Sustainable Freight Transport Research Articles

Last mile distribution using cargo bikes: a simulation study in Padova

The recent growth of e-Commerce has induced an increasing freight demand, which could lead to negative externalities, in particular in urban areas. To foster sustainable development of cities and increase their livability, many local authorities are implementing urban vehicle access regulations, such as low-emission zones, banning the circulation of polluting vehicles. These measures prompted the adoption of new sustainable freight transport solutions for last mile deliveries, such as cargo bikes. The aim of this paper is to describe the study for the implementation of such a system. The procedure was tested (1) to define the location of a transshipment facility where parcels are moved from vans to cargo bikes, (2) to estimate the environmental and economic sustainability of the system, and (3) to quantify the effects of uncertainty in the final results. The framework was applied to the city center of Padova (Italy), where two sets of delivery system were considered: the first with traditional vans starting from an existing urban consolidation center and the second with manual and electric cargo bikes starting from a micro-depot. In particular, demand of home deliveries was estimated for a typical weekday; routes of freight transport means were defined by an optimization procedure; these data were used as input to a Discrete Event Simulation model. A sensitivity analysis was carried out modelling the potential uncertainty associated with load/unload times and travel speed of means, due to traffic congestion. Several scenarios were tested considering three locations as potential transshipment points. Outcomes of the simulations were used to estimate key performance indicators, evaluating the environmental and economic effects of the two delivery schemes. Results highlighted the potentiality of cargo bikes as a sustainable delivery system, and the impacts of uncertainty on the ranking of alternative options (i.e. micro-hubs).

Bi-Level Fleet Dispatching Strategy for Battery-Electric Trucks: A Real-World Case Study

Driven by new regulations concerning greenhouse gas (GHG) emissions in the transportation sector, battery-electric trucks (BETs) are considered one of the sustainable freight transportation solutions. In this paper, a dispatching problem of the BET fleet is formulated as a capacitated electric vehicle routing problem (VRP) with pick-up and delivery. As the BET dispatching problem is NP-hard, the performance of existing approaches deteriorates in large instance problems, especially when the customers have different preferences and constraints. This article proposes a bi-level strategy that incorporates routing zone partitioning and metaheuristic-based vehicle routing to solve the large-scale BET dispatching problem, considering the delivery types, limited travel distances, and cargo payloads. We apply this strategy to a real-world fleet dispatching scenario with around 300 customer positions for pickups and drop-offs. The experimental results demonstrate that the proposed bi-level strategy can reduce total travel distance and travel time by 24–31%, compared to the baseline strategy implemented in the real world.

A start-up’s collaboration in networks for sustainable freight transport: a micro-meso-macro approach to innovation

Purpose The purpose of this paper is to analyse how start-ups with a clear sustainability focus collaborate with multiple actors at different levels to pursue business ideas and develop sustainable freight transport solutions. Design/methodology/approach This paper builds on a theoretical approach that includes three levels of analysis: the actor level (micro), business-network level (meso) and society and government level (macro). An embedded case study is used of a focal start-up aiming to innovate on networked platforms and electric and autonomous vehicles (EAVs). Findings Activities and resources are developed at the firm (micro), network (meso) and societal levels (macro), and all three levels need to be considered for a start-up, with a clear sustainability focus. Interaction within as well as between levels affects the innovation development, integration and implementation. The many-folded collaborations at the meso level serve as a locus for the integration of EAVs. The start-up’s networking activities with actors at meso and macro levels contribute to it gaining legitimacy in the transport system. Originality/value This paper focuses on the importance of collaboration in the context of developing innovative solutions for environmental sustainability and freight transport and provides a unique case of how a start-up company manages collaborations at the micro, meso and macro levels.

Zero-carbon measure prioritization for sustainable freight transport using interval 2 tuple linguistic decision approaches

Freight transport is the main source of carbon emissions. Implementing freight transport zero-carbon measures in an orderly manner has a very important practical value for sustainable development. Thus, the interval 2-tuple linguistic multi-attribute decision-making (I2TL-MADM) approach of zero-carbon measure prioritization for sustainable freight transport is presented. Considering the advantages of interval 2-tuple variables (I2TLVs) expressing the uncertainty evaluation information of zero-carbon measures, the decision model is developed based on I2TLVs. Firstly, the shortcomings of the inconsistent fuzzy preference relations (FPRs) constructed by comparing attribute values expressed by I2TLVs are revealed. Then, additive and multiplicative dominance degrees of I2TLVs are proposed, and their properties are discussed to ensure the consistency of decision information. Two I2TL-MADM methods based on the novel dominance degrees are developed to rank the zero-carbon measures of sustainable freight transport. Finally, the rationality of the developed I2TL-MADM decision framework is illustrated by numerical examples of Guangzhou. The results show that the developed decision methods can effectively construct the consistent FPRs and rank the zero-carbon measures.

