Last-mile logistics in the sharing economy: sustainability paradoxes

This thesis explores the important role of last-mile delivery in the logistics sector, with a particular focus on the e-commerce sector. Daraz, a leader in e-commerce, currently relies on two- and four-wheeled gasoline-powered vehicles for last-mile deliveries, using a hub-based model spread across nine locations across the Kathmandu valley. In line with its commitment to environmental sustainability, Daraz aims to convert its entire fleet of gasoline-powered vehicles to electric alternatives, thereby contributing to the global effort to reduce the carbon emissions. Our research yields compelling findings that highlight the significant benefits of transitioning from internal combustion engines (ICEs) to electric vehicles in the context of e-commerce last-mile delivery. These results highlight the financial and ecological benefits of adopting electric mobility in the logistics sector. We recommend that organizations involved in last-mile delivery, especially in e-commerce, carefully consider the use of electric vehicles as a financially prudent and environmentally friendly option. This conversion promises significant fuel savings, significantly improved fuel efficiency and an extremely short payback period of less than 5 years. In addition to these findings, our research also examines the transformative potential of energy consumption and emissions reduction in last-mile logistics. The energy consumption by EV is found to be less than 50% than that of petrol option. We reveal a stark disparity between petrol and electric vehicles, with petrol two- and four-wheelers showing significant energy consumption and emissions, especially in the area of carbon dioxide (CO2). In summary, our research makes a compelling case for a cleaner, more sustainable and more economically viable future in last-mile logistics through the adoption of electric vehicles and other innovations.

The more successfully the Last Mile Logistics (LML) industry delivers its service, the greater the chance of delivering the Customer Promise for retailers. The motivation for this research was, to better understand the expectations and demands of online customers and the effect thereof on the LML provision. Previous research has sought to apply an understanding of business and operational models to the home delivery service, including vehicle route optimisation and delivery innovation (Perboli, et al., 2018). The LML industry is complicated, somewhat illstructured, relying on multiple and cross-functional approaches that must often be changed with immediate effect, subsequently destabilising the delivery provision. This research addresses the “Implications of express delivery business modelling in the last mile industry” arising from an initial study. This research critically examines key business models as well as the overall governance of the UK LML industry. It then goes onto develop an LML business model. This research addresses the complexity of the end customers’ experiences, recognising the impact of technology, that supports the online customer and its effects on the LML industry. The research identifies a solution for a more efficient LML Express industry business model based on Parmentier and Gandia’s (2017) multi-sided platform model. In 2015, an industry roundtable discussion focus group raised issues affecting the LML industry. A five-year longitudinal last mile delivery survey followed, with an in-depth company study of one leading UK LML and one-to-one interviews with eight leading LML professionals. The results establish significant themes regarding delivery for the customer, and LML delivery service industry. Throughout the research, the reliability of current LML business models and practices were identified. Analysis showed a lack of confidence implementing rigid business models in multi-channel and directional flow of demand, in a fluid marketplace. The research conclusion highlights need to engage with a multi-sided platform business model, incorporating technology, within the customer demand chain. This research provides a solution in the form of a business model platform, that might be used by an LML across the whole or part of the business.

Assessing the e-commerce last-mile logistics’ hidden risk hurdles

Last-mile logistics is both a source and cause of problems in urban areas, especially problems related to traffic congestion, unsustainable delivery modes, and limited parking availability. In this context, multiple sustainable logistics solutions have been proposed. We focus on micro-depots (MDs), which can function as a consolidation center and a collection-and-delivery point for business-to-consumer (B2C) small parcels. This paper presents a new research idea that extends the existing MD solution by introducing the concept of a shared MD network with parcel lockers. Such networks enable multiple logistics service providers (LSPs) and/or business partners to use an MD while minimizing their individual costs and optimizing the use of urban space. We present case studies of such shared MD networks operating in the cities of Helsinki and Helmond. We provide a framework for auxiliary businesses that can exploit the existing MD structure to offer services to the surrounding population. Finally, we define metrics for evaluating the success of shared MD networks while considering social, environmental and economic objectives. The case studies highlight the complexity of implementing such a solution; it requires stakeholders’ involvement and collaboration. In particular, deciding on the location for a shared MD network is a critical phase, since local authorities have their own regulations, and residents’ preferences are usually different than LSPs’ ones. Nevertheless, if these challenges are overcome, this sustainable last-mile logistics solution has a promising future.

