5. Implementation Issues

The methodology described will allow the quantification of the effects of transportation system improvements in relation to freight transportation. First order benefits include immediate cost reduction to carriers and shippers. Second order effects include the impact of improved logistics while keeping output fixed. Finally, third order effects consider additional gains from re-organization such as increased demand, new or improved products, and so on.

Section 3.2's message was that, in a world where marginal-cost prices prevail in all markets including those for transportation facilities, only information on the use made of improved transport facilities is necessary to measure completely the benefits it yields to its users and provider. Section 3.3's first message was that the absence of marginal-cost pricing on roads and other governmentally provided facilities makes benefit measurement much more difficult; determining the full benefit of an improvement requires analyzing not just its use but also the use of other facilities that the improvement affects. Section 3.3's second message was that, if elements of monopoly exist in the markets in which road users participate, sellers’ transportation demand schedules understate total benefits. In the simple model used to illustrate the phenomenon, monopoly hides a third of the benefits.

5.1 Information Requirements

Benefits measurement can be achieved equivalently through the transport demand schedule or the product demand schedule. In this paper, we chose to work with changes in transportation demand. It was argued that a different procedure must be used for monopoly as compared to a competitive market. In this case, benefits accrue to consumers through a consumer's gain from lower prices as well as producers gains through increased profits at their new profit maximization production levels.

In order to quantify overall economic benefits of infrastructure improvements on freight transportation, it will be necessary to quantify the following basic entities:

• Direct logistics cost savings, from travel time savings and reduced variability, due to highway improvements, AND indirect savings from logistics re-organisation (including the threshold at which re-organisation would occur) for a sample of firms;
• The elasticityη × C/T of transportation costs with respect to travel time savings (derived from the above);
• Current transportation demandVM₀ & elasticity of transportation demand with respect to travel timeη × VM/T;
• Current product demand (q) & elasticity of product demand with respect to price, for changes in firms' output (η),
• For the case of monopolies – marginal revenue and elasticities of marginal revenue with respect to logistics cost savings;
• Volume of freight traffic and product movement across transportation links by commodity and market,
• Average travel time and variability following highway improvements for various transportation network links and nodes. These values may also be a function of other parameters such as relaxed weight or height restrictions, port clearance characteristics, etc.

The first point demonstrates recognition of the need for a total integrated logistics system (ILS) cost view of a firm's operations as opposed to an isolated transportation cost component. From this information, the elasticity of logistics cost savings with respect to travel time and/or variability reductions can be estimated. A statistically valid sample of firms' responses by industry and by transportation link will provide a robust estimate of these elasticities aggregated at the system level. The survey will have to be carefully designed to capture re-organization effects. Additional work remains for developing strategies to obtain robust estimates of all parameters described above.

One final point can be made regarding the last point in our list. The most significant attributes of shipments after highway improvement are average travel time and travel time variability. Although these can be treated separately, an alternative approach could be to combine them with a percentile value expressed as the mean travel time plus a fixed number of standard deviations. This way, the two measures merge into one. The meaning of this new measure is that x percent of all trips can be achieved within the new time metric.

5.2 Reliance on Stated/Revealed Preferences

A previous NCHRP study [8] quantified the value of travel time savings and reliability based on a survey using a stated preference methodology. The results of this study should be considered as indicative only since the sample was restricted to 20 carriers, the characteristics of which were not controllable.

Using the stated preference approach, it was found that carriers on average value freight travel time savings at $144–$192 per hour (depending on model specification) and savings in schedule delay late at $371 per hour depending on model specification. These results confirm the importance of transit time and freight costs in shipping decisions.

Several recommendations were made to improve future valuation studies and their findings. These included:

• Increased sample size,
• Increased comprehension of stated preference experiments,
• Adjusting variable values with simulations, and
• Developing a theoretical model of carrier behaviour.

The study also recommended applying a mark-up factor of 2.5 to the value of time when the time savings are under highly congested conditions. The use of stated preference surveys may assist in the estimation of the elasticity of transportation costs with respect to travel time savings.

5.3 Way Ahead

The foregoing discussion does not completely address the following:

• Mode choice switching in response to logistics cost changes from road transport improvements[17]. It is possible that, for instance, some rail shipments would be moved by road due to lower freight rates, and that air shipments would also be moved by road due to shorter and more reliable delivery times. Cross elasticities would need to be estimated.
• Delays and hurdle rates for re-organisation of firm logistics systems. Firms have much invested in present infrastructure and may be reluctant to make immediate changes. What is the Net Present Value (NPV) of the future benefits when re-organisation occurs.
• The effects of e-business growth on transport demand (parcel transport vice TL or LTL)

If the methodology is endorsed, additional work remains for developing strategies to obtain robust estimates of basic parameters described in Section 5.1. Accounting for marginal cost pricing has also been described conceptually. Empirical estimation is the subject of a later research paper.

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