Internet of Vehicles and Real-Time Optimization Algorithms: Concepts for Vehicle Networking in Smart Cities

Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative transport concepts as well as emerging mobility modes (e.g., ridesharing and carsharing) constitute a new paradigm in sustainable and optimized traffic operations in smart cities. Still, these are highly dynamic scenarios, which are also subject to a high uncertainty degree. Hence, factors such as real-time optimization and re-optimization of routes, stochastic travel times, and evolving customers’ requirements and traffic status also have to be considered. This paper discusses the main challenges associated with Internet of Vehicles (IoV) and vehicle networking scenarios, identifies the underlying optimization problems that need to be solved in real time, and proposes an approach to combine the use of IoV with parallelization approaches. To this aim, agile optimization and distributed machine learning are envisaged as the best candidate algorithms to develop efficient transport and mobility systems.

Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research

Synchromodal transportation is a novel multimodal transportation concept. It builds on a collaboration of shippers and logistic service providers to enable real-time switching between transport modes and mode-free transport bookings, enabling more flexible and sustainable freight transportation. This paper summarizes the current state of research since 2010 by means of a systematic literature review. A comprehensive taxonomy consisting of five dimensions and 13 categories for both qualitative and quantitative papers is developed. The results reveal a mixed picture, with high consistency in geographical areas of synchromodal transportation implementation and suitable modeling of operational disruptions and uncertainties. However, compared to multimodal or road transportation, there is little alignment in the forms of collaboration, network organization, or the advantages of synchromodal transportation. Finally, the main fields for future research are identified, namely business, legal, technological, modeling, and awareness.

Antecedents of freight transportation for sustainable supply chain in the post-COVID era: an emerging market study

PurposeIn past years, the global supply chain has witnessed devastating effects of coronavirus (COVID-19) disease. However, the COVID-19 pandemic has renewed the interest of the Sustainable Supply Chain (SSC) stakeholders on sustainability. The stakeholders are now rethinking their business processes and strategy to make them sustainable. In this context, the relevant literature is required to support emerging markets to formulate sustainability-focussed strategies. The purpose of this study is to provide a comprehensive analysis of potential antecedents that leads towards sustainable development of freight transportation in emerging markets.Design/methodology/approachInitially, the antecedents of the Sustainable Freight Transport (SFT) system are derived from the literature survey followed by verification from the experts. Then, the potential antecedents are categorized under four (social, organizational, operational and environmental) broad categories. Afterwards, a Neutrosophic Analytic Network Process (N-ANP) method is employed to obtain the priority weights of the identified potential antecedents.FindingsThe paper identified and ranked 17 antecedents of the SFT system. According to the study’s findings, the top three antecedents of SFT are “the presence of a multimodal transportation system,” “circularity in SFT” and “traffic congestion management”. The results from the study advocate the promotion of existing multi-modal transport facilities which is promising to achieve sustainability. The results suggested the adoption of the digital twin to manage the transport operations.Originality/valueThis study sheds light on how to achieve sustainability in the freight transportation system post-COVID era highlighting the potential antecedents. The study’s findings will assist practitioners in developing SFT strategies in the face of such pandemics in future.

Green Public Procurement for Accelerating the Transition towards Sustainable Freight Transport

Requests for emission reduction in the freight transport sector will be more intense in the coming years. One possible strategy to reduce emissions from freight transport is through utilising zero emission vehicles, which requires substantial investments both by transporters and by authorities. This paper examines how green public procurement (GPP) can be used to push the market in an environmentally sustainable direction. For this purpose, interviews with both public authorities and freight service providers are conducted. The results show that GPP is considered a useful tool for public authorities to both boost the uptake of zero emission vehicles and to share the investment costs with freight service providers. However, our study shows that there are differences between small and large municipalities. Moreover, to succeed with GPP, public authorities must prioritise such tasks in their daily routines through political decisions and strategies. Additionally, barriers related to financial possibilities are crucial to handle, as public support schemes are important to reduce costs for all involved stakeholders. Altogether, our paper shows that with the right tools and willingness among both public and private stakeholders, GPP can contribute to the use of more environmentally friendly solutions in the freight transport sector.

