Value Of Time

The “value of time” according to transport economics refers to the opportunity cost of the time that voyager spend on their journey. In other words, it is the amount that a traveler would be willing to pay in order to save time, or the amount they would accept as compensation for lost time. It’s a known fact that one of the main reasons behind the transport improvements is the amount of time that travelers can save. Using a set of values of time, the economic benefits of a transport project can be quantified to compare with the costs (which form the basis of cost-benefit analysis) (Ben-Akiva and Lerman, 1985). Values of time consist of the calculation of the non-monetary costs incurred as part of a journey, so that the generalized cost of the journey (a combination of both monetary and non-monetary costs) can be calculated.

Although the value of time is an entity which depends upon the purpose of the journey, but can generally is divided into two sets of valuations: working time and non-working time (wiki). Working time is subject to the forces of the labor market, and so can be valued in a relatively straightforward manner. The value of working time is the opportunity cost of that time to the employer, which is generally equivalent to the salary of the worker. For example, if a worker is on a salary of Ð'Ј15 per hour travels to a meeting, the value of time in that case is Ð'Ј15 per hour, because that is the amount the employer would be willing to pay to reduce travel time (as travel time can be considered to be "wasted", i.e. not spent working). According to the UK Department for Transport, calculation is done for the average values of time for travel on various modes of transport so that these values can be used to appraise transport projects. The non-working time is calculated the time spent outside work, which might include journeys to and from work and leisure journeys. Since this time is not valued in a market, it can only be estimated from revealed preference or stated preference analysis techniques, where the real or hypothetical choices of travelers between faster, more expensive modes and slower, cheaper modes can be examined.

Since last 25-30 years, discrete choice models have played an important role in transportation demand analysis .They are generally used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justifications. The discrete choice models are powerful but complex in nature. The art of finding the appropriate model for a particular application requires both a close familiarity with the reality under interest and a strong understanding of the methodological and theoretical background of the model (M. Bierlaire and Y. Vandevyvere. HieLoW, 1995). These models consider that the demand is the result of several decisions of each individual in the population under consideration. These decisions generally consist of a choice made among a finite set of alternatives. An example of sequence of choices in the context of transportation demand is described in Figure 1: choice of an activity (play-yard), choice of destination (6th street), choice of departure time (early), choice of transportation mode (bike) and choice of itinerary (local streets).

Figure 1: A sequence of choices

A model, as a simplified description of the reality, is able to provide a better understanding of complex systems. Apart from that, it allows for obtaining prediction of future states of the considered system, controlling or influencing its behavior and optimizing its performances. The complex system under consideration here is a specific aspect of human behavior devoted to some choice decisions. The complexity of this ``system'' clearly requires many simplifying assumptions in order to obtain operational models. Some of the assumptions about different entities can be as described below:

Decision maker

The decision-maker is generally assumed here to be an individual. The concept of ``individual'' may easily been extended, depending on the particular application such that we may consider that a group of persons (a household or a government, for example) is the decision-maker. The example described above in Figure 1 reflects the decisions of a household, without accounting for all potential negotiations among the parents and the children.

Alternatives

Analyzing the choice of an individual requires the knowledge of what has been chosen, but also of what has been left out. Therefore, assumptions must be made about alternatives, which were considered by the individual to perform the choice. The set containing these alternatives, called the choice set, must be characterized accordingly.

A discrete choice set contains a finite number of alternatives that can be explicitly listed. The corresponding choice models are called discrete choice models (D. A. Hensher and L. W. Johnson, 1981). The choice of a transportation mode is a typical application leading to a discrete choice set. In this context, the characterization of the choice set contains the identification of the list of alternatives. To perform this task, two concepts of choice set are considered: the universal choice set and the reduced choice set. The universal choice set contains all potential alternatives in the context of the application. Considering the mode choice in the example of Figure 1, the universal choice set may contain all potential transportation modes, such as walk, bike, bus, car, etc. The reduced choice set is the subset of the universal choice set considered by a particular individual.

Attributes

Each alternative in the choice set needs to be characterized by a set of attributes. The analyst needs to identify the attributes of each alternative that are likely to affect the choice of the individual. In the context of a transportation mode choice, the list of attributes for the mode car may include the travel time, the out-of-pocket cost and the comfort. The list for bus could include the travel time, the out-of-pocket cost, the comfort and the bus frequency. An attribute is not necessarily a directly observed quantity. It can be any function of the available data. For example, instead of considering travel time as an attribute, the logarithm of the travel time may be considered.

Empirical models

After identifying and characterizing both the decision-maker and all available alternatives, we will