Dramatic improvements in information and communication technologies (ICTs) are seemingly daily occurrences in today's society. The Internet, mobile phones and other wireless communications services, and broadband residential access are just a sample of such advances that people are beginning to take for granted. These new or improved products and services are changing the way many people work, shop, play, and live. It is important that we, as a society, understand these changes and their implications, and it is this desire that motivates our research.

We approach this subject from the travel behavior perspective. That is, we analyze the transportation-related impacts of advanced ICTs. Transportation-related impacts embrace a wide range of issues, including implications for land use and the environment. In addition, forecasting the travel impacts of a specific application such as telecommuting requires accurate forecasts of how much telecommuting will occur, and so we model the adoption of telecommuting as well. Our investigations include empirical studies of these transportation-related impacts, together with original conceptual frameworks within which to place the empirical results, and occasional reviews of the empirical evidence on a certain issue. A recurrent theme of these studies is that, contrary to initial optimistic views, the net impact of ICTs on travel is likely to be complementarity (generation) rather than substitution.

We are also collaborating on a related, NSF-funded, project with operations research professors Anna Nagurney (U. Mass. Amherst) and June Dong (SUNY Oswego). This project is among the first to combine the real transportation network with the virtual telecommunications network, and explicitly model flows through the combined network when individuals have a choice about reaching a destination (work, shopping) either by traveling there or by telecommunications.

More broadly, we are examining a number of interrelated travel behavior issues. One ongoing study deals with attitudes toward mobility. This study challenges the near-universal belief (among transportation professionals - apparently real people have known better all along) that the demand for travel is derived from the demand to engage in spatially-separated activities. Rather, we contend that to some extent travel is intrinsically desirable, and that this positive utility increases the demand even for daily local travel (not just fun vacation travel). We believe this is one reason that optimistic expectations for the substitution of travel by ICTs have not been realized. This work could have important implications for transportation planning, policy, and demand forecasting, all of which are predicated on the derived-demand premise. It is exciting to see empirical evidence for this contrary view mounting - not just in our multi-faceted study, but also in work conducted by other respected transportation researchers.

Our recent study on induced demand has also gone against the current mainstream. A number of studies have supported the controversial view that providing new transportation capacity will in and of itself stimulate the demand for more travel. This obviously raises questions about the wisdom of providing new capacity, and how to properly account for its full costs as well as benefits. Our empirical study, by contrast, found no evidence favoring the induced demand hypothesis. This prompted careful consideration and presentation of potential reasons for the differences across studies. We believe that our empirical results and the discussion of discrepant outcomes will provide a useful perspective to the continuing debate.
A third subject of our recent research has been "travel time budgets". Here, the theory goes that individuals have a fixed time budget for travel, the implication being that if they save travel time through one means (faster speeds through capacity enhancements or technological improvements, mixed land use patterns offering closer destinations, substitution of ICTs), they will simply travel more in other ways in order to keep their total travel time constant. This has been one foundation for the induced demand argument, and at first glance appears to contradict the assumption that travel is a derived demand. This is not necessarily the case, however: the travel added to meet a constant budget need not be travel for its own sake, but can be used to reach more distant but more attractive destinations. Trading off the disutility of travel for the utility of reaching a more desirable destination is completely consistent with the derived demand paradigm. Our review and analysis of the literature has convinced us that the TTB as it is usually meant (an observable, robust, nearly universal constant - 1.1 hours a day) is a myth, but we explore the reasons why the concept has been so persistent in the literature, and link it to our research on attitudes toward travel by suggesting that there is an unobserved and variable (but predictable) desired travel time budget that individuals strive to achieve. We also review the literature on approaches to modeling travel time expenditures, and propose a new utility maximization model for this problem.

Another theme of our research is the impact of land use patterns on travel behavior. In one paper, we present compelling empirical evidence for why the common practice of classifying residential neighborhoods as traditional (urban) or suburban (for the purposes of comparing their transportation patterns) is far too simplistic, and offer a more sophisticated yet practical alternative. A related paper constitutes perhaps the most rigorous evidence to date that land use and urban form themselves have little influence on travel behavior, once the influences of attitudinal predispositions, demographics, and other variables are controlled for. This suggests that using land use patterns as a transportation policy tool may not be very effective.

Findings from these studies offer valuable support to the decision-making processes of public planners and policy-makers as well as private industry. For example, by providing concrete empirical and theoretical insight into what the impacts of new technologies and applications are likely to be, these findings help inform decisions about how heavily and how best to promote such technologies to reduce congestion, improve air quality, and achieve other desirable social goals.