![Modelled impact of the 1st scenario* on aggregated sectors (change, %)
[* 1st scenario – larger demand for land transport services (+10%), postal and courier services (+10%), and in a result also for electricity (+10%), but less warehousing and support services for transportation (-5%) due to digital solutions and more efficient technologies.]
Source: the author’s calculations](https://www.researchgate.net/publication/378255359/figure/fig1/AS:11431281259702648@1720602729249/Modelled-impact-of-the-1st-scenario-on-aggregated-sectors-change-1st-scenario_Q320.jpg)
![Modelled impact of the 2nd scenario** on aggregated sectors (change, %)
[**2) 2nd scenario - noticeable relative demand decrease for petroleum products (-3%) and less air transport services (-2%) due to emissions limitations and growing flight ticket prices, hard-hitting target levels due to environment (EU New Green Deal) and replacement with land transport and glocalization (in this study meaning the allocation of production closer to consumers; shorter transportation distances (less air transport, more land transport as water transport is relatively specific and limited options to be used for the majority of products transported by land transport inlands), larger share of local materials and products in produced product or service; gradual replacement of imported ingredients due to policy measures to reduce import dependence in strategic importance industries and products as high-technology manufacturing). ]
Source: the author’s calculations](https://www.researchgate.net/publication/378255359/figure/fig2/AS:11431281259658246@1720602894120/Modelled-impact-of-the-2nd-scenario-on-aggregated-sectors-change-2-2nd_Q320.jpg)
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Modelling the Potential Impact of the Application of Environmentally Friendly Transport Applied in Last-Mile Delivery on the National Economy: The Case of Latvia
Abstract and Figures
Green logistics or greener technologies in logistics compared to the current are widely discussed and promoted in the European Union (EU) level and national level energy, environmental, transport, economic recovery, economic transformation policies and initiatives. However, a limited amount of quantitative studies and report covers both impacts on specific sectors or industries and national level impact. Two development scenarios on technology application effects are modelled with input-output model for Latvia’s economy obtaining results for 64 products of economic activity (NACE Rev2), and additional regional development examined (NUTS 3 disaggregation). The modelling results claim that if more land transport services (+10%), postal and courier services (+10%), and hence electricity (+10%), are demanded, but less warehousing and support services for transportation (−5%) due to digital solutions and more efficient technologies then the national economic output increase by 0.8%, amid aggregated sectors the largest impact is on wholesale (+1.7%) and industry (+1.3%) and regionally impact is between +0.85% (in Pieriga region) and 0.72% (in Vidzeme). Results on relatively noticeable demand decrease for petroleum products (−3%) and less air transport services due to emissions and replacement with land transport and glocalization (−2%), modelled impact is +0.5%. Results are highly sensitive on scenario assumptions. Companies and policies are tackling different areas; only identified are modelled.
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COVID-19 policy and measures have caused both negative and positive challenges for the transport sector. The aim of the research is to model an impact of shocks that transport and logistics encounter during the COVID-19 era on the economy and regional development. A comparative-static approach that involves an input-output model with additional regional modelling block and scenarios are applied. Two scenarios are estimated for Latvia’s economy: firstly, extremely dramatic decline in demand on air transport services by 90%; secondly, unexpected increase in demand for postal and courier services that doubled output. The results of the first scenario argue that the service sector is influenced more than manufacturing due to air transport collapse –rental and leasing services (-11.6%), employment services (-9.7%), other transport services (-7.0%), impact on manufacturing is relatively minor and only on certain branches. The results of the second scenario on doubled output in postal and courier services argue that there is a positive impact, but the scale is relatively low, the most affected industries are manufacturing (of paper products (increase by 1.7%), rubber and plastic goods (1.6%)). The findings confirm that the urban areas due to higher economic activity and larger service sector are more affected to the modelled shocks both negative and positive. The rural areas are relatively less negatively affected during the crisis, but at the same time, during the recovery (for example, in the post-COVID era) it may lead to weaker economic activity and the rural areas will continue to lag behind urban areas.
