfect solution. The minimisation of the disadvantages could lead to key research developments. For example, different studies identified technical deficiencies in cargo bikes [28,65,69], but investigating if these deficiencies can be suppressed by having adequate infrastructure was rarely addressed.
The integration and combination of multiple solutions is pointed out in the literature as a way to minimise these disadvantages. For instance, designing a delivery service based on sustainable alternatives like parcel lockers and cargo bikes, or based on integrating these alternatives into a traditional network. These combined systems could create a symbiosis environment where the advantages of one solution ‘cancel’ the disadvantages of the other. Some combined solutions have already been studied (e.g., cargo bikes and delivery points [52]), however, other interesting solutions could emerge by integrating emerging technological concepts like IoT, AI, and Industry 4.0 into the logistics sector. For example, exploiting blockchain technology to trace and track the last-mile operations could provide valuable insights for better evaluation of its impacts.
The vast majority of the publications are classified with just one cluster (76%), which suggests that there is a research gap regarding this combination/integration of multiple concepts. Hence, future research focused on the interplay and relations among the various innovative concepts is needed.
Other topics scantly assessed like the impacts caused by product returns; delivery failures; accidents involving people, products and property; and packaging solutions, although they could be considered secondary problems of the last-mile, could be the focus of interesting studies needed to achieve sustainable solutions in all three dimensions. Studying the problem of last-mile operations in different city areas like the historic centre, by identifying which criteria and solutions should be prioritised in each context, is almost absent in the literature analysed.
The number of publications in each cluster is relatively similar, pointing out the diversity of areas of the studied topic, as well as, the effectiveness of the followed systematic literature review methodology in collecting a comprehensive array of the concepts associated with the last-mile. Because there is a significant number of articles in clusters (ii) Delivery methods & attributes and (iv) Logistic infrastructures & schemes, concepts like parcel lockers and UCC seem to be the most consolidated last-mile solutions.
The clusters with the least associated publications are the (iii) Emerging business models, (v) Innovative vehicles, and (vi) Operational optimisation. Although these clusters include consolidated solutions like electric vehicles and cargo bikes, it also includes very novel and less explored concepts like drones and autonomous vehicles, and emerging concepts like crowdsourcing logistics or the broad use of IT systems. As research on these topics is dependent on technological advances or legal and political support that is yet to emerge, the research is still in its infancy. For instance, research on a solution like drone delivery is limited either because there are still no concrete regulations, or because there is still no weather-proof technology.
In fact, the small share of theoretical articles reveals that the overall last-mile logistics research is still an emergent topic. In this context, and because theory is undoubtedly crucial for the development and maturation of any field, researchers should devote more effort to studying last-mile logistics through a theoretical lens. Furthermore, case studies, in particular real-life experiments, can particularly help the maturation of emerging vehicular solutions like drones.
The focus on the economic dimension could indicate that the primary motivation for exploring and introducing new solutions is the generation of higher profits and lower operational costs. However, it also stresses the importance of financial viability when proposing a novel system; when evaluating infrastructures like the UCC; or when calculating the cost savings returned by a routing optimisation model. Nevertheless, improving the economic dimension can worsen the social or environmental dimensions. This points out that, although different novel business models have been developed to address the new challenges of modern society, more complete business models are needed to make solutions like the omnichannel, the combined transport of people and freight, or UCCs economically viable without affecting its sustainable principles. In fact, this lack of complete solutions is suggested in the results, as more than half of the studies (57%) do not consider (simultaneously) the three sustainability dimensions.
Collaboration can be the answer to achieve these complete three-dimensional sustainable solutions, and although there is already literature on how collaboration can help, its actual feasibility is still very challenging. The major challenge is creating a collaborative system that pleases all involved stakeholders, as each has not only distinct interests but also different modus operandi.
The lack of consensus among stakeholders is a significant challenge for innovation as it is the involvement of different stakeholders with different perspectives that is the key to the definition of the goals, the effectiveness of the implementation, and the legitimacy and credibility of the process. Therefore, models that integrate a larger number of stakeholders are required, as their absence strongly limits the benefits of the last-mile solutions. Surveys contemplating this wider variety of stakeholders can be a good initial step that could pave the way to a better understanding of the conflicting objectives involved.
Moreover, establishing partnerships between the industry, public administration, and academic sectors where, for example, real delivery data is shared, could also be beneficial to create more complete and accurate models. However, the mechanisms related to data sharing and data privacy need to be carefully addressed.
The relative lack of studies focused on the social dimension should be highlighted, especially on a topic such as last-mile delivery where consumers are part of the problem and can be part of the solution. At this level, solutions that can yield significant benefits like crowdsourcing logistics require more research. For instance, studying the link between crowdsourcing initiatives and social inequalities, or how big companies like Amazon could adopt these initiatives without altering its sustainable principles.
Survey-based or theoretical studies from a marketing and sociology perspective could help identify effective transition pathways in order to encourage companies, consumers, and authorities to adopt sustainable methods like the use of parcel lockers.