PurposeCurrent online business development redistributes last-mile logistics (LML) from consumer to retailer and producer. This paper identifies how empirical LML research has used and defined logistic performance measures for key grocery industry actors. Using a multi-actor perspective on logistic performance, the authors discuss coordination issues important for optimising LML at system level.Design/methodology/approachA semi-systematic literature review of 85 publications was conducted to analyse performance measurements used for effectiveness and efficiency, and for which actors.FindingsFew empirical LML studies exist examining coordination between key actors or on system level. Most studies focus on logistic performance measurements for retailers and/or consumers, not producers. Key goals and resource utilisations lack research, including all key actors and system-level coordination.Research limitations/implicationsCurrent LML performance research implies a risk for sub-optimisation. Through expanding on efficiency and effectiveness interplay at system level and introducing new research perspectives, the review highlights the need to revaluate single-actor, single-measurement studies.Practical implicationsNo established scientific guidelines exist for solving LML optimisation in the grocery industry. For managers, it is important to thoroughly consider efficiency and effectiveness in LML execution, coordination and collaboration among key actors, avoiding sub-optimisations for business and sustainability.Originality/valueThe study contributes to current knowledge by reviewing empirical research on LML performance in the grocery sector, showing how previous research disregards the importance of multiple actors and coordination of actors, efficiency and effectiveness.

With the proliferation of B2C e-commerce and the advancement in service technologies, logistics service providers (LSPs) are increasingly offering innovative solutions that invite end-consumers’ participation. As embodied within the concept of value cocreation (VCC), consumers contribute their resources in co-creating logistics services in the form of reverse logistics, self-collection, crowd-sourcing delivery, etc. In so doing, consumers are empowered to influence specific changes in the service offerings, whereas LSPs accrue benefits in transferring parts of the service obligations to consumers. Given the mutual benefits, the trend of VCC is expected to gain a strong development in lastmile logistics. However, the concept of VCC is not without controversies. Some VCC literature regards the concept as an idyllic market where consumers and producers live in harmony, whereas the discordant side of VCC has been underemphasised. The aim of this thesis is thus to examine the discordances of consumers’ participation in co-creating last-mile logistics. Three rounds of survey were administered and the collected data were analysed using Structural Equation Modelling. From an innovation diffusion perspective (Study 1 of this report), it is found that consumers’ attitudinal hesitation significantly influences their initial adoption intention, whereas the perceived characteristics of the co-creation interface exert differentiated impacts on consumers’ decision-making process. Consumers’ hesitation may be overcome by a sense of compatibility, simplicity and trialability of the co-creation interface as perceived by the consumers. A perception of relative advantage acts as a direct motivator that encourages consumers’ adoption. From a service fairness perspective (Study 2), the results suggest that consumers’ fairness perception is influenced by their evaluation on the service value as well as the voluntariness of their participation. More importantly, the evaluation process is shown to be biased towards consumers’ pre-formed beliefs of the participation. A positive belief (participation in logistics services is enjoyable) leads to selective processing of positive signals (service value) and disregarding negative information (involuntariness). A negative belief, on the contrary, results in significantly worsened service experiences due to biased information processing. Study 3 examines consumers’ green scepticism in response to LSPs co-creation initiatives marketed as green value propositions. It is found that consumers’ green valueorientation is not a sufficiently strong moderator in attenuating their green scepticism. It is only when LSPs also show their commitments to the environment that consumers’ scepticism (unfair perception) would be significantly reduced. In this regard, consumers’ green scepticism results in a conditional contribution to green initiatives, where a harmonious co-creation relationship can only be formed when LSPs show their genuine care of the environment. Overall, this thesis contributes to the research domain with a unified framework of consumers’ participation in co-creating logistics values. The framework aligns with innovation diffusion theory, attitude theories, service fairness theories, selective information processing theory, green consumerism / scepticism theories, which are used as theoretical anchors of this thesis. The results also caution LSPs that values may not be harmoniously formed when collaborating with consumers in service creation. It is important to build innovations, fun elements and green efforts into logistics services.