Effective government transport policy can be based only on realistic data, sophisticated and detailed transport sector analysis, and productive modelling. The aim of the paper is to demonstrate the main elements used to develop a relatively small macro-economic input-output model with the emphasis on transport for one European Union (EU) country. Transport sector faces similar problems in various countries linked with emissions, transport flows, road accidents and other issues hence appropriate modelling tool should be selected. The model presented in this article consists of econometric and input-output relations. The research analyses and examines three scenarios and stresses the importance of the transport investment not only for development of the transport sector, but also for the economic development in general. The scenarios imply zero, 9 million and 6.7 million additional investment in transport sector eligible to the EU funding. As the result of additional investment, GDP recovers faster leading to 0.3-1.7%points faster growth rates as compared to the base scenario with no additional investment leading to faster cohesion with the average EU level, as well as higher number and turnover of passengers in the public and commercial transport, while the number of passenger cars is lower. The model can also be applied to study regional development, if it is possible to distinguish, which regions will benefit from the investment, as well as influence on fuel consumption and CO2 emissions, if the investments are targeted to specific means of transport.
Covid-19, the global pandemic, has taught us the importance of contactless delivery service and robotic automation. Using self-driving delivery robots can provide flexibility for on-time deliveries and help better protect both driver and customers by minimizing contact. To this end, this paper introduces a new vehicle routing problem with time windows and delivery robots (VRPTWDR). With the help of delivery robots, considerable operational time savings can be achieved by dispatching robots to serve nearby customers while a driver is also serving a customer. We provide a mathematical model for the VRPTWDR and investigate the challenges and benefits of using delivery robots as assistants for city logistics. A two-stage matheurisitic algorithm is developed to solve medium scale VRPTWDR instances. Finally, results of computational experiments demonstrate the value of self-driving delivery robots in urban areas by highlighting operational limitations on route planning.
Last mile logistics (LML) is the least efficient and complex part of supply chain. The main objective of this study was to identify major challenges of urban freight LML and opportunities for intervention. For this, 42 peer-reviewed full papers published after 2010 and three additional references were used. The findings indicated that urban freight flow has a trend of steady growth. The main driving forces behind this steady growth are population growth, urbanization, densification, globalization, online and omni-channel (OC) retailing, and urban economic development. Using typology analysis, three main potential freight LML configurations were mapped and discussed. Freight LML configurations that involve light cargo vehicles and cargo bike-based delivery schemes could be the most sustainable freight LML models if the delivery failure is minimized. The LML challenges were categorized as technological, infrastructural, LML system and management, and logistic cost related challenges, and discussed broadly. Similarly, the potential opportunities were discussed from environmental, economic, and social sustainability aspects. Finally, this report has pinpointed future potential research agendas related to LML. The study could be a knowledge base useful for academicians and practitioners, logistics and technical service providers, policy makers, and customers.
E-commerce is still a strong growing segment with fierce competition among parcel delivery service providers. To stay ahead of the competitors innovation is necessary. Currently, parcels are being delivered with large delivery vans which will usually deliver single parcels to doorsteps of their customers. This so called ‘last mile delivery’ is the most expensive logistics activity. In the literature it is proposed that parcel lockers have high potential to save cost. In our paper a literature review on parcel lockers, 3 methods for analysis are described and the results of a case study are provided.
E-grocery is developing into a frequent and prominent form of online shopping. While some empirical studies suggest that online shopping substitutes personal shopping travel, others indicate a limited or no impact on number of trips and travel distance. Mobility for passengers and freight is one of the key issues in integrated planning in urban areas, and the growth of e-commerce and home deliveries is likely to affect the structure and performance of the urban freight chain. This study explores the use of home delivery services through a survey among Norwegian users of services connected to food and groceries. The study draws on insight from the survey to discuss how city municipalities can integrate trends of urbanisation and digitalisation into planning for sustainable mobility and efficient urban freight transport. A prominent finding is that home delivery of food and groceries is associated with fewer trips to physical grocery stores and reduced car use on these trips. In considering implications for city planning, several strategies and potential instruments are presented and discussed.