5. Conclusions

This paper provided a systematic literature review that aims to characterise the sustainable urban last-mile logistic research field through a consolidation and analysis of the existing literature (2016–2022). The review followed a methodology based on the Web of Science database and sets of objective exclusion criteria. This procedure resulted in 102 articles of interest. Each article was classified according to the thematic cluster, the sustainability dimensions considered and the research methodologies followed.
The six thematic clusters discussed a wide variety of concepts like examining the current practices or developing tools to evaluate the supply chain; studying parcel lockers or the attributes of the delivery systems; examining innovative vehicles and infrastructures like electric vehicles and UCCs; exploring the use of technology in logistical operations; or the proposal of novel business models based on collaboration. Moreover, three types of solutions were identified: Vehicular solutions like drones; Operational solutions such as off-peak delivery; and Organisational solutions like crowdsourcing logistics.
The research field is characterised by its multidisciplinary nature, encompassing a multitude of concepts and solutions discussed under very different perspectives and methodologies, however, there are still various research gaps and opportunities remaining for deepening the knowledge on sustainable urban last-mile logistics. Further research is particularly required in domains like the exploration of the so-called “triple bottom line of sustainability”; the integration and combination of multiple last-mile alternative concepts; or the establishment of collaboration schemes that minimise the stakeholders’ conflicting objectives.

Author Contributions

Conceptualization, V.S., A.A. and T.F.; methodology, V.S., A.A. and T.F.; validation, V.S., A.A. and T.F.; formal analysis, V.S.; investigation, V.S.; data curation, V.S.; writing—original draft preparation, V.S.; writing—review and editing, V.S., A.A. and T.F.; supervision, A.A. and T.F. All authors have read and agreed to the published version of the manuscript.


This work is financed by National Funds through the FCT–Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the e-LOG project (EXPL/ECI-TRA/0679/2021). Tânia Fontes also thanks FCT for the Post-Doctoral scholarship SFRH/BPD/109426/2015.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


The following abbreviations are used in this manuscript:
AI Artificial Intelligence
API Application Programming Interface
AV Autonomous Vehicle
B2B Business-to-Business
B2C Business-to-Consumer
CDP Collection and Delivery Points
ERP Enterprise Resource Planning
GDP Gross domestic product
GHG Greenhouse Gas
GIS Geographic Information System
GPS Global Positioning System
ICT Information and Communications Technology
IoT Internet of Things
QR Quick Response
RFID Radio-frequency Identification
TKA Title, Keywords and Abstract
UCC Urban Consolidation Centre
WMS Warehouse Management System


