Transportation Geography Research Paper

1. Understanding Flows

Transportation is critical to contemporary society. In the USA, the transportation sector represents 11 percent of gross domestic product (GDP), and transportation is the second largest expenditure category for households. Economic growth is closely linked with transportation: movement of people and goods is positively associated with GDP. Why is transportation so critical, and what motivates these flows? Transport is costly, both in terms of time and money. Hence there must be some benefit to justify incurring these costs. Flows occur when the benefits derived from transport exceed transport costs. Flows can be understood in terms of a few basic principles.

1.1 Flow Depends On Transport Costs And Gains From Trade

The first principle of flows can be illustrated with the journey to work. Consider a worker: the cost of commuting is incurred in order to remain employed. How much is a worker willing to pay in order to receive a given wage rate? The average US commute is about 23 minutes (based on 1995 national survey data); and just 4 percent are longer than 1 hour. Since commute costs reduce the effective wage (wages net of commute costs), it follows that as commute costs increase, fewer people will be willing to accept employment at a given wage level. The converse also holds: as commute costs decrease, more workers will be willing to accept employment at a given wage level. The likelihood of flow taking place is a function of transport costs and benefits from trade. This principle applies to goods and information as well as people.

1.2 Declining Transport Costs Are Associated With Increased Flows

Transport cost includes both time and money costs. Technological change and infrastructure investment have increased travel speeds and reduced unit costs. The late nineteenth century transcontinental railroad offered trips from New York to San Francisco in 6 days; the trip by air today takes about 5 hours. Similarly, France’s high-speed train offers service from Paris to Lyon in 2 hours. Around 1900 the same trip would have taken 6 or 7 days. These improvements also apply to intrametropolitan travel, but to a lesser extent, since intrametropolitan travel has so far been limited to surface transport modes. Transport cost has also greatly declined. For example, it is estimated that the average cost of commuting by streetcar in the USA at the turn of the twentieth century was about 20 percent of the average daily wage. Today the average cost for auto commuters is about 7 percent (Giuliano 1989).

Increases in speed result in ‘time/space convergence,’ a reduction in friction of both distance and time (Janelle 1995). Time/space convergence is illustrated in Fig. 1(a) and Fig. 1(b) for all of Europe, excluding Russia and the Ukraine (Spiekermann and Wegener 1994). Figure 1(a) provides actual spatial relationships and is calibrated on a homogeneous travel speed of 60 km per hour^-1 . Figure 1(b) provides a picture of temporal relationships, based on the 1993 rail transport network. Note that Paris is ‘closer’ to major cities of Switzerland, The Netherlands, and Amsterdam, while in East Europe, Bucharest and Sophia are both ‘further’ from one another and from Central Europe. Time/space convergence is associated with globalization and the emergence of the time- sensitive economy (Janelle and Beuthe 1997).

Large reductions in transport costs have resulted in equally large increases in transport demand. Figure 2 shows the increase in US passenger-miles for private vehicles and for domestic air service, 1960 through 1995. Figure 3 shows the increase in ton-kilometers of surface freight transport for 10 European Union (EU) countries, 1970 through 1996.

1.3 Declining Transport Costs And Increased Flows Are Associated With Development Of The Space Economy

Historical development of the space economy is explained in part by declining transport costs. In the preindustrial era, nonmotorized transport was slow and difficult. There was little exchange between cities, because transport costs exceeded benefits at very short distances. Technological changes that reduce transport cost, e.g., ‘space adjusting technologies,’ allow regions to exploit comparative advantage, engage in regional specialization, and expand their areas of economic influence (hinterlands).

Nonmotorized modes of the preindustrial era were replaced with motorized modes in the nineteenth century: steamships and railroads. These technological advances greatly reduced the cost of intercity travel and hence led to large increases in both passenger and goods transport. The railroads in the US connected vast regions, resulting in the emergence of an integrated national economy. Railroads also contributed to the development of the national economies in Europe. Change accelerated in the twentieth century with the emergence of paved roads, autos and trucks, and the development of commercial air transport.

A famous example of the impact of reduced transport costs is the Erie Canal, built in 1825 to open a waterway between Lake Erie and New York by connecting Lake Erie to the Hudson River. The reduction in transport cost was dramatic: over-the-road transport cost 20 times as much per ton-mile as shipping via canal; travel time was 20 days over the road and 6 days via canal. Goods movement greatly increased. New York’s hinterland was extended through the entire northeast region and its position as the US center of international trade and the dominant city in the US urban hierarchy was consolidated.

