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Some economists have suggested a causal connection between transportation and trade. Such causality, it is argued, arises from the effects that the costs of moving goods have on the observed amounts of volume and value of international trade. Transportation costs are, however, just one category in a series of costs incurred by buyers and sellers when they trade. These costs are composed of direct elements, freight charges and insurance; and indirect elements, such as the financial cost of the time goods are in transit and their inventory cost. Other trade costs include transactions costs such as search costs, legal fees, and currency exchanges, among others. Thus, research on the effects of transportation costs results are rather relevant, particularly for developing countries attempting to compete in global markets with lower production costs.

The demand for goods has increased steadily over the past half century and a cost effective freight transportation system has become an integral ingredient of a thriving national economy. Only recently, freight transportation has been systematically analyzed and planned and is comparatively new compared to passenger transportation planning. A critical part of freight transportation analysis and planning is freight transport modeling which is used to forecast and predict behaviors of actors (e.g. freight shippers and carriers) in freight transportation system as well as evaluate related policies and measures. However, the complexity of freight transportation models is far beyond that of passenger transportation. As indicated by Chiang et al. (1980), “In modeling freight transportation systems, models have been developed by researchers from many disciplines using many different approaches in an attempt to solve many different problems. This is just one indication that freight transportation involves complicated decision-making processes.” Other factors contributing to the complexity of freight transportation modeling include variables affecting freight movement patterns, for example, locations, range of transported commodities, characteristics and nature of raw materials and end products, manufacturing operations and demand variation and pricing (Ortuzar and Willumsen 1990).

Taxonomy of Freight Transportation Models

Freight transportation models can be generally classified into two main categories: operational models for short to medium-term decision making and strategic models for long-term decision making. The details and differences between these two types of freight transport models are as follows (Kristiansen and Petersen 2002, Tavasszy et al. 2000).

Operational Models – This type of freight transportation models is at the firm level and usually applied for optimization purposes. Compared to strategic models, operational models are closer to actual decision making and more detailed in their description of logistic activities. Besides, a multitude of data is potentially available for modeling at the operational level. Some examples of issues to be analyzed by this type of models are change in cost structure, change in transport market, weight and dimension of vehicle, locations of distribution centers and fleet and crew arrangement.

Strategic Models – In contrast to operational models, a strategic model is an aggregation of firm-related flows. Strategic models are usually descriptive in nature and used to obtain insight into the impact of freight flows on the infrastructure network for long-term planning purposes rather than to optimize decision-making processes as required by operational models. Strategic models can be used to analyze, for instance, effects of transport policy measures on long-term patterns and modal distribution, effects of specific transport infrastructure investment projects on traffic pattern/modal distribution and socio-economic and environmental impacts as well as assessment of transport network development plans. Some examples of policy questions to be analyzed by strategic models are (i) what is the influence of central distribution on transport pattern and mode share, (ii) what is the competition between ports and (iii) what consequences will multimodal transport policy have on utilization of the different transport networks.

Most strategic modeling concepts applied in freight transportation have originally been developed based on the conventional four-step sequential model approach widely applied in passenger transportation. However, the context of four-step model in freight transportation is quite different from passenger transport as follows; (De Jong et al. 2004)

Production and attraction: In this step, the quantities of goods to be produced in various origin zones and the demand for goods that are attracted/consumed in various destination zones are determined (the marginal of origin-destination (OD) matrix). The output dimension is tons of goods. In intermediate stages of the production and attraction models, the dimension of freight flows could be converted to monetary units or vehicle units i.e. number of trucks used to transport goods.

Distribution: The flows for each commodity type transported between each origin and destination (each cell of the OD matrix) pair are determined.

Modal split: The allocation of the commodity flows to modes, for example, highway, rail and waterway. Flow Assignment: Freight flows are assigned onto the network of each mode in this step. Flows could be assigned directly in tons onto the network or converted into vehicle-units before being assigned onto the network.

From a research perspective in international development, not enough progress has been made in the debate between transportation costs and airborne trade as reflected by the low number of publications in leading journals addressing the issue. The debate between transportation and the increase of economic activity levels is in need of even further work. While more recent industrial organization and business literature, particularly logistics, has addressed air freight transportation’s role in the supply chain, it still lacks a broader perspective integrating it within the processes of production, distribution, and trade, particularly in developing countries. Consequently, gaps remain, not only in the international development literature but also in transportation geography and other disciplines, surrounding the relationships between air freight transportation costs and global economic activity, particularly for developing countries in which the shipping of goods by air may be the only realistic transportation choice (Radelet and Sachs, 1998).

From a wider public policy perspective, challenges for development arise not only from the infrastructure investments required for airports, airlines, associated facilities, and the logistics needed to achieve competitive aviation markets but also from the complexity of navigating the dense network of bilateral air service agreements and regulations restricting the growth of the international air transportation markets.

An important constraint is the lack of good quality and suitable time-series data on commodity flows tied to specific cities and urban regions (in addition to national levels of aggregation) that are needed to capture the processes and patterns of linkage between places of production and consumption (Janelle and Beuthe, 1997). In the absence of such disaggregated data and to unmask the interregional variations in the accessibility impacts of air freight transport, only data available for commodity flows to and from the US and the EU are used. All monetary values are current values, unless otherwise specified. As intuited from descriptive statistics, these flows likely capture most of the existing bilateral trade flows that travel by air. An associated concern to analyzing trade data is the difficulty in distinguishing how much of the extra trade from developing countries can be properly attributed to the availability of inexpensive air freight, as opposed to general globalization effects or the general trade liberalization measures of recent years.

A second challenge to assess transportation costs arises from methodological concerns that have proved appropriate to measure these costs domestically and internationally, in different legs of the supply chains including production, distribution, and consumption, as well as their role in reducing economic growth. Particularly relevant to this dissertation is the exploration using a gravity model of a possible causal effect of air freight on economic activity; i.e., the effect of air freight costs on export levels. No comprehensive approach has yet been developed to look at these relationships. In the absence of this, more partial analysis must suffice.

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References

Chiang, Y. S., Roberts, P., Ben-Akiva, M. (1980), “A Short-run Freight Demand Model: The Joint Choice of Mode and Shipment Size”, Center for Transportation Studies, M.I.T., Cambridge, Massachusetts.

De Jong, G., Gunn, H. and Walker W. (2004), “National and International Freight Transport Models: An Overview and Ideas for Future Development”, Transport Reviews, Volume 24, No.1, January, pp.103-124.

Janelle, D.G. and M. Beuthe (1997) ‘Globalization and Research Issues in Transportation,’ Journal of Transport Geography 5 (3): 199-206.

Kristiansen, J. and Petersen, M. S. (2002), “Goods Transport Modelling: Data and Methodologies”, The Danish Transport Council, Denmark.

Ortuzar, J. D. and Willumsen, L. G. (1990), “Modelling Transport”, John Wiley & Sons, Chichester, West Sussex, England.

Radelet, S. and J. Sachs (1998), ‘Shipping Costs, Manufactured Exports and Economic Growth,’ Paper presented at the American Economic Association Meetings, Chicago.

Tavasszy, L. A., Groothedde, B. and Ruijgrok, C. J. (2000), “Aggregate Models of Spatial Logistics”, Proceedings of The Third International Meeting for Research in Logistics, Québec, Canada.