Collecting longitudinal data from freight operators: survey design and implementation ideas and challenges

Freight transport research has generally been limited by a lack of data of the breadth and quality available for passenger transport, particularly in terms of behavioural data. This paper discusses the survey design and implementation of a survey intended to collect longitudinal behavioural data on the responses of freight transport firms to environmental policies. The design of the survey is centred around a hypothetical scenario where respondents are asked how they would complete a given freight task within common constraints. One of the key components of the survey design is a dynamic component intended to simulate the changing business environment. The paper illustrates the many challenges in getting complex freight related surveys in the field.     

Meeting an 80% reduction in greenhouse gas emissions from transportation by 2050: A case study in California

This paper investigates how California may reduce transportation greenhouse gas emissions 80% below 1990 levels by 2050 (i.e., 80in50). A Kaya framework that decomposes greenhouse gas emissions into the product of population, transport intensity, energy intensity, and carbon intensity is used to analyze emissions and mitigation options. Each transportation subsector, including light-duty, heavy-duty, aviation, rail, marine, agriculture, and off-road vehicles, is analyzed to identify specific mitigation options and understand its potential for reducing greenhouse gas emissions. Scenario analysis shows that, while California’s 2050 target is ambitious, it can be achieved in transport if a concerted effort is made to change travel behavior and the vehicles and fuels that provide mobility. While no individual ‘‘Silver Bullet” strategy exists that can achieve the goals, a portfolio approach that combines strategies could yield success. The 80in50 scenarios show the impacts of advanced vehicle and fuels technologies as well as the role of travel demand reduction, which can significantly reduce energy and resource requirements and the level of technology development needed to meet the target.     

On including travel time reliability of road traffic in appraisal

In many countries, decision-making on proposals for national or regional infrastructure projects in passenger and freight transport includes carrying out a cost–benefit analysis for these projects. Reductions in travel times are usually a key benefit. However, if a project also reduces the variability of travel time, travellers, freight operators and shippers will enjoy additional benefits, the ‘reliability benefits’. Until now, these benefits are usually not included in the cost–benefit analysis. To include reliability of travel or transport time in the cost–benefit analysis of infrastructure projects not only monetary values of reliability, but also reliability forecasting models are needed. As a result of an extensive feasibility study carried out for the German Federal Ministry of Transport, Building and Urban Development this paper aims to provide a literature overview and outcomes of an expert panel on how best to calculate and monetise reliability benefits, synthesised into recommendations for implementing travel time reliability into existing transport models in the short, medium, and long term. The paper focuses on road transport, which has also been the topic for most of the available literature on modelling and valuing transport time reliability.     

Determinants of modal choice in freight transport

In the next few years, exciting developments in the field of freight transport are likely to occur. The Channel Tunnel will be perceived as giving railways much greater distance of operation, compared to the current train ferry to/from Great Britain. The further development of swap-body technology will allow easier modal transfer and the creation, in 1992, of a single market in Europe will transform the pattern of trade. All of these are likely to have significant impacts on modal choice, and hence modal split, in freight transport. Reappraisal by many firms of the modes of transport used is likely but will it result in a net transfer of freight from road to rail and, if so, to what extent? To answer such questions, an accurate and reliable method of predicting modal split is required. Research in the past has concentrated on the development of modal split models based on generalised costs. These fail to explain adequately the prevalence of road freight in the UK. From surveys of freight managers within industry, it is clear that models to date rely too heavily on the economic cost factor and too little on behavioural factors (Jeffs 1985). This paper derives from a recent study of freight transport modal choice from the standpoint of the transport decision-maker within the firm. It attempts to shed light on the actual parameters which should be incorporated into a modal split model. Many variables appear to exert an influence on modal choice decision-making process. However, it is possible to categorise them into six main groups, namely: customer-requirements; product-characteristics; company structure/organisation; government interventions; available transport facilities; and perceptions of the decision-maker him/herself. It is the interactions and inter-relationships between these which ultimately determine freight modal split. This study has shown that the relationship between the outcome of the transport decision process and the values of particular determinants of modal split is not straight-forward, due to the complexity and variety of interactions involved. Perhaps one of the main reasons for researchers' failure hitherto to develop a successful modal-split model has been the preoccupation with techniques that rely on the development of common metric (e.g. generalised cost), which has led to the exclusion of some important explanatory variables along quite different dimensions. Another important issue concerns the appropriate level of aggregation. In order not to reduce the explanatory power of the key variables, it is important to work at a disaggregate level, although this does make substantial demands on data. The use of factor analysis enables both the aggregation of information without loss of behavioural reality and the specification of variables in terms of a common metric. In conclusion, freight transport has usually been examined within too narrow a framework. It must be placed firmly within the context of the total industrial process. The demand for freight transport is directly influenced by the level, composition and geographical distribution of production and consumption activities. Freight flows are complex and so it is highly unlikely that a universal mode-choice model can ever be developed. Future research should, therefore, be directed towards developing partial models in response to specific needs of those involved in decision-taking in the freight sector.     