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Figure 1. Systematic literature review methodology followed. 1 For example: Public, Environmental & Occupational Health; Food Science & Technology; Biodiversity & Conservation. 2 TKA: Title, Keywords and Abstract.
Figure 1. Systematic literature review methodology followed. 1 For example: Public, Environmental & Occupational Health; Food Science & Technology; Biodiversity & Conservation. 2 TKA: Title, Keywords and Abstract.
Sustainability 15 02285 g001
Table 1. Supply chain & channels literature summary.
Table 1. Supply chain & channels literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[17]PracticesAustraliaC, S
[4]Practices, ChallengesEnglandC, T
[29]Challenges T
[18]PracticesEnglandC, T
[28]Omnichannel, Challenges T
[30]Challenges T
[16]PracticesBrazilM, S
[23]Packaging T
[33]Research community, Channels T
[36]ChannelsChinaM, S
[5]Channels T
[26]ChallengesPolandC, M
[14]Research community, Channels T
[19]PracticesSwedenC, M
[27]Omnichannel, Challenges T
[24]Packaging T
[25]PracticesSpainC, M
[32]Research community, Channels T
[38]OmnichannelSingaporeM, S
[22]PackagingChinaC, M, S
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 2. Delivery methods & attributes literature summary.
Table 2. Delivery methods & attributes literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[4]Parcel locker, OtherEnglandC, T
[51]Parcel lockerBrazilM
[52]Parcel lockerBelgiumC, M
[28]Parcel locker T
[30]Other T
[57]Delivery attributesNorwayM, S
[31]Night deliveryEuropeC
[56]Off-peak deliveryBrazilC, S
[37]Parcel lockerBrazilS
[16]Off-peak deliveryBrazilM, S
[58]Delivery attributesBrazilM, S
[36]Delivery attributesChinaM, S
[39]Parcel locker, Other T
[45]Parcel lockerItalyM, S
[42]CDPNew ZealandC, M, S
[50]Off-peak delivery, Parcel lockerPolandM, S
[40]Parcel lockerAustraliaC
[55]24/7 deliverySerbiaM, S
[43]Parcel lockerPolandS
[26]Parcel lockerPolandC, M
[46]Parcel lockerPolandS
[54]Off-peak deliveryCanadaC
[44]Parcel lockerItalyC, S
[48]CDPFinland, NetherlandsC, T, S
[49]Parcel locker S
[27]Parcel locker, Other T
[53]Parcel lockerGermanyM
[14]Parcel locker, CDP, Other T
[32]Parcel locker, CDP, Night delivery, Other T
[29]CDP, Off-hours delivery T
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 3. Innovative vehicles literature summary.
Table 3. Innovative vehicles literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[66]E-vehicle C, T
[52]Cargo bikeBelgiumC, M
[29]E-vehicle, Cargo bike, AV T
[18]E-vehicle, Cargo bikeEnglandC, T
[28]E-vehicle, Cargo bike, Drone, AV T
[30]E-vehicle, Cargo bike, Drone, AV T
[65]E-vehicle, Cargo bikeItalyC, M
[60]E-vehicle, Cargo bike, AV T
[39]E-vehicle, Cargo bike, Drone, AV T
[69]Cargo bikePolandC
[59]E-vehicle, Cargo bike, Drone, AV T
[27]E-vehicle, Cargo bike, Drone, AV T
[70]Cargo bike, DroneSpainM, S
[24]E-vehicle, Cargo bike, T
[53]Cargo bikeGermanyM
[50]Cargo bikePolandM, S
[14]E-vehicle, Cargo bike, Drone T
[32]E-vehicle, Cargo bike, Drone, AV T
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 4. Logistic infrastructures & schemes literature summary.
Table 4. Logistic infrastructures & schemes literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[4]ParkingEnglandC, T
[73]UCCSweden, Italy, NetherlandsC
[28]Parking T
[74]UCCEnglandC, S
[80]UCCBrazilM, S
[31]UCC, Parking, Road, Micro-depotEuropeC
[56]UCC, Parking, RoadBrazilC, S
[16]Parking, RoadBrazilM, S
[77]UCC T
[76]UCCLuxembourg, France, Spain, ItalyC, M
[85]UCC, Sprawl T
[50]Parking, RoadPolandM, S
[78]UCCEnglandC, S
[79]UCCEnglandM, S
[81]UCCEngland, ItalyC
[44]Parking, RoadItalyC, S
[48]Micro-depotFinland, NetherlandsC, T, S
[49]UCC, Parking, Road S
[27]UCC T
[24]UCC, Road, Sprawl T
[72]UCCEngland, NetherlandsC
[14]Parking, UCC T
[32]UCC, Parking T
[29]UCC, Sprawl, Parking T
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 5. Operational optimisation literature summary.
Table 5. Operational optimisation literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[29]Parking optimisation, Technology, Routing T
[28]Technology T
[86]Parking optimisationSingaporeC, M
[93]Technology T
[87]Parking optimisationItalyC, M
[95]TechnologyEurope, AsiaC
[97]TechnologySouth AfricaC
[99]TechnologyUSA, Colombia, SpainM
[92]Technology M, S
[94]TechnologyEurope, Canada, USAT
[44]TechnologyItalyC, S
[49]Technology S
[27]Technology T
[24]Technology T
[91]Routing M
[90]Routing M
[14]Routing T
[32]Technology, Routing T
[50]Routing, TechnologyPolandM, S
[4]TechnologyEnglandC, T
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 6. Emerging business models literature summary.
Table 6. Emerging business models literature summary.
Ref.ConceptCountryMethod 1Env.Eco.Soc.
[4]Crowdsourcing, Collab.EnglandC, T
[27]Crowdsourcing, Collab., People/Freight T
[100]Crowdsourcing, Collab., People/Freight T
[24]People/Freight T
[103]CrowdsourcingItalyM, S
[104]CrowdsourcingItalyM, S
[105]CrowdsourcingItalyC, M
[106]CrowdsourcingNetherlandsC, M
[18]CrowdsourcingEnglandC, T
[107]Crowdsourcing M