The last-mile delivery problem is one of the most complex and resource-intensive aspects of modern logistics, especially within the growing e-commerce sector. As online shopping continues to expand, companies are under immense pressure to deliver goods more quickly, efficiently, and at lower costs, all while meeting the demands of increasingly time-sensitive customers. This has created a need for innovative solutions that can tackle challenges related to dynamic traffic patterns, fluctuating customer preferences, and operational constraints such as vehicle capacities and delivery windows. In response to these challenges, this paper explores the application of predictive analytics as a tool for optimizing last-mile delivery routes in real-time.The study begins by identifying the core challenges inherent in last-mile logistics, particularly in the U.S. e-commerce landscape, where the cost of last-mile delivery can represent up to 53% of total shipping costs. With traffic congestion, unpredictable customer availability, and delivery time constraints posing significant hurdles, conventional static route planning models often fall short. In this paper, predictive analytics is proposed as a solution to these challenges, utilizing real-time data to inform more efficient routing decisions. By processing vast amounts of real-time traffic data, customer preferences, and delivery constraints, predictive models can offer a more flexible and responsive approach to last-mile delivery.The research then presents a comprehensive literature review of existing route optimization methods, such as the traditional Vehicle Routing Problem (VRP) and its extensions, including VRP with Time Windows (VRPTW), Dynamic VRP (DVRP), and Capacitated VRP (CVRP). While these models have proven useful, their limitations are exposed when faced with real-time operational complexities in the e-commerce sector. Therefore, this study introduces an advanced dynamic routing model that integrates machine learning algorithms—such as decision trees and neural networks—with traditional VRP frameworks. These machine learning models, trained on historical data, are capable of predicting future traffic patterns, customer behavior, and delivery time windows.A case study is conducted using data from U.S.-based e-commerce companies to demonstrate the practical application of predictive analytics in optimizing last-mile delivery. The case study outlines how predictive models are used to dynamically adjust delivery routes based on real-time conditions, leading to significant improvements in efficiency, cost savings, and customer satisfaction. Key performance indicators such as delivery times, fuel consumption, and vehicle utilization are examined before and after the implementation of the predictive models, with the results showing a reduction in delivery time by 20% and fuel costs by 15%, alongside improved on-time delivery rates.The paper concludes by presenting the proposed dynamic route optimization model as a solution that combines the flexibility and responsiveness of predictive analytics with the robust framework of traditional VRP models. Through the integration of machine learning, real-time data processing, and dynamic routing, the model is shown to significantly improve last-mile delivery efficiency. This study's findings highlight the potential for predictive analytics to revolutionize the logistics industry, particularly in the high-demand e-commerce sector, where quick and reliable delivery is paramount. The research suggests that as e-commerce continues to grow, predictive analytics will play an increasingly critical role in ensuring that last-mile delivery is both cost-effective and responsive to the evolving needs of consumers.

PurposeAn increasing number of last mile deliveries (LMDs) pose many sustainability challenges that retailers and logistics service providers (LSPs) can address. Using cognitive frames (CFs) as a lens, this study explored how retail and LSP managers make sense of sustainable LMDs.Design/methodology/approachThe methodological approach used is a multiple embedded case study. The data were obtained from interviews with retailers and LSPs, supplemented with secondary data for triangulation.FindingsThe findings present the operational aspects of LMDs that managers associate with sustainability and indicate that retail and LSP managers frame sustainability primarily as emission reduction. Managers indicate an externalization of responsibility and a compartmentalization of the supply chain, in which social sustainability is not associated with the last mile. Most managers indicate hierarchical CFs regarding sustainability, in which sustainability is an important topic but is subordinate to economic interests.Practical implicationsCollaboration between retailers, LSPs and other stakeholders is viewed as challenging but could alleviate some of the sustainability shortcomings and aid in the paradoxical framing and inclusion of social issues.Originality/valueA conceptualization of managerial CFs for sustainable LMDs, together with empirical frame indicators and three propositions, is presented, providing novel insights into how paradoxical CFs could make LMDs more sustainable. This approach illuminates the possibilities for how to untangle the operational manifestations of managerial framing and adds to the empirical exploration of CFs in supply chain management.