A cost and CO2 comparison of using trains and higher capacity trucks when UK FMCG companies collaborate

Companies working in a collaboration are able to achieve higher vehicle capacity utilisation and reduced empty running, resulting in lower costs and improved sustainability through reduced emissions and congestion. Collaboration produces higher volumes of goods to be moved than individual companies which means that further efficiencies may be possible by relaxing the freight mode constraints and considering rail and higher capacity vehicles. This paper explains how real world data has been used in a model to quantify the economic and environmental benefits in the FMCG sector delivered through collaboration utilising road and rail freight modes. Data for one month was provided by 10 FMCG companies and included freight transport flows between depots and customers, inter depot movements, and supplier collections. Detailed road and rail costs and operating characteristics were obtained and, with the transport flows, applied to a network design model which was used to validate the company data sets. A strategy examining the potential use of alternative higher capacity vehicles and rail for the flows between nine regional consolidation centres showed cost and CO₂ savings. Just under half the inter-regional flows benefited from double deck trailers, longer heavier vehicles for 30% of the flows and rail with different wagon configurations for the rest. In summary there was a 23% reduction in cost with 58% fewer road kilometres and a 46% reduction in CO₂ emissions. The ability to backhaul the same mode of transport between most of the regional centres was one of the strengths of this strategy.     

The ‘Four Dimensions of Behaviour’ framework: a tool for characterising behaviours to help design better interventions

This paper sets out the rationale and structure of a tool for assisting policy-makers and practitioners to understand behavioural challenges and open up thinking on the design of effective ‘behaviour change’ interventions. The ‘Four Dimensions of Behaviour’ (4DB) framework is based on the theoretical and empirical research in a range of policy domains including transport and pro-environmental behaviour more generally. The 4DB framework characterises multifaceted behaviours along dimensions of actor, domain, durability and scope. Its application in workshop or structured settings opens up diverse and non-exclusive discussion on designing interventions to match salient behavioural characteristics. The use of the 4DB framework in the transport domain is demonstrated for travel behaviours of interest to policy-makers using examples of buying plug-in vehicles (PiVs), commuting by bicycle, eco-driving and making business trips by train.     

Calculation of external costs for freight transport

Abstract

The negative impacts of transport are in general associated with costs. These costs are usually denoted as ‘external costs’ or ‘externalities’. This paper presents a tool for calculating external costs for freight transport together with its application to a number of case studies. The categories considered include: air pollution, greenhouse gases, noise, accidents and congestion. Results are presented for a number of different transport alternatives as total costs and divided into categories. The uncertainties in the results are discussed. The assessment of these costs is essential for predicting future transport costs.     

Valuing Freight Transport Time using Transport Demand Modelling: A Bibliographical Review

The value of time for freight transport is of major importance in infrastructure-related cost–benefit analysis and yet its study has been largely neglected when compared with its passenger counterpart. In fact, one of the attributes that could decide the profitability of a project is how much can be saved if freight vehicles use new infrastructure. Despite being the primary benefit of most investments in transport infrastructure, researchers have not yet reached agreement over either the size or the nature of the values of time that should be used when evaluating projects. This article provides a review of the estimation of freight value of time through transport demand modelling and extant empirical evidence on this topic. Similarly, the bibliographic review of studies undertaken has allowed us to pinpoint the most critical issues when modelling freight transport demand and the position of various research teams regarding these aspects. Such issues include identifying the decision-maker, heterogeneity in the transport flows and transport attributes considered by decision-makers.     

Environmental benefits from better freight transport management: freight traffic in a VAR model

Most macro empirical studies on the price elasticity in the freight transport sector focus on the demand for transport. However, most of the external costs from the freight transport sector are more closely linked with the traffic volumes. In the paper an explicit distinction between traffic and transport demand is made by regarding traffic as an input in the shippers’ production of transport services, while transport demand is derived from firms’ production of output. An empirical analysis based on aggregate time series is carried out in a VAR model, where the stationary long run relationships are estimated using the so-called ‘Johansen Procedure’. The estimated price elasticity with respect to traffic (−0.81) is considerably higher than the elasticity with respect to transport (−0.47).     