Contemporary cities are becoming more and more crowded, polluted and devoid of space. At the same time, along with the development of e-commerce, the logistic flows are growing rapidly, which is an increasing challenge for city authorities. Sustainable development of urban logistics is becoming more and more important for the quality of dwellers life, while the solution of two main problems - congestion and poor air quality is the key to success in this field. The use of cargo bikes as a means of transport operating at least part of freight flows within the city has a positive impact on both problems. The article presents the course and results of field research on the use of cargo bikes in urban logistics in Stargard under the Low Carbon Logistic project. Particular attention was paid to the condition of the existing bicycle and road infrastructure in Stargard and the possibility of using cargo bikes for the needs of local government administration. The applied bicycles were also analyzed in terms of adapting their mobility and transport capabilities to the needs of potential users.
Nowadays, online retailers are offering a variety of delivery options consisting of varying combinations of delivery attributes. This study investigates how consumers value these delivery attributes (e.g., delivery speed, time slot, daytime/evening delivery, delivery date, and delivery fee) when selecting a delivery option for their online purchases. Mental accounting theory is used to frame the research and to suggest how mental accounts for money, time, and convenience influence consumer preferences for online delivery options. Specifically, the results of a conjoint analysis show that the most important attribute in shaping consumer preferences is the delivery fee, followed by nonprice delivery attributes. For individual attributes, significant differences are found in consumer preferences between gender and income groups. Cluster analysis reveals three consumer segments that show distinct preference structures: We identify a "price-oriented," a "time-and convenience-oriented," and a "value-for-money-oriented" consumer segment. This study has practical implications for online retailers when implementing suitable delivery strategies and designing effective delivery options to maximize consumer satisfaction.
Last mile deliveries are one of the major effectors of heavy traffic of commercial vehicles in the whole city area. Due to e-commerce's generic specificity, its functioning on B2C market is based on home deliveries. In recent years very interesting and popular solution became the parcel lockers as the efficient last mile delivery system. This paper is focused on the analysis of usability and efficiency of this measure based on the example of Polish InPost Company system. It introduces the results of pilot survey realized in Szczecin (Poland), as well as the general expectations regarding the efficient utilization of this kind of solution.
This paper addresses whether consumers’ environmental attitudes and behavior are reflected in their stated preferences for last mile delivery options for clothing rentals, and whether preferences are heterogenous across groups of respondents in terms of socioeconomic characteristics, income, and environmental attitudes. The analysis relies on data collected through a discrete choice experiment among Norwegian females between 18 and 70 years of age.
The key results are: i) females have a negative utility from delivery time, delays, local air pollutants (PM) and greenhouse gas emissions (CO2) from last mile deliveries, and a positive utility from information services and ii) females consumers are likely to accept increased delivery time if it implies reduced emissions. The findings are relevant for both urban planners, online retailers, and transport operators as they show that consumers prefer environmentally sustainable last mile delivery options and that other measures than price can incentivize consumers to choose sustainable deliveries.
In the literature, city logistics in terms of last mile delivery on the e-commerce market is quite new area of research that is not thoroughly investigated. It can be observed that there are many papers discussing various topics from the perspective of different groups of stakeholders such as residents, governments, shippers, receivers, transport companies (CEP), and others. However, there is no holistic approach covering the presented field of research. Therefore, the paper’s purpose is identification of trends in sustainable last mile delivery on e-commerce market in cities from the perspective of various stakeholders. The research method that serves the paper’s purpose is systematic literature review in the above-presented field performed through traditional method and machine learning (VOSviewer). In order to conduct critical analysis of published sources, the Web of Science and Scopus databases were applied. The paper's added value is a comprehensive approach to sustainable city logistics of last mile delivery that includes all stakeholders' perspectives and the identification of trends in this area. During the critical literature analysis, authors identified the relations between stakeholders, the fields of the research, and the trends for developing sustainable last mile delivery on the e-commerce market. It should be noted, that recent articles discuss newer technological and organization solutions, such as IoT, autonomous vehicles, crowd-shipping, parcel lockers, and concentrate on the behavior analysis of e-customers.