An Evaluation of Ireland’s Sustainable Freight Transport Policy

Background: The Irish government has put forth sustainable transport policy measures, yet the emphasis is mainly on the active travel and sustainable mobility for passenger transport. Contrariwise, freight transport has not received equal consideration in policy measures, regulatory frameworks, and support schemes towards the low-carbon transition. This study seeks to address this imbalance. Methods: The paper proposes an adaptation of the ASI framework for freight transport and assesses the applicability of a number of international sustainable transport measures based on their potential sustainability impact if adopted in Ireland. The research applied a Policy Delphi Method to a heterogeneous expert panel. Results: The findings indicate that the current sustainable freight transport policy measures in Ireland are limited, and the paper suggests 38 measures for supply chains, maritime transport, rail transport and urban freight transport. The analysis further suggests that decarbonisation measures in Ireland should first formulate on the decarbonisation stages ‘avoid’ and ‘shift’, and then move to the ‘improve’ stage, thus leading to a greater impact on decarbonising the freight sector. Conclusions: An ‘ASI for freight transport’ framework is proposed as a taxonomy to systematically compare freight decarbonisation policy measures locally and internationally. This updated framework can serve as a new lens to prioritise sustainable freight policy measures. Recommendations are proposed for developing policy measures for sustainable freight transport in Ireland.

A systematic scientometric review of sustainable rail freight transportation

The negative externalities of freight transport have caught the attention of scholars and practitioners to study sustainable freight transportation. Past studies have reviewed sustainable logistics from varying perspectives, but the rail mode-specific sustainable logistics has not been thoroughly reviewed. This sets the motivation to review existing research on sustainable rail freight transportation (SRFT). A science mapping approach was used to develop and visualize bibliographic networks of 378 articles published between 2001 and 2022 and indexed in the Scopus database. Four scientometric analysis techniques, namely journal co-citations; countries/organizations/authors co-authorship; document co-citations; and keywords co-occurrence, were employed in the VOSviewer software to reveal conceptual structure, social structure, and influential themes of the SRFT domain. Based on the results, the SRFT knowledge was categorized into six thematic branches (31 sub-branches), namely intermodal transportation for decarbonization; green policies, risk, and energy assessment research; savings in externalities for a sustainable future; decision-making with environmental and economic considerations; case studies and applications in SRFT research; and technological advancements towards sustainability. Finally, future research directions were proposed in the form of research questions. This systematic literature review will facilitate the researchers, practitioners, and policymakers to understand the status quo, existing research gaps, and emerging research topics in the SRFT research domain. This study is restricted to research articles and review articles published in English and indexed in the Scopus database.

Hydrogen storage station location selection in sustainable freight transportation via intuitionistic hesitant decision support system

Increasingly fierce competition in energy industry for alternative fuels has raised demand for fuel storage stations to be one of the pivots towards sustainable urban freight transportation. For zero-emission hydrogen-powered vehicles, these demands focus mostly on storage capacity and refueling-station location selection to maximize freight forwarding efficiency in major urban regions. This research proposes a Decision Support System (DSS) for hydrogen storage station location selection based on Intuitionistic Hesitant Fuzzy (IHF) methodologies. An ensemble of four methods were analyzed and applied for the use case of Larissa city urban region, central Greece. Fifteen evaluation criteria were imposed by experts from the transportation department and the local competent authorities, spanning to hydrogen infrastructure, socioeconomics and fleet and road network. Scenarios such as energy efficiency, pollution prevention and public acceptance in conjunction to the risk and safety considerations play a critical role in the process. All qualitative indicators were represented by triangular intuitionistic fuzzy numbers. The ensemble produced the same ranking indicating the Steiner point locations of the imposed communication tree on the road network as the most preferable scenario.

Modelling Freight Trip Generation Based on Deliveries for Brazilian Municipalities

Freight trip generation modelling is important for forecasting freight movements, and understanding freight movements is crucial to enabling sustainable freight transportation planning. The existing literature focuses on model development, and most of the previous models are estimated by ordinary least squares regression. However, few studies have carefully considered the OLS assumptions. The objective of this paper is to estimate freight trip generation models using deliveries to commercial establishments in Brazilian municipalities. A procedure is described to estimate models by ordinary least squares (OLS), and alternative techniques are considered to address the violations of the OLS assumptions. The analysis was conducted with data from 860 commercial establishments in nine Brazilian municipalities, and models were estimated for capital, non-capital, small, medium, and larger municipalities. The findings showed that alternative techniques to OLS regression can provide better-estimated parameters and more accurate results. Not evaluating the OLS assumptions could compromise the quality of the model and, consequently, planning using these models. Moreover, the results showed that the number of employees has a more significant influence in small cities and a lower influence in medium-sized municipalities. Finally, the findings demonstrated the importance of local models that include the municipalities’ characteristics and that can support freight transportation planning. These models can also include sustainable strategies for freight transport.

