Recommendations for utilizing the model developed in this research for

In light of these implications addressed above in section 6.4.1, this thesis contributes in this regard – the developed model (the accessibility model developed within the utility-based paradigm and its discrete choice model-form variant) in this thesis provides an alternative to the current available models in the literature and in practice. This model provides an alternative to more effectively measure the effects of both forms of ICT on accessibility, as it explicitly takes travelers’ choices and preferences, and both the “I” and the “C” in ICT into consideration. This contributes to the lack of such models in the literature and in practice. This section further discusses and provides recommendations with regard to how to apply the developed model in case of studies, and how the model can be utilized in actual planning and policy-design processes.

One way is that the model can be used in an exploratory sense to identify possibilities for obtaining synergy between investments or other policies in different forms of ICT. For example, the model may be applied to identify in what situations investments in travel information and/or teleworking facilities may lead to a situation where benefits of these investments in the two types of ICT might reinforce one another, leading to additional user benefits at least in terms of increases in accessibility.

Another way is to utilize the model to predict and quantify accessibility benefits of ICT-investments in general. These effects can subsequently be used in the assessment (e.g., cost-benefit analyses) of policy options in transportation planning – ultimately leading to a more informed process of policy-development.

However, it should be noted that it is critical to properly specify the developed model according to real-world situations, and to empirically estimate and validate the model in advance of any applications in actual planning and policy-design processes, for the following reasons.

First, to identify the choice set composition in real-world situations – the alternatives that are available in reality and actually considered by travelers when they make choices – is important before applying the model. As heterogeneity exists among individual travelers, the effects of the same ICT-related services on different traveler’s accessibility differ. The heterogeneity in terms of the alternatives available and actually considered by different travelers should be considered in using the model to quantify accessibility benefits of ICT in order to more objectively evaluate the follow-up planning and policy design. It becomes more critical to properly define individuals’ perceptions of the choice sets when exploring the synergy effects between travel information and teleactivities. For example, while the decision to acquire travel information, in general, may be often spontaneous, the choices of teleworking can be driven by (relatively) long-term factors such as the obligation of child-care and the residential location. For the people who decide to telework only based on these long-term factors rather than short-term factors such as commuting times, the option of travel information to assess the expected commuting time before commuting would probably not affect their choices of teleworking and therefore no synergy effects would be achieved in this example.

Secondly, it is important to properly identify relevant alternative attributes related to travel information and teleactivities in the model. As shown by the survey study (Chapter 3), in addition to those that are considered in the study, there are many other factors that are relevant to travelers’ preferences for travel information and teleactivities. Literature also identifies a wide range of factors that could impact travelers’ choices of travel information and teleactivities (see Chapter 2). To properly define related attributes in operationalization of the model in real-world situations according to the particular study aim becomes increasingly important.

Having addressed the importance to properly specify choice sets, choice alternatives and alternative attributes in model specifications, another challenging yet important task is to collect sufficient empirical data in order to estimate and validate the specified model.

It is critical for analysts to correctly observe and measure travelers’ perceptions of choice sets, alternatives, and attributes (including the uncertainties related to alternative attributes). The research (travel simulator study and model estimation) in

Chapter 5 shows that the model can be successfully estimated based on travel simulator data, and the estimated model is able to capture many of the behavioral mechanisms that have been presented by the sample in the study. It is also expected that it does not pose particular difficulties when using stated choice data. However, it becomes difficult and hence becomes a challenge when the model is to be applied to case studies and to planning and policy-designing where revealed data are often used. Great care must be exercised in terms of measuring traveler perceptions of choice sets, choice alternatives and attributes (including the associated attribute- uncertainty).

Finally, the developed model is built around several assumptions. It is important to note these assumptions when applying the model in practice and in turn interpreting and using the results derived from the applications for planning and policy-designing.

First, the model places fairly strict assumptions on traveler’s behavior, in which the traveler is assumed to be fairly rational and a utility-maximizer, and as such the measure of accessibility is conceptualized and operationalized within the RUM (random-utility-maximization) paradigm (i.e., the LogSum approach to accessibility (Ben-Akiva and Lerman, 1985)). As addressed in Chapter 2 and also reflected later in section 6.5, despite the advantages, the assumption of travelers being rational and utility-maximizers in such conceptualization and operationalization of accessibility (and hence the subtle computations and relations for the value of teleactivity and travel information assumed in the model) may be considered as not realistic from a psychological or bounded rationality perspective. Some of the assumptions are hence open to debate due to their (lack of) behavioral validity. It should also be noted that the operationalization of the accessibility measure as a LogSum in this research is one option among many others, and all the results derived in this research given the related assumptions might not hold for different ways of operationalization. Secondly, the model focuses on individual accessibility rather than on aggregate accessibility. That is, the model is developed from a perspective of a representative individual traveler and considers the individual’s choices of ICT, while aggregate accessibility should also take into consideration interactions between people (e.g., the interactions of ICT-use between different household members). Thirdly, the model focuses on expected (valuation of) accessibility at the time of making the decision instead of experienced or realized accessibility. That is, the model focus on the moment right before an individual has received information and/or right before he or she has made choices between location-based alternatives and, possibly, the teleactivity-option. In addition, this thesis does not consider long-term accessibility effects related to, for example, changes in land use patterns. Another assumption is that the individual considered in the model is assumed (to know that he or she is) fully capable of using different forms of ICT. That is, the potential limitations in people’s ICT-use capabilities are not explicitly considered. Furthermore, in the model, the travel information is assumed to be fully reliable, while it is often perceived unreliable in reality by travelers. It is therefore likely that any application of the model without any relaxation of this assumption would yield a somewhat optimistic picture of the impact of travel information on accessibility. A final assumption that is made is that the information only refers to known travel alternatives. As such the model does not consider the situation where the information service is also able to generate previously unknown alternatives, which is considered as one possible aspect for further model extension.

Each of these assumptions has been made to keep the model’s tractability at an acceptable level. However, it is important to be aware of these assumptions when the model is to be applied.