Empirical research on the relationship between transport and economic development is mixed. Research on both developed and less developed countries indicates that transport infrastructure is a necessary but not sufficient condition for economic development (Hoyle et al. 1998). The first links of major networks (rail, highway) have generally had significant impact, while the impact of additional links tends to be marginal (Munnell 1992). There are many failed examples of transport infrastructure investments made to promote trade and economic development, as for example the US efforts to promote economic development in the Appalachian region.

1.4 Transport And Urban Spatial Structure Are Interdependent

Urban spatial structure is the outcome of economic, social, political, and cultural forces. Within the complex process of urban evolution, however, transportation has played a major role. The historical relationship between transport and urban form is well-established (Muller 1995). With faster and cheaper transport has come more decentralized and dispersed spatial structure, and as activities have become more spread out, travel has increased. Decreased accessibility has been offset by increased travel speeds.

US cities in the latter half of the nineteenth century were crowded and congested. Industrialization had generated a surge of urbanization. The lack of motorized transport forced population and businesses to co-locate in close proximity to one another. Electricity-powered rail transport proved to be the breakthrough technology. Starting in the late 1880s, urban railways allowed cities to grow outward as workers took advantage of the new mode to seek less crowded residential locations outside the city core, and gave the city center special dominance as the center of the intracity transport network. Urban rail was followed in the 1920s by the automobile and truck. Development of the highway network proceeded rapidly, increasing travel speed, and allowing ever more rapid decentralization. The post-World War II freeway era continued these trends, with both jobs and population decentralizing, and with the emergence of suburban activity centers. European cities have followed a similar trajectory, but under quite different social, economic, and political conditions, and with—to date—less dramatic spatial change.

The relationship between transportation and urban form has been the subject of much theoretical research. The familiar ‘standard model’ of urban location and spatial structure as developed by Alonso (1964) and others, serves to illustrate the close relationship between transport costs and urban spatial structure. Consider the simple case of a city where all employment is located at the center, transport cost is a linear function of distance, and households trade off housing and commuting costs in making their residential location decisions. How will workers locate themselves with respect to the city center? Clearly net wages will be highest at the city center, where transport costs are near zero, hence workers will prefer location near the center, and locations near the center will be valued higher than locations away from the center. If workers could bid on locations, the result would be a gradient of both land prices and population density that declines with distance from the center. Declining transport cost results in less steep density gradients, as the relative value of living near the city center declines. Decreases in the density gradient have been documented for metropolitan areas around the world (Mills and Hamilton 1994).

2. Research Issues

Increasing concerns regarding the social and environmental consequences of urban transport, structural changes resulting from development of information and communications technologies, and a changing institutional context in transportation policy decision-making are affecting the research agenda of transport geographers (e.g., Hanson 2000). This section discusses three areas of current research: travel behavior; transportation, land use, and environmental costs; and transportation and information technology.

2.1 Travel Behavior

Transport geographers have examined personal travel at both aggregate and disaggregate levels of analysis.

2.1.1 Aggregate Models. Various forms of spatial interaction models have been applied in aggregate analysis, most commonly the gravity model. The gravity model incorporates two basic factors that affect the level of flow between places: the population of each place (or some measure of potential for flow), and the distance between them:

The model in Eqn. 1 states that flow from origin i to destination j is a positive function of (a)

the potential of the origin zone for generating trips and (b) the relative attractiveness of the destination zone, and is a negative function of the distance between them. Gravity models have been applied to many topics, from intercity transport to local shopping flows. They have been extended to account for alternative travel destinations (intervening opportunities) as in the example above, differences in nodal characteristics, and differences in travel costs across modes or links (Taaffe et al. 1996).

The widespread availability of geographic information systems (GIS) has made possible the use of gravity formulations to measure accessibility patterns of different modes or population segments and hence analyze such policy issues as the distribution consequences of urban transport investment. The gravity model plays an integral role in state-of-practice urban transportation planning models: trip distribution (the allocation of trips to specific zonal destinations) is accomplished using a model that accounts for the relative attractiveness of zones as destinations and expresses distance as a generalized cost.

2.1.2 Disaggregate Models. Understanding the travel patterns of individuals is a more complex task. Geographers and economists began to address the issue in the 1970s with the application of utility theory. In this case, travel decisions are discrete choices made on the basis of the utility of each alternative available. The utility of an alternative is a function of its attributes and the attributes of the individual making the choice. Since utility cannot be observed directly, utility-based models estimate the probability that a given alternative will be chosen.

