Freight Mode Choice Research Articles

Joint Model of Freight Mode and Shipment Size Choice

Mode and shipment size choice are among the most critical logistics decisions but are typically studied separately in freight demand studies despite their strong correlations. The study described in this paper used an innovative copula-based framework to model freight mode and shipment size choice simultaneously as a joint decision-making problem. The study used a copula-based joint multinomial logit–multinomial logit model in which both mode choice and shipment size were modeled as discrete choices in a multinomial logit structure. The proposed copula-based model was intended to capture the potential effects of observed and unobserved factors that jointly affect both choices. The data used in this study were gathered through a large-scale establishment survey conducted in 2011 in the United States. The survey provided detailed information on more than 1,840 individual shipments that were used to develop the disaggregate models. Results of the estimated model underline the importance of the interrelationship between freight mode choice and shipment size and suggest that common unobserved factors influencing mode and shipment size choices exist. The model provides a better way to capture the effects of observed and unobserved factors that affect both choices simultaneously.

Estimation of an Inventory Theoretical Model of Mode Choice in Freight Transport

A model of freight mode choice was developed on the basis of the economic order quantity model, an inventory theoretical model of optimal shipment size. Shipment size is not explicit in the mode choice model; however, the specifications of the utilities associated with each transport mode account for shipment size and transport mode, which are two related decisions that depend on transport costs and on the logistics costs of shippers. The explanatory variables of the mode choice model are the total commodity flow between the shipper and the receiver, the distance between the origin and the destination, the value density of the commodity, and a few additional variables. No transport supply data are used. Four versions of the model were estimated with the use of the French shipper survey ECHO. As a result of these estimations, the terms of the utility functions inspired from inventory theory substantially improved the statistical goodness of fit of the models. This finding tends to confirm the potential of inventory theory to improve freight mode choice modeling. The finding also shows that the commodity flow between the shipper and the receiver is an important explanatory variable of mode choice and indicates that this variable should be observed in shipper surveys.

Modeling Rail Operating Costs for Multimodal Corridor Planning

Cost and delivery times are key variables used by shippers to determine freight mode choice. Unfortunately, transportation planners wishing to examine truck versus rail trade-offs on major state and regional corridors use models that rarely capture the effects of cargo weight, running speeds, network capacity, or route characteristics, even though they are key inputs to any logistical analysis. Moreover, current models are incapable of fully internalizing external or social costs into their calculations, a failure that becomes more important as sustainable strategies are sought by society. Therefore, in three critical areas of transportation planning—network capacity, route features, and operating characteristics—most existing models are deficient. This study gives planners a mechanistic method to determine variable rail costs on a single corridor. When this model is combined with the latest truck operating cost mechanistic models, the cost differentials that underlie the choice of truck versus rail will be revealed. The model, C-TRIT, is part of a study sponsored by the Texas Department of Transportation to support freight movement on the extensive state network of multimodal corridors.

Accommodating Risk Attitudes in Freight Transport Behaviour Research

Behavioural choice modelling is growing in interest as a framework to understand the decision-making of shippers, freight forwarders and other freight agents. Since the 1980s, we have witnessed an increasing number of freight behaviour studies, primarily the freight mode choice, where the roles of one or more freight decision-makers has been addressed, which was neglected in the traditional aggregate approach to freight demand modelling. Stated preference techniques have become a main approach to establishing the role of attributes that define the key drivers in the freight distribution chain. The underlying theory of choice is based on the neoclassical economic assumption that a decision-maker, in choosing, acts as if they are a utility maximizer (working to deliver a profit maximization or cost minimization outcome for the freight business), and this utility maximizing behaviour engenders a population theory of Random Utility Maximization (RUM). Despite the continuing appeal of the RUM framework in applied travel choice studies, a number of specific application assumptions have been questioned by studies in psychology and behavioural economics, arguing that the decisions made by agents are often conditioned on a number of underlying psychological components, one of which is risk attitude. This paper reviews recent freight behaviour studies established on RUM, and presents a major limitation of adopting a risk-neutral assumption through its linear utility specification. Using an existing freight stated choice data set, a nonlinear utility model is estimated which reveals risk-taking attitudes of transporters and shippers. An alternative behavioural paradigm, Rank-Dependent Utility Theory (RDUT), is introduced and incorporated to better accommodate trip time variability, a feature of growing importance in transport systems (passenger and freight). The proposed attribute-specific extended RDUT framework that accommodates the attitude towards risk and preference in freight transport behaviour modelling requires new data, which we detail.