Social Responsibility and Urban Consolidation Centres in Sustainable Freight Transport Markets

This paper investigates the impact of Corporate Social Responsibility (CSR) strategies adopted by urban consolidation centres on the competition between logistics service providers. Taking into consideration pollution charges issued by city councils to reduce CO2 emissions in freight distribution, we study a Hotelling-like market setting where logistics providers could voluntarily outsource last mile deliveries to platforms endowed with eco-friendly vehicles. We considered the intensity of the competition, which is captured by switching costs and we theoretically find that in more contestable markets, the interplay between environmental policies and CSR strategies—intended as consumers-oriented pricing schemes—is more likely to enhance the demand by providers for consolidation centres’ deliveries. Conversely, when the competition is weak, i.e., the providers have a relatively strong market power, platforms’ services are less attractive and more relevant CSR pricing strategies are needed to spread out greener freight deliveries and make city logistics environmentally sustainable.

Transportation as a loosely coupled system: a fundamental challenge for sustainable freight transportation

In view of the pressing need to reduce the negative environmental impact of freight transportation we argue that it is essential to take account of the organization of the freight transportation system when considering how to address various individual activities and parts of the system. To support a transition to a more sustainable freight transportation system this paper examines the way in which different parts of the system interact and the way this can impact the scope for profound change. Taking loosely coupled systems (Weick, 1976) as a starting point, we scrutinize the couplings within and between three system layers of the freight transportation system: the supply chain layer, the transportation layer, and the infrastructure layer. In addition, we address two interfaces connecting these layers: the market for transportation services, and the traffic using the infrastructure. We find that tight couplings dominate in the supply chain and infrastructure layers and that these couplings depend on loose couplings in the transportation layer and the two interfaces. The pattern of couplings identified in the freight transportation system can explain several positive outcomes, such as flexibility and efficiency. But there are also major negative aspects of the loosely coupled nature of the system that create resistance to change and present a barrier in the drive for increased sustainability. The paper concludes that the identified couplings and system features have important implications for policies aiming to change the freight transportation system in ways that lead to significant reduction in the reliance on oil.

Prioritizing transport planning strategies for freight companies towards zero carbon emission using ordinal priority approach

Freight transportation counts for remarkable negative effects like emissions, noise, and congestion. This urges for a modal shift toward structuring a more efficient systematic network, facilitating full use of potentials among the transportation modes. Decision-makers face uncertainty and restricted information processing skills when assessing the alternatives for sustainable freight transportation. In this study, a novel extension of the Ordinal Priority Approach under picture fuzzy sets (OPA-P) is proposed to rank the alternatives. In the OPA-P algorithm, experts’ preferences are used to determine the weighting coefficients of criteria and rank the alternatives. A case study is employed to demonstrate the formulation and solution of the problem. The outcome of this study suggests the top-ranked and most important solution for the sustainable transport planning. In addition, to verify the stability of the proposed model, a validation analysis is carried out.

Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging

This study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC).

Designing a sustainable freight transportation network with cross-docks

This study aims to develop a sustainable freight transportation network considering capacitated cross-docks for minimising the overall supply chain costs, including carbon emission cost. The problem is inspired by a major retail company based in India, which would like to expand its product portfolio in the new region. A mathematical model is developed to minimise total costs encompassing transportation cost, pipeline and retailers inventory cost, fixed cost of cross-dock and carbon emission costs. The deterministic time dependant demand, multiple products and multiple sourcing and distribution are some of the challenges faced by the retail industry. A two-level self-adaptive variable neighbourhood search algorithm is applied to solve a computationally complex problem. The results based on a two-level self-adaptive variable neighbourhood search algorithm are compared with the variable neighbourhood search algorithm to test the robustness of the developed model. Results reveal that an increase in retailers over suppliers significantly influences the number of open cross-docks. A multiple-case scenario approach captures the implications of varying capacity on the number of open cross-docks; thus, supporting the freight distribution managers in making sustainability-driven decisions.