The first applications of discrete choice were made to mode choice problems; later applications included destination choice, route choice, and car ownership. Mode choice models are now routinely used in transportation planning applications. Models have been extended to account for conditional or sequential choices, as for example, mode choice given car ownership. Multilayered models are one approach to developing integrated transportation planning models (Anas et al. 1998).

A major theoretical issue in travel behavior analysis is what should be predicted: the trip or the underlying behavior that motivates the trip. Given that travel constitutes a disutility, it is argued that understanding travel requires understanding activity patterns. Termed activity analysis, this approach to travel behavior predicts travel choices as a function of activity choices (Kitamura 1988).

The roots of the activity analysis approach to travel behavior lie with the Swedish school’s time-space geography (Hagerstrand 1970). In this case the individual has a set of resources (time, money, vehicles) and a set of constraints (schedule, physical, and coupling constraints) that define the feasible set of activities they may accomplish over the course of a day. Hagerstrand terms this feasibility area the spacetime prism. Activity-based models seek to capture the complex process of choosing a set of daily activities and their location, timing, and sequencing, given feasibility constraints.

Utility-based models assume rational behavior. Travel choices are a function of resources, preferences, and supply characteristics. Some geographers and planners argue that the rational behavior assumption is too strong; people act as much on attitudes and perceptions as on resources and constraints. Travel choices are joint choices (resources and tasks are allocated among household members) which reflect (and affect) underlying attitudes and perceptions. They therefore borrow somewhat from the disciplines of sociology and psychology.

2.1.3 Travel As Having Positive Utility. Travel has historically been considered a derived demand. However, some recent research suggests that this may not be the case (Mokhtarian and Salomon 2001). People may derive pleasure from travel to a far greater extent than assumed. They may conduct activities outside the home in order to travel, or they may travel to more distant destinations because the travel itself is part of the activity experience (e.g., take a drive and go out to dinner). Transportation planners have consistently under predicted the growth in travel demand, even accounting for unanticipated changes in demographics, income levels, fuel prices, and other key factors. Positive utility of travel may explain people’s greater-than-predicted propensity to travel.

The concept of travel as having positive rather than negative utility has significant policy implications. On the one hand, it helps to explain why travel demand is highly inelastic. On the other, it suggests that efforts to reduce travel for environmental or other reasons will be most difficult to accomplish.

2.1.4 Travel Budgets. Finally, many geographers argue that time budgets determine travel. People make about four (one-way) trips per day and spend an average of about 1.3 hours each day traveling. These averages have been observed consistently both over time and across places, ranging from preindustrial agrarian villages to the major developed nations of the world. This consistency has led to the concept of a time budget: people allocate a given amount of time to traveling (Zahavi and Talvitie 1980). Hence distance traveled is a function of transportation technology and infrastructure. As travel speeds increase (say by construction of a new highway or rail line); people will use travel time savings to travel further distances. There are two main criticisms of the time budget. First, taken to its logical extreme, it conflicts with notions of rationality and utility-maximizing behavior. Second, the empirical observation may be an artifact of central tendency, and therefore may have little value as an explanation for human behavior.

2.2 Transportation, Land Use, And Environmental Costs

Transportation provides many benefits to society. As noted earlier, an efficient transportation system is critical to economic growth. People have greatly benefited from cheap and efficient mobility. The value placed on mobility is revealed in willingness-to-pay: households devote a significant portion of income to transportation, and the public has been remarkably willing to tax itself to invest in transportation infrastructure. However, mobility generates an array of environmental costs, notably air and noise pollution, traffic congestion, accidents, damage to the natural environment, and possibly global warming (Greene et al. 1997). In addition, everyone has not realized the benefits of mobility. Those without access to a private vehicle, for example, have suffered a relative decline in accessibility as activities have dispersed and public transport has become an increasingly poor substitute for the car. Concerns about these external costs are intensified by observation of current trends (Fig. 2 and Fig. 3). Extrapolation of these trends leads many to believe that policy actions must be taken to move toward a sustainable transport system (Newman and Kenworthy 1998). Hence transport is a key issue in the sustainability debate.

Sustainable transport has many dimensions. Strategies to increase sustainability range from improving transport technology to reducing travel via regulation, pricing, or land use policy. Transport geographers have focused on land use. The relationship between accessibility and travel is well known. Some geographers make a distinction between accessibility and mobility (e.g., Hanson 1995). Accessibility measures potential—the relative location of opportunities—and is a function of spatial form and transportation supply. Mobility measures outcomes—how much a person travels. Mobility is a function of both accessibility and travel resources. It follows that as accessibility increases, activities can be conducted with less travel, all else being equal. It is therefore argued that one promising strategy for sustainable transport is to promote higher density development. Proponents argue that such a strategy preserves accessibility while reducing mobility: activities can be accomplished closer to home, and greater access may allow more non-motorized travel. The overall effect is to reduce private vehicle travel and its associated external costs.