Review of GPS Travel Survey and GPS Data-Processing Methods

Abstract

Global positioning system (GPS) devices have been utilised in travel surveys since the late 1990s. Because GPS devices are very accurate at recording time and positional characteristics of travel, they can correct the trip-misreporting issue resulting from self-reports of travel and improve the accuracy of travel data. Although the initial idea of using GPS surveys in transport data collection was just to replace paper-based travel diaries, GPS surveys currently are being applied in a number of transport fields. Several general reviews have been done about GPS surveys in the literature review sections in some papers, but a detailed systematic review from GPS data collection to the whole procedure of GPS data processing has not been undertaken. This paper comprehensively reviews the development of GPS surveys and their applications, and GPS data processing. Different from most reviews in GPS research, this paper provides a detailed and systematic comparison between different methods from trip identification to mode and purpose detection, introduces the methods that researchers and planners are currently using, and discusses the pros and cons of those methods. Based on this review, researchers can choose appropriate methods and endeavour to improve them.     

Refocusing the Modelling of Freight Distribution: Development of an Economic-Based Framework to Evaluate Supply Chain Behaviour in Response to Congestion Charging

The distribution of freight is a major contributor to the levels of traffic congestion in cities. However it is much neglected in the research and planning activities of government, where the focus is disproportionately on passenger vehicle movements. Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, we see a void in the study of how the stakeholders in the supply chain might cooperate through participation in distribution networks, to reduce the costs associated with traffic congestion. Given that transport costs are typically over 45 of all distribution costs, with congestion a major contributor in the urban setting, the importance of establishing ways in which supply chain partnerships might cooperate to reduce levels of freight vehicle movements has much merit. This paper sets out a framework to investigate how agents in a retail supply chain might interact more effectively to reduce the costs of urban freight distribution. We propose an interactive agency choice method as a way of formalising a framework for studying the preferences of participants in the supply chain to support specific policy initiatives. Such a framework is a powerful way of investigating the behavioural response of each agent to many policies, including congestion pricing, as a way of improving the efficient flow of traffic in cities.     

Breakthrough innovations in intermodal freight transport

Breakthrough innovations, whether technological, organizational or both, are a necessity if the market share of intermodal freight transport is to expand. The main growth potential lies in the markets for flows over short distances, for perishable and high-value commodities, for small consignments, and for flows that demand speed, reliability and flexibility. It will take radical innovations to produce a breakthrough in the modal split and allow these new markets to be conquered. This special issue is based on papers presented at an international conference on freight transport automation and multimodality, held in Delft in May 2002, that are illustrative of the direction of breakthrough research and development (R&D) aimed at increasing the market share for intermodal transport.     

Improvement actions for reducing transport’s impact on climate: A shipper’s perspective

The purpose of this paper is to compare improvement actions for reducing transport’s impact on climate from the shipper’s perspective. To that end, it introduces an evaluation tool for comparing improvement actions in transport systems in terms of transport costs, impact on climate, and barriers to implementation. Within the context of five international flows involving a food producer, three actions—namely, engaging intermodal transport, increasing load factors by double-stacking pallets, and using high-capacity vehicles—were evaluated. Shipment data were collected to calculate reductions in transport costs and impact on climate, whereas interviews with the food producer were conducted to identify barriers. Results showed that reductions in transport costs and impact on climate attributed to the improvement actions differed among the five flows. Engaging intermodal transport reduced the system’s impact on climate by 27–53%, double-stacking pallets by 0–23%, and using high-capacity vehicles by 7–15%, with differences primarily due to different freight densities. Concerning barriers to implementation, the improvement actions also varied by flow. Altogether, unlike other papers, which have examined improvement actions separately, this paper offers an evaluation tool for comparing several improvement actions at once, as applied to a particular empirical case. Shippers with multiple flows and several possible improvement actions can use the evaluation tool to efficiently reduce their systems’ impact on climate.     

The Impact of Urban Freight Transport: A Definition of Sustainability from an Actor's Perspective

Abstract

This paper presents a definition of sustainable urban freight transport (SUFT), based on the existing theories and concepts, and develops an indicator set that describes SUFT. The definition of SUFT makes a categorisation of actions possible which enables actors to select effective strategies towards SUFT. The indicator set consists of two levels: impact indicators – which describe how the urban freight transport violates the principles of sustainability; and performance indicators – which describe different categories determining the characteristics and performance of the urban transport system. A literature study analyses the characteristics determining the performance of actors in the urban freight transport chain. Knowing the current state and improvement potential of the urban freight transport system are prerequisites for defining successful strategies and implementing effective actions.     

CO2 efficiency in road freight transportation: Status quo, measures and potential

Road freight transport continues to grow in Germany and generates 6% of the country’s CO₂ emissions. In logistics, many decisions influence the energy efficiency of trucks, but causalities are not well understood. Little work has been done on quantifying the potential for further CO₂ reduction and the effect of specific activities, such as introducing computer assisted scheduling systems to trucking firms. A survey was survey out and linked fuel consumption to transport performance parameters in 50 German haulage companies during 2003. Emission efficiency ranged from 0.8 tonne-km to 26 tonne-km for 1 kg CO₂ emissions. The results show potential for improvements given a low level of vehicle usage and load factor levels, scarce use of lightweight vehicle design, poorly selected vehicles and a high proportion of empty runs. IT-based scheduling systems with telematic application for data communication, positioning and navigation show positive effects on efficiency. Fuel use and transport performance was measured before and after the introduction of these systems.     