Modeling Freight Mode Choice in Greece

The main purpose of this paper is to present the results of a comprehensive research study that took place in Greece in order to investigate the process and the criteria for freight modal choice behavior. It involved a large scale survey among various “actors” in the freight transport scene in Greece, and a full scale analysis of the results and outcomes. The objective was to reveal the mechanisms and the factors that influence freight transport mode choice and to produce mathematical models relating the users’ perception of the system with the various criteria and parameters that the statistical analysis, of the survey results, revealed as relevant.The present paper presents the modeling part of the above research work. Firstly, an analysis of relationships between the various attributes with the more “conventional” linear regression analysis is described. This analysis is presented in a summary form starting with the tests of linearity performed on the various parameters, and then proceeds with the presentation of the actual (linear) models developed.In the second part of the paper, a more comprehensive disaggregate logit analysis is presented. The purpose of this analysis is to replicate more closely the observed “individual user” behavior by use of appropriate explicatory variables from data collected in the survey. The resulting disaggregate models are tested for representativeness and accuracy and the final outcomes are presented. In all the above analyses the variables used are ratings and not absolute numbers.The study is quite unique for Greece and presents overall results and findings that can be utilized in many ways, from stimulating further research to supporting the adoption of effective policy.

A Freight Mode Choice Analysis Using a Binary Logit Model and GIS: The Case of Cereal Grains Transportation in the United States

Mode choice is important in shipping commodities efficiently. This paper develops a binary logit model and a regression model to study the cereal grains movement by truck and rail in the United States using the publically available Freight Analysis Framework (FAF2.2) database and U.S. highway and networks and TransCAD, a geographic information system with strong transportation modeling capabilities. The binary logit model and the regression model both use the same set of generic variables, including mode split probability, commodity weight, value, network travel time, and fuel cost. The results show that both the binary logit and regression models perform well for cereal grains transportation in the United States, with the binary logit model yielding overall better estimates with respect to the observed truck and rail mode splits. The two models can be used to study other commodities between two modes and may produce better results if more mode specific variables are used.

A behavioral analysis of freight mode choice decisions

This paper develops a behavioral analysis of freight mode choice decisions that could provide a basis for an acceptable analytical tool for policy assessment. The paper specifically examines the way that truck and rail compete for commodity movement in the US. Two binary mode choice models are introduced in which some shipment-specific variables (e.g. distance, weight and value) and mode-specific variables (e.g. haul time and cost) are found to be determinants. The specifications of the non-selected choice are imputed in a machine learning module. Shipping cost is found to be a central factor for rail shipments, while road shipments are found to be more sensitive to haul time. Sensitivity of mode choice decisions is further analyzed under different fuel price fluctuation scenarios. A low level of mode choice sensitivity is found with respect to fuel price, such that even a 50% increase in fuel cost does not cause a significant modal shift between truck and rail.

Investigation of Inland Freight Transport Modal Choice in Greece

The process and criteria for freight modal choice behavior in Greece were investigated in research between 2004 and 2009. The work involved a large-scale survey of various freight transport actors in Greece; a full statistical analysis of the results and a presentation to determine priorities, preferences, and detailed rankings of mode choice criteria; and a modeling exercise to produce models that depict the mode choice behavior of Greek firms. This paper discusses the questionnaire survey, characteristics of the participating firms, the decision-making process used for choosing the mode of transport, and the criteria used for mode choice decision making in Greece. The results contain conclusions and data that can be used to describe mode choice behavior in freight transport not only in Greece but also in other countries. These are summarized as reliability and quality of transport services, transport cost, characteristics of the transport chain, and the prevailing governmental policy and its corresponding legal framework for operation of the transport market. A future paper will contain the results of the modeling exercise and the various models of freight mode choice behavior that were formed.

The truth, the myths and the possible in freight road pricing in congested urban areas

This paper discusses a number of myths related to the trucking industry, its economics, and the industry response to pricing and what the author considers a fundamental truth and a possible course of action. The paper analyzes the empirical and econometric evidence about the behavioural impacts of freight road pricing, complements it with game theoretic analyses, and concludes that moving trucks to the off-hours require comprehensive policies targeting key components of the supply chain (i.e., receivers and carriers). The paper discusses the role of agent interactions and their role in determining freight mode choice, and the carrier industry response to time of day pricing. The paper shows that shipper-carrier interactions are part of a cooperative game in which both agents interact to find the overall optimal.The paper also shows the decision about delivery times is jointly made between carriers and receivers, as part of the “Battle of the Sexes” game. This suggests that moving truck traffic to the off-hours requires a change in the behaviour of receivers, so that they accept off-hour deliveries. This could be accomplished by a combination of financial incentives to receivers in conjunction with freight road pricing. Due to the fact that transporting during the off-hours is more efficient than during regular hours, it is likely that, should a sufficient number of receivers be willing to accept off-hour deliveries, the carriers will follow suit. The paper suggests a toll surcharge to finance the incentives to receivers.

