Stated preference study into the value of time and reliability of travel time for passenger and freight transport in The Netherlands. Development of a micro-level logistics module including determination of shipment size, transport chain, use of consolidation and distribution centres, modes for the Norwegian, Swedish and Danish national freight model systems.
Re-estimation of the Dutch national model LMS for traffic and transport. The impacts on car ownership of abolishing the car purchase tax and introducing kilometre-based charging stated choice experiment and model. Cohort-based forecasting model for demand for rail travel for NS.
Study on the value of safety in transport for the European Investment Bank. Passenger and freight transport models for the mobility masterplan Flanders. Demand forecasting risk analysis for a new high speed rail link and for a large tunnel project. Estimation of mode choice models for Dutch national freight transport model BasGoed. Review of freight transport elasticities.
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Review of transport policies for reducing emissions for Israeli Ministry of the Environment. Input—output models are usually used in this step.
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In a second step freight distribution the flow of commodities between the zones is calculated. There are different methods e. The output is an origin—destination matrix that describes the sources and sinks of the commodity flows. Once the flows of goods are converted into vehicles, the demand is assigned to the supply network in the fourth and final step traffic assignment [ 1 , 14 ].
We will recover these steps in most of the models reviewed in this article.
Furthermore, the short explanation of the model characteristics above provides a better placement for the upcoming argumentation of the different models. This chapter will show that logistical elements found inadequate or no consideration in most national models until a few years ago. This hampered the accurate mapping of freight transport and logistics as an import influencing factor. An overview of developments in freight transport modelling concerning the integration of logistics will be given in the section below.
Thus, the following introduction provides the general frame for the subsequent presentation of different models that consider logistics and transport logistics hubs in particular. Early attempts towards integrating logistics aspects into models can be found in the field of disaggregated modelling dealing simultaneously with mode choice and logistics choices.
In Chiang et al. Winston [ 50 ] stated in his review that models in application were lacking logistics aspects since the time his article was published. The paper from Bergman [ 5 ], presented at the International Meeting on Freight , Logistics and Information Technology , can be recognized as the starting point of integrating transport logistics into modelling. He proposes a more detailed spatial representation of logistics processes in freight logistics models. Introducing elements of logistics decision-making in freight models took off in the Netherlands in the early s. Furthermore, it has taken years before similar approaches started to be adopted elsewhere [ 39 ].
Broadly speaking, there are different models taking logistics into account. These models are currently operated in different countries and, to some extent, across borders. Although transport demand modelling concerning logistical matters has developed enormously in recent years, there are currently only a few models in use that incorporate logistical aspects concretely [ 27 ]. Even though there are different articles dealing excellently with integrating logistics into freight transport modelling see. Almost all papers review international models in a more general way and address the integration of logistics in general.
Differing to that, the following part focusses specifically on the integration of transport logistics hubs see chapter 2 in models in application. Below we will present an overview of models in operation that consider logistics aspects and hubs. Therefore, they represent the most interesting models in use in respect to the topic of this paper. Due to the fact that the reviewed models differ in their characteristic e. Subsequently, the analysis will focus on the integration of transport logistics hubs.
From a certain point of view it can be seen as a mixed model see next section when referring to its depth of aggregation. The model is based on several sub-models that take into account developments of economy, trade as well as foreign trade etc. The model considers 35 commodity groups and offers 86 predefined transport chains with 34 possible means of transport for transportation processes via a multimodal network.
Decisions on shipment size, suitable routes and means of transportation are achieved by a logistics module [ 11 , 39 , 47 , 49 ]. The logistics module consists of three steps and follows the ADA structure aggregated-disaggregated-aggregated.
Flows of goods between places of production and consumption are firstly provided on the aggregated level. In order to assign them to individual firms they are disaggregated. To allocate the OD-flows to routes, the data are finally aggregated again [ 10 ]. Selecting one of the predefined transport chains, the logistics module sets modes of transport for each section and determines whether transport is accomplished directly or via the utilization of logistics hubs.
Transport logistics hubs are also included in the model — defined as locations were goods are transhipped and possibly stored [ 11 ]. The logistics module consists of subroutines that develop decisions gradually. Due to the fact that the model also includes transhipment processes, linking different legs of the transport chain, the corresponding costs incurred by using transport logistics hubs are also considered transport logistics hubs like truck terminals, ports, intermodal terminals and airports.
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Included costs then vary per ton and vehicle type. Existing information regarding terminal properties e. Due to economies of scale, for instance, or differences in technologies operating at hubs, the derived costs vary at these nodal points. Therefore, the model distinguishes between different classes of terminals, which are characterized by a technology factor between zero and one.
It is based on the assumption that, for example, ports which handle more goods use more advanced technologies [ 10 , 11 , 13 ]. Beside a general integration of hubs, the differentiation of diverse types of transport logistics hubs represents a further step in considering and distinguishing hubs in demand modelling — also with regard to node-specific characteristics within a category [ 11 , 13 ]. Network Model for Freight Transport is a national model applied to the area of Norway. Thus, the model represents an extension of the Swedish one to the spatial area of Norway and, therefore, will not be examined separately.
SMILE simulates transport flows by taking economic developments into account and linking the economy, logistics and transportation. It was the first model especially developed to include distribution centres into the routing processes of commodity flows [ 39 ]. Land use via production , trade via sales, sourcing , logistics via inventory and transport are coupled across four stages [ 40 ].
The impact of logistics hubs, which is represented by distribution centres in this case, becomes noticeable by considering hub characteristics, and the attributes of goods and their requirements in terms of inventory, handling and transportation. With respect to this, different types of products are clustered into 50 logistics families. The clustering process is based on certain characteristics of the product e. The characteristics of these logistics families impact the potential and capability to handle certain types of goods.
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Therefore, hubs influence distribution chains and transport flows, and provide a spatial redistribution of the flows of goods through handling and stock rates, packaging density and volume to weight related to hub characteristics see Fig. The mapping of distribution centres with appropriate opportunities of consolidation and the resulting transport flows based on characteristics of goods and hubs is one way to include hubs in transport demand modelling.
Similar to other models, trade and transport relations are linked with inventory and storage services in SMILE.
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However, transport logistics hubs are not considered in particular. SLAM is designed to evaluate the effects of changes in logistics and in the transport system across Europe. Therefore, a major application is the detection and location of distribution centres in Europe. Accordingly, SLAM ought to give a more accurate picture of transport flows involving logistical matters. The model considers changes in distribution structures e. SLAM receives production and consumption flows e.
In this context a distribution chain is defined as the combination of distribution centres and transportation relations for trade flows between producer and consumer region. In this manner, a main function of the model is the consideration of alternative distribution chains production — distribution centre — consumption see Fig.
Hubs in SLAM based on [ 16 , 43 ]. In order to determine alternative distribution chains, located hubs are listed in accordance to characteristics of products, markets and transport services. A location score module then calculates a score for each region related to its attraction as a possible location for distribution centres based on economic activity, centrality and accessibility to infrastructure etc.
Afterwards, a chaining module selects the most attractive regions for distribution centres and constructs logistics chains via these centres. Furthermore, logistics costs are calculated for each single chain composed of transportation, inventory and other logistics costs. The construction of transport chains thus follows the approach of minimizing total costs [ 9 , 26 ].