Supply And Demand Considerations for Over-The-Road Transportation

This is a world of scarcity whereby resource are limited and the consumption of a good or service means foregoing another good or service. Economists call the description an “opportunity cost,” one of the basic fundamentals in economics (Fricker & Whitford, 2018). This paper therefore compares and contrasts the demand and supply and discusses market equilibrium of Over-The-Road Transportation

In Over-The-Road Transportation, the most critical component that users face is the time spent on transit which could be spent on other pursuits like engaging in leisure or getting involves in other income generating activities (Fricker & Whitford, 2018). The value of the other activities represent he opportunity cost. Beside, Over-The-Road Transportation is associated with safety because on transit, people face the risk of property damage, injuries, and in worst cases death as a result of crashes.  The value of the risks is associated with the willingness to pay for reduction of risks of the adverse outcomes (Ritchie & SUN, 2018). Also, Over-The-Road Transportation incurs direct costs like cost for vehicle operation, like maintenance, oil, tires, fuel, travel related taxes, and depreciation.

Demand on Over-The-Road Transportation is associated with the value consumers have for time in a given manner, place, and time and is measured by their willingness to pay for the trip. Some trips are highly valued while others are less valued. Thus the level of demand and cost of travel is depicted in a demand curve where the cost of highway travel is inversely proportional to the volume of traffic (Ritchie & SUN, 2018). The demand curve slopes downwards which reflects a basic economic truth whereby demand increases with decline in price of goods and services. When the price of trips is high, few people are willing to make few trips unlike when the price is low; people are willing to make more trips.  Also, the numeber of people in origin and destination of goods and services determine the demand of goods and service hence the number of routes made to deliver the goods and services. Also, the elasticity of demand is affected by the availability of close substitutes where people can have a choice to choose between goods or have no choice but to pay high prices for products (Fricker & Whitford, 2018). In Over-The-Road Transportation, telecommunication can offer a good substitute during peak periods.

With regards to the supply side, Over-The-Road Transportation, congestion delay is the decline in speeds of ravel as the traffic volumes approach the capacity of the road-way (Fricker & Whitford, 2018). The result is that there exists relationship between traffic volumes and highway user costs on a given road (Ritchie & SUN, 2018). When the volumes are low, there is a relatively constant cost with respect to volume. However, the user costs begin to raise when traffic volumes increase and the point of occurrence is determined by the road capacity. 

Lastly, market equilibrium for the Over-The-Road Transportation is achieved when there is a balance between demand and supply which determines market-clearing quantity and price (Ritchie & SUN, 2018). At this point, consumers are willing to pay the price for a given amount of a product. The point of equilibrium determines how high volumes of traffic will be and how their respective average costs will be at the volume level (Fricker & Whitford, 2018). When the demand is low, relative to the road capacity, the road will be uncongested but the price will remain relatively constant regardless of the change in volume (Ritchie & SUN, 2018). However, when the demand is high, congestion in the roads increase leading to sharp increase in both traffic volumes and user costs with continuous increase in demand.

References

Fricker, J. D., & Whitford, R. K. (2018). Fundamentals of transportation engineering: A multimodal systems approach. Place of publication not identified: The Scholar Collection. Ritchie, Stephen G, & SUN, YUE. (2018). Commodity Based Freight Demand Modeling Framework using Structural Regression Model. eScholarship, University of California.