An Experimental Economics Investigation of Shipper-carrier Interactions in the Choice of Mode and Shipment Size in Freight Transport

The paper discusses the theoretical and empirical evidence on the subject and concludes that freight mode choice can be best understood as the outcome of interactions between shippers and carriers, and that mode choice depends to a large extent on the shipment size that results from shipper-carrier interactions. These conclusions are supported by economic experiments designed to test the hypothesis of cooperative behavior. This was accomplished by conducting two sets of experiments (ones with the shipper playing the lead role in selecting the shipment size; and others in which the shipment size decision was left to the carriers), and by comparing their results to the ones obtained numerically under the assumption of perfect cooperation. The comparison of results indicated that the experiments converged to the perfect cooperation case. This is in line with the conclusion from game theory that indicates that under typical market conditions the shipper and carrier would cooperate. These results also imply that it really does not matter who “makes” the decision about the shipment size and mode to be used at a given time period, as over time the shipper—that is the customer—ends up selecting the bids more consistent with its own interest. In other words, these results do not support the assumption that freight mode choice is solely made by the carriers.

A STATED PREFERENCE FREIGHT MODE CHOICE MODEL

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.

A Stated preference freight mode choice model

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.

Freight mode choice and adaptive stated preferences

This paper presents empirical results from a survey of determinants of mode choice for freight in India. The Leeds Adaptive Stated Preference software was used for the main survey which was carried out in summer 1998 on the Delhi to Bombay corridor. The survey results show that frequency of service is an important attribute determining mode choice. Valuation of reliability is generally lower than expected. Value of time is quite similar across different product segments. Given prevailing costs, the results suggest that intermodal services can be viable for high value and finished goods.

Freight Demand Characteristics and Mode Choice: An Analysis of the Results of Modeling with Disaggregate Revealed Preference Data

Considerably less research has been done on modeling freight demand with disaggregate discrete models than on modeling passenger demand. The principal reason for this imbalance is the lack of freight demand data. Freight demand characteristics are expensive to obtain and are sometimes confidential. This paper analyzes the freight demand characteristics that drive modal choice by means of a large-scale, national, disaggregate revealed preference database for shippers in France in 1988, using a nested logit. Particular attention is given to private transportation (own account transportation) and combined public and private transportation. After aggregation and validation of discrete choice models, the influence of demand characteristics on freight modal choice is analyzed. The maximum probability of choosing public road transportation takes place at approximately 700 kilometers, while that of choosing rail transportation take place at 1,300 kilometers. Freight Demand Characteristics and Mode Choice: An Analysis of the Results of Modeling with Disaggregate Revealed Preference Data

Exploration of a box cox logit model of intercity freight mode choice

Abstract During the past years, the linear logit model has been used extensively in modal choice analysis. More recently, the introduction of Box–Cox transformations on the explanatory variables in passenger studies have generally shown the superiority of the Box–Cox logit over the linear logit. Nevertheless, we have found only one such application in freight transportation. This study is devoted to filling this gap by testing different configurations of the Box–Cox logit over the linear logit. Our results confirm the usefulness of the nonlinear Box–Cox specification found in passenger studies. We have used an original data bank developed for Canada. The bank contains, for 64 commodity groups, the 1979 domestic flows among 67 geographical zones, by three transportation modes: truck (private and for hire), rail and ship. To the authors’ knowledge, this is the first Canadian study on mode choice that takes into account private trucking; since Canadian private trucking is at least as important as for hire trucking, this could have contributed to the results obtained.

Regulatory reform and freight mode choice

Reform of trucking Vehicle Weights and Dimensions (VWD) regulations in Canada is now underway. The effect these reforms will have on the freight transportation industry are only recently the subject of research. This paper is part of this new research effort, aimed at understanding how regulatory reform in the trucking sector will affect the existing competitive relationship between trucks and the railways. The paper presents the results of study and research into modelling the relationship between mode choice and the service characteristics that are affected by VWD reform. Using several periods of data, a series of econometric models are developed which help to elucidate the relative relationships between the mode service characteristics for both of the principal interprovincial freight modes. A technique is developed and presented to model railway user costs in order to overcome the complex and often unrepresentable pricing activities of Canadian railways. The strength of the developed econometric models is presented, including their significance and statistical reliability. This is further reinforced by the similarities exhibited by all the models in the series. The selected model is applied to predict market service responses required of the railway industry in order to compete with the trucking sector now adapting to the new regulations. The impact of the newly implemented vehicle weight and dimension reform on the rail transportation industry is analyzed and railway industry improvements aimed at maintaining its market share are presented. The results predicted by the model show that railway user cost reductions should be moderate, and likely less than the level of inflation over the period of time when trucking converts its fleet to take advantage of the new regulations.

An inter‐Urban freight mode choice model

The Australian railway research and development organisation is conducting a study with one of its objectives being to determine factors affecting freight mode use. Part of this has included the development and calibration of freight mode choice models. This paper outlines the results obtained from the application of an elimination by aspects (eba) model to this task. The paper describes the theoretical background to the eba model, within the context of a general choice process, and then describes the results of the model when applied to three samples of shippers involved in regional freight transport (a).