The optimisation of last-mile logistics increasingly relies on advanced technologies and innovative strategies to enhance efficiency and reduce environmental impact. The literature indicates that urban last-mile delivery is significantly hindered by traffic congestion, leading to delays and consumer dissatisfaction. Addressing this issue requires improved delivery systems that balance speed, sustainability and cost-effectiveness. This chapter adopts a secondary qualitative research methodology, reviewing scholarly articles and reports to explore innovations that could alleviate congestion in last-mile logistics. Findings suggest that last-mile delivery, though a relatively recent focus, has become integral to urban logistics, particularly in cities like London, where demand for efficient delivery solutions is rising. Technological integration is expected to improve cost management and delivery speed. Moreover, the research process has enhanced critical thinking, time management and analytical skills, contributing to a deeper understanding of the field. The study concludes that technologies such as the Internet of Things (IoT) and artificial intelligence (AI) hold significant potential for optimising delivery routes and streamlining last-mile logistics. However, further research is necessary to assess the financial, infrastructural and operational challenges associated with their implementation. A comprehensive evaluation of these factors will be essential to ensure the successful adoption of technological advancements in urban logistics.

The purpose of this study is to conduct a literature review on urban last-mile logistics in the context of smart cities to help with defining the industry in new ways which involve space-wise innovations and the use of new technologies such as robotics, drones, IoT etc., toward a sustainable future. This literature review follows the SALSA approach and the CASP checklist, as well as several inclusion criteria for article collection. The results highlight the positive role of the industry 4.0 technologies and the role of smart cities in alleviating the last-mile logistics problem, while pinpointing that new initiatives such as dark stores and micro-fulfilment centers can also be a positive determinant of a more sustainable urban life. This is an original literature review which combines many important elements that come together in the context of smart cities and try to give some new perspectives to their last-mile logistics from viewpoints that have never been used before in similar research works. In addition, it can be used as a yardstick for future researchers who might try to dig dipper into the context of last-mile logistics, especially in smart cities.

This study investigates the evolution and reconfiguration of last-mile delivery strategies in the U.S. e-commerce sector, focusing on both technological and operational innovations. The study was anchored on four research objectives with Theory of Constraint (TOC) providing the theoretical anchor. Quantitative Survey Research Method was used with questionnaire as the instrument of data collection. Using supply chain managers, warehouse coordinators, and last-mile delivery operators working in logistics firms engaged in e-commerce fulfilment as the population of the study, a total of 250 respondents were selected as sample size based on the recommendation of Comrey and Lee (1992) and that of Kline (2005) who posited that in a population without definite number, a sample of 100 is considered small, a sample of 100 to 200 is medium, and a sample over 200 is considered large. Finding revealed that the explosive growth of e-commerce has put significant strain on traditional last-mile delivery models, thus, e-commerce growth has significantly reshaped strategic decision-making in the US’s last-mile logistics. While urban traffic and regulations, suburban route inefficiencies and rural infrastructure gaps were found as the geographical disparities in last-mile delivery efficiency and infrastructure, findings equally revealed that artificial intelligence and route optimization tools are the most widely adopted innovations (mean = 4.21) in last-mile delivery, followed closely by micro-fulfillment strategies (mean = 4.11), while autonomous delivery technologies as well as collaborative delivery platforms followed with (mean = 3.64), and (mean = 3.69) respectively. In light of the findings and guided by the Theory of Constraints (TOC), it was recommended that logistics firms operating within the U.S. e-commerce landscape adopt a constraint-focused approach to last-mile delivery strategy. Firms must first identify the primary bottlenecks, be they infrastructural, technological, labour-related, or geographic and apply tailored innovations to exploit and eventually elevate these constraints.