Incorporating Logistics in Freight Transport Demand Models: State-of-the-Art and Research Opportunities

Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects of changes in logistics systems on future transport flows. As such it provides better estimations of the costs of interaction and allows to predict changes in spatial patterns of freight transport flows more accurately. In recent years, the attention for freight modelling has been growing and new research work has appeared aimed at incorporating logistics in freight models. In this paper we review the state of the art in the representation of logistics considerations in freight transport demand models. Our focus is on the service and cost drivers of changes in logistics networks and how these affect freight transport. Our review proceeds along a conceptual framework for modelling that goes beyond the conventional 4-step modelling approach. We identify promising areas for freight modelling that have an integrative function within this framework, such as spatial computable general equilibrium models, supply chain choice models and hypernetwork models.     

Understanding transport mode choice for commuting: the role of affect

This study examines the relationship between positive and negative user valence and transport mode choice behaviour. We integrate latent attitudes ‘affect’ and ‘salience’ into transport mode choice models using the framework of integrated choice and latent variable modelling and simultaneous maximum likelihood estimation methods. The results are consistent with findings in similar travel behaviour and behavioural economics literature. The study extends the findings of previous research and has demonstrated that user sentiments about public transport mode and salient public transport experiences have a significant impact on travel mode choice behaviour. It was found that private motorised users are more sensitive to overcrowding and anti-social behaviours on PT than active and PT travellers. Key attitudinal indicators influencing individual transport choice behaviour are established to guide public policy. The key indicators of Affect and Salience must be analysed and addressed through public policy to enhance PT user experience and develop services and facilities to increase the utility of PT in-vehicle travel time.     

The potential demand for a urban freight consolidation centre

This paper reports the results of a stated-preference study aimed at investigating how transport decisions are made by receivers or by transport operators about the potential use of an urban freight consolidation centre in the city of Fano, Italy. Because there are no revealed preference data, a stated-choice methodology is used. The stated-choice experiments present two alternatives—one using a private vehicle subject to various traffic regulations and one using the urban freight consolidation centre with varying cost and efficiency levels. Conventional discrete choice data modelling shows that the potential demand is influenced mainly by the distance of the parking bay from the shop, by access permit cost, by the service cost of the urban freight consolidation centre, and by the delay in delivery time. Simulations are then performed to assess how the potential demand is affected by various incentives and regulations affecting urban goods distribution.

Stakeholder-specific data acquisition and urban freight policy evaluation: evidence,implications and new suggestions

Cities, characterised by scarce resources and facing increasing citizens’ requests for more liveable and attractive environments, need to define and implement more efficient urban freight transport policy interventions. It is strategically relevant to perform an ex-ante in-depth policy evaluation. The paper aims at investigating the relevance, the needs and the implications of the data acquisition process by combining a focused review with an original research study. It critically compares five categories of methodological approaches adopted for policy evaluation purposes with an explicit focus on the stated preference method given its behavioural peculiarity and robustness. The review, following a systematic procedure where scientific quality is complemented by relevance and coverage, underlines a high variability in the level of sophistication for data acquisition. While a stakeholder-specific approach seems natural in all those cases where local authorities want to adopt distinct policy instruments for each stakeholder, this is also needed when homogeneous policies impacting the various stakeholders are tested. Stakeholder-specific data acquisition translates into the creation of multiple experimental designs, explicitly conceived for each stakeholder considered. A case study, intended to compare two alternative strategies for data acquisition, provides a quantitative measure of potential distortions in policy evaluation due to the adoption of a stakeholder-generic approach. Results, in terms of willingness to pay measures, show that a stakeholder-specific approach is needed not only when modelling but also in the data acquisition process.     

Assessing the cost-optimal mileage of medium-duty electric vehicles with a numeric simulation approach

Electric freight vehicles have the potential to mitigate local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. Research within the body of the current literature suggests that increasing the driven mileage can enhance the competitiveness of electric freight vehicles. In this paper we develop a numeric simulation approach to analyze the cost-optimal balance between a high utilization of medium-duty electric vehicles – which often have low operational costs – and the common requirement that their batteries will need expensive replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with medium-duty electric vehicles. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to diesel prices or consumptions, or if the battery is not safeguarded by a long warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost gap at lower daily mileages, or increase the utilization of medium-duty electric vehicles, in order to abate the negative impact of urban road freight transport on the environment.