The “First-Last Mile” problem (FLM) is a relevant transport issue. According to the Green Paper on Urban Mobility, the combination of passenger and freight flows may be a valid approach to promote sustainable, efficient and socially desirable FLM transport. This paper proposes a set of key performance indicators to evaluate potential improvements in operational, environmental and social performances of integrated passenger and freight flows, compared to the current transport schemes. The two case studies of the Northern lagoon of Venice in Italy and the Slovenian Municipality of Velenje indicate that the model may be particularly effective in those cases where reduced freight volumes, limited freight pickup/delivery locations and a lower elasticity of the travel demand reduce the constraints to the adoption of this integrated scheme. Results call for a reduction both in distances travelled and in externalities produced, and hence a good potential in FLM terms. Beside these technical aspects, one of the main issues is the need for innovation in the normative/regulatory context: a prerequisite in order to apply this solution to real-life contexts.
Purpose
The purpose of this paper is to explore if e-commerce customers change their preferred last-mile delivery, when they are provided with additional information on the environmental and social sustainability impact of the available last-mile delivery options.
Design/methodology/approach
We conduct a stated-preference survey and apply McNemar test on the collected data.
Findings
The results show that displaying the environmental and social impacts of last-mile deliveries influences E-commerce customers, and generally makes them more likely to choose a more sustainable last-mile delivery.
Research limitations/implications
The main limitations are (1) the possible inconsistency between participants' intentions stated in the survey and their actual behaviour in real life and (2) the possibility of participants denying socially undesirable behaviours. Further research can study e-commerce customers' real behaviour.
Practical implications
E-retailers and logistics companies could implement transparent information sharing on the delivery sustainability impact on all three sustainability pillars.
Social implications
The suggested transparent information sharing has the potential to change customers' behaviours towards more sustainable deliveries.
Originality/value
We provide a new approach in investigating customers' preferences on last-mile deliveries, by giving E-customers the chance of making choices between different deliveries, not only based on the economic factors (as in common practice nowadays) but also based on the environmental and social factors.
Current trends related to increased sustainability requirements, the application of new digital technologies, and changes in consumer behavior have disrupted conventional food supply chains, entailing challenges for the last mile logistics and distribution of food products. The main aim of this study is to develop a toolset for exploring the sustainability potential of last mile logistics and distribution strategies, employing (1) a centralized distribution network with a click & collect option, (2) a decentralized distribution network with a home-delivery option, and (3) a distributed network based on a crowd logistics concept. For this, a system dynamics (SD) simulation and a multi-criteria decision aid (MCDA) were applied to assess the sustainability performance of these distribution channel options for a case study of a local food cooperative and a logistics service provider in Austria. The sustainability potential of developing a new logistics system in collaboration with these players has been estimated for the first time, while considering the dynamic interplay of all relevant sustainability elements within operational, tactical, and strategic planning. The results show that an integration of the two players into a distributed network strategy based on a crowd logistics concept is the most viable and sustainable option. This highlights the significant role of the logistics sector in proactively innovating services to make sustainable choices easier for the customer.
Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation.
In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot.
The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.