La thématique du développement durable se déploie dans le cadre contractuel de la prestation logistique « aval », entre GMS et prestataires. Cette recherche exploratoire basée sur une étude de cas interroge ces relations contractuelles. Les auteurs tenteront de démontrer que le « Développement Durable et Impact Environnemental » (DDIE) devient un levier de découplage et d’encastrement par le biais d’une démarche volontariste. Ces résultats montrent l’intérêt de faire appel à la théorie de l’encastrement et du découplage. Ils questionnent et justifient les conditions d’échange, assurant une plus grande stabilité dans le temps, entre GMS et prestataires logistiques, des relations au sein de la chaîne logistique « aval ».

In the e-commerce last-mile delivery process, the asset operators (logistics service providers who own parcel locker facilities) support their delivery service with parcel lockers, while the non-asset operators (logistics service providers without parcel lockers) perform door-to-door delivery. Due to demand fluctuation, asset operators’ parcel-locker slots may be left vacant, while non-asset operators are stuck with the high-cost door-to-door service. The exclusiveness of parcel-locker usage reduces resource utilization and service efficiency in last-mile delivery. Therefore, this paper proposes a parcel-locker-sharing model in which these two parties share the parcel-locker capacity in last-mile delivery. The asset operator rents the unused parcel lockers to the non-asset operator by charging a rental fee,while the non-asset operator rents the parcel lockers for delivery to save logistics costs. The motivation of this alliance is to increase the profits of both parties and that of the total supply chain. This study establishes the supply-chain profit model for the parcel-locker-sharing framework and finds that the profit or loss depends on the comparison of the operation cost savings and delivery-cost savings. A numerical analysis is conducted to validate the final result. The research further suggests the optimal rental quantity and price interval. This paper is the first to study the operational mechanism of sharing the parcel locker between two distinct types of logistics service providers and to offer recommendations for industrial application.

ObjectiveThe growth of e-commerce has transformed last-mile logistics, with direct-to-consumer deliveries and frequent delivery failures. This has exacerbated pollution and congestion issues, negatively impacting urban life. Given this scenario, the present study aimed to develop a taxonomy that enables the design of a sustainable last-mile logistics network specifically tailored to the context of e-retail. MethodA systematic literature review was employed for collecting robust scientific research, with the PRISMA diagram used to represent the steps followed in this process. Content analysis was applied to categorize the sustainability practices identified in the literature, grouping them according to the last-mile logistics process. RelevanceThis research contributes to understanding the last-mile logistics field in the e-retail context and provides valuable insights for formulating sustainable strategies and practices to mitigate the negative impacts of e-retail growth on the urban environment and society’s quality of life. ResultsThe research presents a structured taxonomy with 31 categorized practices across last-mile logistics processes: fulfillment, transportation, and delivery modalities. The results indicate that a sustainable last-mile network includes consolidation centers, shared micro-depots, shared freight transportation, electric vehicles such as bicycles and tricycles, and the implementation of collection and delivery points (CDPs). Social/Management ContributionsThe taxonomy offers elements that may contribute to operational efficiency, environmental impact reduction, and improving society’s quality of life by providing practical guidelines for the sustainable management of last-mile logistics in the e-retail context.

E-commerce growth as experienced during the COVID-19 pandemic was only expected to occur by 2025–2030. Online shopping increased in intensity and diversity. At the same time, retailers diversified their operations and opened online channels, also in sectors that previously showed reluctance to make this shift. These evolutions resulted in an expansion of household freight in terms of volume, geography, and organisation. Hence, half a decade of innovation in the e-commerce sector was needed in the span of two years. This manuscript summarises the repercussions for household freight since the pandemic's start. Given that interactions between consumers, retailers, and logistics service providers drive the e-commerce system, this manuscript combines these different literatures into a holistic framework, going beyond traditional siloed research on last-mile logistics, retail strategies, or online shopping behaviour. We found that logistics has come to the forefront: logistics service providers now need to provide tailored services and come in direct contact with consumers. As a result, we need (i) to gain insights into the new geography and dynamics of household’s freight origins and destinations; (ii) use this to re-examine existing relationships between consumer, retailer, and logistics service provider, and; (iii) assess the impact of more demanding consumers on the sustainability of the overall system.