[30]Crowdsourcing, People/Freight T
[108]People/FreightSpainC, M
[110]People/Freight M
[28]Collaboration T
[111]People/FreightNetherlandsC, S
[113]CollaborationEnglandM, S
[114]CollaborationNetherlands, CanadaC
[49]Collaboration S
[50]CollaborationPolandM, S
[29]Crowdsourcing, Collab., People/Freight T
[14]Crowdsourcing, Collab. T
[32]Crowdsourcing, Collab., People/Freight T
1 C: Case study & interview; M: Modelling; T: Theoretical; S: Survey.
Table 7. Advantages and disadvantages associated with the main last-mile solutions identified.
Table 7. Advantages and disadvantages associated with the main last-mile solutions identified.
Vehicular solutionsElectric vehicle• Reduces operational and environmental costs [61,62,63,64,65]
• Battery suitable [62,67,68]
• High investment and infrastructural needs [18,28,63,66]
Cargo bike• Reduces congestion, noise, pollution [52,53,65,69]• Needs adequate road infrastructure and policies [28,69]
• Speed, load, and terrain limitations [28,69]
• Lower number of deliveries per hour [65]
• No consensus regarding operational costs reductions [52,53,65]
Autonomous vehicle• High future potential [59]• Uncertain benefits and applicability [27,59]
Drone• General consumers’ acceptance [70]• Needs infrastructural investments [28]
Operational solutionsOff-peak delivery• Reduces fuel consumption, GHG and other pollutants emissions [54,55]
• General consumers’ acceptance [55,56]
• Faster deliveries [54]
• No noise complaints [54]
• Non-consensual acceptance among stakeholders [16,50,56]
• Increased service times [54]
Omnichannel• Enhance customer experience [27]
• Increase customer base [27]
• Additional operational complexity [27,28]
• High cost [28]
• Not well perceived by consumers [38]
Technological systems• Reduces vehicle use, route length and duration, congestion, accidents, environmental costs, re-deliveries, operational costs, cooperation problems [27,28,88,92,95,96,97,98]
Parking-related measures• Reduces congestion, air pollution, accidents, delivery costs, illegal parking [86]• Non-consensual acceptance among stakeholders [16,44,49,50,56]
Road-related measures• General stakeholders’ acceptance [16,44,49,56]
• More efficient resource utilisation [24]
Organisational solutionsPeople/Freight transport• Reduces congestion, accidents, noise, pollutant emissions, operational costs [24,108,109,111]
• Efficient operation and business model [24,110,111]
• Low passenger impact [110]
• New job opportunities [111]
• Requires extra transshipment costs, handling equipment and labour tasks [24]
Horizontal collaboration• Reduces the number of vehicles, route length and duration, lead time [4,27,112,113]
• Increases resource utilisation efficiency [4,27]
• Additional revenue source [112]
• General stakeholders’ acceptance [49,114]
• Difficult coordination [28]
UCC• Reduces noise, accidents, congestion, fuel consumption, pollutant emissions, costs for carriers [71,72,75,76]
• General stakeholders’ acceptance [56,78,79]
• Not economically viable [71,72,73]
• Dependent on large scale operation [73,75,77]
Parcel locker• Reduces fuel consumption, trip length and duration, external and internal costs, re-deliveries [4,26,28,42,51,52]
• General consumer’s acceptance [37,42,43,45,46,47]
• General stakeholder’s acceptance [44,49,50]
• Potential generation of more external costs (e.g., noise, emissions) [52,53]
• Should have 24 h accessibility [43,45,46]
• Should be placed in frequently visited commercial sites [37,42,43,44]
Crowdsourcing• Reduces pollutant emissions, operational costs [103,105]
• General willingness-to-use [104]
• Additional income source for citizens [105]
• Needs a large number of crowdshippers [27,106]
• Potential social inequalities [18]
Table 8. Literature review summary.
Table 8. Literature review summary.
Method 1Dimension
1 (C) Case study & interview: empirical, comparative and field studies, and qualitative interviews with relevant stakeholders or experts. (M) Modelling: studies based on data mining, heuristic algorithms, genetic algorithm, linear programming, discrete choice modelling, Analytic Hierarchy Process, agent-based simulation model, among others. (T) Theoretical: mainly consist of classic narrative and systematic literature reviews. (S) Surveys: predominantly quantitative studies based on a stated preference questionnaire on consumer’s behaviour, satisfaction and preferences.
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Silva, V.; Amaral, A.; Fontes, T. Sustainable Urban Last-Mile Logistics: A Systematic Literature Review. Sustainability 2023, 15, 2285.

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Silva V, Amaral A, Fontes T. Sustainable Urban Last-Mile Logistics: A Systematic Literature Review. Sustainability. 2023; 15(3):2285.

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Silva, Vasco, António Amaral, and Tânia Fontes. 2023. "Sustainable Urban Last-Mile Logistics: A Systematic Literature Review" Sustainability 15, no. 3: 2285.

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