In recent years, the role of freight transportation and parcel delivery in urban areas has increased, supporting the economic and social development of cities. At the same time, the industry is affected by various issues, inefficiencies, and externalities, particularly in the last-mile segment. As such, there is an emerging awareness of a need to improve urban mobility and transportation, making them more sustainable and competitive by mixing traditional and emerging technologies, such as cargo bikes, autonomous vehicles, and drones. In contrast, the complexity of the overall system, characterized by multiple actors with conflicting goals, requires a strategy that harmonizes these actors’ business and operational models. This study contributes in this direction along three axes. First, it defines the main actors involved in urban parcel delivery, and then analyzes their business models and the interactions between them. Second, it investigates the integration of traditional and green logistics (mainly cycle-logistics), from both business and operational perspectives, in order to identify synergies, conflicts, and the operational and economic consequences of adopting green vehicles. Third, it introduces a simulation-optimization decision support system tool capable of assessing mixed-fleet policies for the management of parcel delivery in urban areas. Finally, the decision support system is tested using real data of the city of Turin.
The last-mile problem concerns the provision of travel services from the nearest public transportation node to a passenger’s home or other destination. We study the operation of an emerging last-mile transportation system (LMTS) with batch demands that result from the arrival of groups of passengers who desire last-mile service at urban metro stations or bus stops. Routes and schedules are determined for a multivehicle fleet of delivery vehicles, with the objective of minimizing passenger waiting time and riding time. An exact mixed-integer programming (MIP) model for LMTS operations is presented first, which is difficult to solve optimally within acceptable computational times. Computationally feasible heuristic approaches are then developed: a myopic operating strategy that uses only demand information from trains that have already arrived, a metaheuristic approach based on a tabu search that employs demand information over the entire service horizon, and a two-stage method that solves the MIP model approximately over the entire service horizon. These approaches are implemented in a number of computational experiments to evaluate the system’s performance, and demonstrate that LMTS is notably preferable to a conventional service system under certain conditions.
Unmanned aerial vehicles, or drones, have the potential to significantly reduce the cost and time of making last-mile deliveries and responding to emergencies. Despite this potential, little work has gone into developing vehicle routing problems (VRPs) specifically for drone delivery scenarios. Existing VRPs are insufficient for planning drone deliveries: either multiple trips to the depot are not permitted, leading to solutions with excess drones, or the effect of battery and payload weight on energy consumption is not considered, leading to costly or infeasible routes. We propose two multi-trip VRPs for drone delivery that address both issues. One minimizes costs subject to a delivery time limit, while the other minimizes the overall delivery time subject to a budget constraint. We mathematically derive and experimentally validate an energy consumption model for multirotor drones, demonstrating that energy consumption varies approximately linearly with payload and battery weight. We use this approximation to derive mixed integer linear programs for our VRPs. We propose a cost function that considers our energy consumption model and drone reuse, and apply it in a simulated annealing (SA) heuristic for finding sub-optimal solutions to practical scenarios. To assist drone delivery practitioners with balancing cost and delivery time, the SA heuristic is used to show that the minimum cost has an inverse exponential relationship with the delivery time limit, and the minimum overall delivery time has an inverse exponential relationship with the budget. Numerical results confirm the importance of reusing drones and optimizing battery size in drone delivery VRPs.
Driven by new laws and regulations concerning the emission of greenhouse gases, carriers are starting to use electric vehicles for last-mile deliveries. The limited battery capacities of these vehicles necessitate visits to recharging stations during delivery tours of industry-typical length, which have to be considered in the route planning to avoid inefficient vehicle routes with long detours. We introduce the electric vehicle-routing problem with time windows and recharging stations (E-VRPTW), which incorporates the possibility of recharging at any of the available stations using an appropriate recharging scheme. Furthermore, we consider limited vehicle freight capacities as well as customer time windows, which are the most important constraints in real-world logistics applications. As a solution method, we present a hybrid heuristic that combines a variable neighborhood search algorithm with a tabu search heuristic. Tests performed on newly designed instances for the E-VRPTW as well as on benchmark
Aggregations of manufacturing based on NACE Rev
- Eurostat