A corollary to this strategy is to expand public transport while imposing restrictions on the private vehicle. Public transport is seen as less damaging to the natural environment and contributing to urban quality of life. Effective public transport depends upon concentration; supportive land-use policies will create the trip densities required to support transit. Conversely, the presence of transit will promote higher density development (Newman and Kenworthy 1998).

Whether such strategies can succeed in reversing current trends in transport and urban structure is the subject of many debates. A positive correlation between development density and measures of private vehicle use has been observed in several empirical studies, but their validity is questioned on several grounds, e.g., whether less car use is offset by congestion, whether the relationship is significant at densities that realistically could be achieved, or even whether a causal link exists. Studies that control for household characteristics and other relevant factors show a much weaker (and sometimes insignificant) relationship between density and private vehicle use for all but extremely high densities (Pickrell 1999). Other research has examined neighborhood level characteristics and its relationship to transit use or walks trips, with very mixed results.

The empirical research examines whether travel patterns would change, if land use and transport policies were used to promote reconcentration and less private vehicle use. The more interesting question is whether reconcentration and reduced private vehicle use at a scale sufficient to generate significant environmental benefits is feasible. Views on this question are decidedly mixed. Some argue that long-term economic and technological trends suggest continued decentralization and dispersion, while rising incomes will generate increasing demand for private vehicle travel (e.g., Morrill 1991, Giuliano 1999). Hence environmental costs should be addressed via technology, pricing, and regulation. Others argue that the social and environmental consequences of not changing these trends are enormous, and it is assumed that the political will necessary to achieve major change will therefore be found (e.g., Newman and Kenworthy 1998).

2.3 Transportation And Information Technology

The emergence of the information economy is an increasingly important theme of transport research. Advances in information and communications technology (ICT) are affecting all aspects of society and the economy. Transport geographers have focused primarily on direct effects of ICT: to what extent does ICT serve as a substitute for transport? Most of this research addresses telecommuting (working at home or at a nearby work center by communicating electronically with the office) (Mokhtarian 1998).

Telecommuting eliminates or shortens the daily commute. Remote offices, home offices, and mobile offices also reduce the work trip. Empirical research shows that travel savings from fewer trips to and from work are not entirely offset by nonwork travel. People are more likely to telecommute if they have very long commutes, generating travel savings in the short run, but suggesting that the opportunity may also motivate people to live even farther from their jobs. In addition, social and institutional constraints have so far prevented telecommuting from becoming a common practice.

Far more widespread than telecommuting is the use of telecommunications in place of personal contacts. Of course the telephone has served this purpose for a century. The difference now is in the variety and efficiency of communications devices, notably the now ubiquitous email. Interaction is growing; business and personal networks are increasingly complex and extensive. It seems reasonable to expect that more interpersonal connections would result in more rather than less physical interaction.

The impacts of ICT on work patterns are potentially far more extensive than these direct substitution effects. ICT is fundamentally changing the structure of the workplace and the organization of work. Labor statistics show that temporary work and self-employment are increasing more than proportionately with job growth. There is some evidence of declining job tenure. Changes in the structure of work will no doubt affect commuting and residential location patterns. Will households increasingly choose residences on the basis of neighborhood quality and other amenities, given uncertainty of future job location? Will access to job opportunities become more important, promoting location close to large job centers? Research on these questions is just beginning.

The impacts of ICT on firm location and on the structure of production also have enormous implications for transport. Outsourcing, customized production, flexible production, and just-in-time management of production and distribution characterize restructuring. The emergence of spatial production networks implies increased goods movement and growing dependence on an efficient global transport network.

Preliminary research indicates strong complementarity between ICT and freight transport (Plaut 1997). The freight transport sector has rapidly adopted ICT to increase speed and efficiency of freight flows. The growth of multinational firms and global trading networks also suggests more long distance passenger transport. While ICT allows for rapid and cheap electronic communications, the need for face-to-face communication among global managers remains. Hence the rapid increase of commercial air transport observed since the 1980s.

Time/space compression is bound to increase as the boundaries between transportation and communication break down. Indeed, ICT calls into question the very notion of accessibility as an essentially physical concept (Hodge and Janelle 2000). The direct and indirect effect of ICT will be a major area of future research in transport geography.

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