Transitioning to sustainable freight transportation by integrating fleet replacement and charging infrastructure decisions

The transportation sector is the largest contributor to global greenhouse gas emissions. Disruptive technological changes in this sector, such as alternative fuel vehicles, are crucial for emission reduction. We show how a cost-minimizing strategic transition plan to adopt electric trucks over time can be developed for a firm that owns and operates a fleet of diesel trucks. We consider the case in which the firm decides to invest in the charging infrastructure required to support this transition, either because the public charging infrastructure is currently inadequate or for strategic reasons. The congestion effect at the charging stations, the charging times, and the potential loss of productive driving time due to detours to reach charging stations are explicitly considered. By developing an independence property, we are able to model this problem as a linear integer program without specifying origins and destinations. We illustrate the resulting transition plan with realistic parameter configurations. Our results indicate that a firm with high transportation demand density over a given service region significantly benefits from adoption of electric trucks, while also enjoying substantial carbon emissions savings. High demand density also favors smaller battery capacity with shorter ranges under the optimized charging network capacity, even though larger battery capacity would increase productivity with extended ranges. Our analysis also offers insights for governments and regulators regarding the impact of several influential factors such as carbon cost, content of renewable energy in electricity mix, diesel engine efficiency, and subsidizing the charging infrastructure. Additionally, we present an extension to the model that allows for different modalities of partnership in the infrastructure investment; notably public-private and private-private partnerships. While in general our results suggest that such partnerships are beneficial to all involved, the amount and relative distribution of the potential gains depend on the topography and on the density of charging infrastructure.

An integrated optimization approach using a collaborative strategy for sustainable cities freight transportation: A Case study

• Logistics collaboration is studied in the planning of sustainable city freight transportation. • An integrated and collaborative approach is proposed for sustainable freight logistics networks. • Three sustainability dimensions are considered. • A case study is conducted to show the applicability of proposed approach and the effects of collaboration on the sustainable development of the society and the environment. In recent years, the increasing freight transportation activities has caused extensive economic, environmental and social impacts on society. Therefore, it becomes necessary for logistics companies to find high-performance strategies to enhance their sustainability. Collaboration between companies appears as one of the promising solution that improves the freight transport efficiency of modern cities. Existing studies on collaborative transport did not sufficiently account for sustainability aspects and they mainly discuss the independent planning of decision-making problems with economic objectives. However, collaboration an integrated decision-making process can significantly ameliorate the effectiveness of urban transportation systems. This study addresses the issue of sustainable freight transportation planning by formulating and solving a collaborative and integrated two-echelon inventory, location and routing problem (2E-CILRP). The 2E-CILRP is formulated as a multi-objective integer programming model that minimizes logistics costs, C O 2 emissions and accident rate. A hybrid heuristic based on machine learning is also introduced to solve the studied problem. The proposed approach combines k -means clustering and genetic algorithms. Comparison of the obtained results with those provided with exact method reveals that the developed approach is more efficient and more practical for designing integrated and collaborative networks with large-sized data. A case study of four agri-food SMEs in France is investigated in order to demonstrate the sustainable benefits of the developed optimization approach. The obtained results suggest that the developed approach can significantly reduce the level of C O 2 emissions, logistics costs and accident rate caused by transportation in cities.

Developing a holistic decision support framework: From production logistics to sustainable freight transport in an urban environment

In recent years, policy makers as well as urban logistics and transport research have investigated how to reduce environmental impact from transportation in urban areas. Therefore, many new frameworks that can help a specific actor in its decision making process at a certain decision making level (i.e., business or policy level) have been implemented and published. However, the first screening of existing literature did not reveal frameworks that can be used across different decision making levels. This limits the possibility for actors using the same infrastructure but not necessarily co-operate to discuss how the actions and needs of each actor of different decision making levels mutually influence each other. This paper first presents an outcome of a literature review and analysis of existing research project results before. It combines these to a multi-layer framework that can enhance collaborative decision-making and seamless aggregation of performance measures such as environmental impact from multiple transportation activities in and around urban areas. For this multi-layer framework, factors are identified, and possible relationships across the various layers are indicated. The field of application is the area near urban manufacturing sites and specifically addressing all actors that share on regulate infrastructure relevant to last mile inbound logistics. The source of data is project databases as well as for the literature review research databases. The methodology applied is a combination of a literature review based on database entries and a snowball approach. The article also presents how the framework can be prototypically implemented in participatory simulations using a simplified example. Potential usage for establishing holistic urban mobility structures is also discussed.