Potential Impacts of High Oil Prices on Transportation

For the transportation sector, six major types of interdependent impacts of high oil prices can be expected:

Usage level. This trend is clear and straightforward as users of a specific mode generally respond to higher prices by limiting or rationalizing (e.g. speed) their usage level. Transport operators, such as airline companies, can reduce the frequency of their services. It is a matter of price elasticity where an increase of price P will result in a usage level change of Q. This function is rarely linear. At first, price increases may have limited effects as they are simply absorbed with the expectation that they are a temporary condition. Once a specific price threshold is reached, then significant changes will result as marginal and extraneous usage will be cut until a new equilibrium is reached. Usage for this mode is said to have reached a paradigm shift. For instance, in 2008 the amount of driving in the United States fell sharply as well as the number of flights, on par with an increase in oil prices.
Modal shift. In conjunction with a drop in usage level for a mode, an alternative mode may capture the traffic of that change, in whole or in part, through a modal shift. Again, this process is commonly not linear and a modal balance (A/B) can shift rapidly once a price threshold is reached. Thus, an increase of price P may result in a substantial shift, Q(A/B), in the modal balance. A modal shift commonly takes place towards a mode which is less energy intensive (less elasticity) than the other. It can thus be expected that with higher oil prices some trucking will shift towards rail and that public transit will gain in market share.
Service area changes. Under a specific price level, each mode has an optimum service area; a distance at which it provides mobility in a cost effective fashion. Since each mode has a different elasticity, an increase in prices will have different impacts on the cost / distance function. For two modes, A and B, the same increase in energy price would create a different inflection of the cost / distance function where the range of mode B would reduced by R(B). Thus, mode A gains in market share. An example is trucking versus rail in North America where about 700 miles (1120 km) was considered to be a standard cutting point, but a rise in fuel prices has placed this range around 500 miles (800 km).
Gateway / Hub selection. A gateway is a point of interface between two systems of circulation. Since these systems have different elasticities, a rise in energy prices can eventually change their relationships, particularly the locations where intermodal transportation takes place. A shipping service using gateway port A and taking advantage of faster (but more energy intensive) hinterland connections may instead switch to gateway port B which is closer to customers. Although this change may result in longer total shipping times, the cost trade-off would make it acceptable. Higher energy prices are thus likely to reinforce gateways that have the most efficient hinterland connections, notably in terms of modal choice.
Network configuration. Enduring high energy prices are likely to trigger shifts in the configuration of transportation networks in terms gateways, hubs, routing and corridors. For instance an inland corridor may experience a change of the linkages with inland load centers that minimize road use and maximize rail. An airline may decide to abandon less profitable routes an offer more direct (point to point) services. An air transport network may experience a reconfiguration and an abandonment of marginal services, namely at small airports.
Supply chain propagation. A supply chain is composed of a series of inputs and outputs having a complex geographical and functional structure. Rising energy prices imply a wide variety of changes in the cost structure within a supply chain, namely a propagation of those costs. Procurement, manufacturing and distribution costs are all impacted to various degrees. It is possible for some of these costs to be absorbed through reduced profit margins and higher efficiencies, but they do eventually propagate and end up in higher consumer prices. The functional and geographical structure of a supply chain is a key element of the nature and extent of its costs propagation. At certain price level, some supply chains cease to be profitable and a reconfiguration becomes necessary.

It is assumed here that the origins and destinations remain relatively constant. However, it is clear that locational choices are significantly impacted as well. For instance, many comparative advantages in global trade are mainly based on low transport costs. In a higher energy prices environment, locational practices may change in several manufacturing sectors with sites closer to final markets, even if characterized by higher labor (or input) costs, may be advantaged.

Copyright © 1998-2008, Dr. Jean-Paul Rodrigue, Dept. of Economics & Geography, Hofstra University. For personal or classroom use ONLY. This material (including graphics) is not public domain and cannot be published, in whole or in part, in ANY form (printed or electronic) and on any media without consent. Permission MUST be requested prior to use.