Transportation and Urban Planning Description of a research program at Aalborg University. By Professor Petter Næss, Aalborg University, Department of Development and Planning. Revised February 9, 1999 INTRODUCTION...................................................................1 DISTANCES, ACCESSIBILITY AND NEEDS.............................................3 STATUS OF KNOWLEDGE REGARDING THE INFLUENCE OF SOME URBAN FORM VARIABLES ON TRAVELING DISTANCES, MODAL SPLIT AND ENERGY USE................................5 DENSITY.......................................................................5 LOCATION OF RESIDENTIAL AREAS.....................................................6 LOCATION OF WORKPLACES...........................................................7 GEOMETRICAL SHAPE...............................................................8 REGIONAL DEVELOPMENT PATTERN......................................................8 PUBLIC TRANSPORT, ROAD SYSTEM AND PARKING POSSIBILITIES..............................10 THE RESOURCES, VALUES AND PREFERENCES OF THE TRAVELERS........................11 THE LIFESTYLE CONCEPT...........................................................12 RESEARCH ISSUES GIVEN PRIORITY WITHIN THE PROGRAM “TRANSPORTATION AND URBAN PLANNING”.....................................................................17 METHODOLOGICAL CONSIDERATIONS.................................................18 DATA SOURCES..................................................................20 GEOGRAPHICAL AREAS OF INVESTIGATION...........................................23 STUDY OF THE REGIONAL PATTERN OF DEVELOPMENT.......................................23 STUDY OF LIFESTYLE DOMAINS AND TRANSPORTATION.......................................25 PERSONNEL AND WORK SCHEDULE...................................................25 REFERENCE GROUP...............................................................26 COOPERATION WITH OTHER RESEARCH PROJECTS......................................26 REFERENCES.....................................................................0 0
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Transportation and Urban PlanningDescription of a research program at Aalborg University.By Professor Petter Næss, Aalborg University, Department of Development and Planning.Revised February 9, 1999
DISTANCES, ACCESSIBILITY AND NEEDS.................................................................................................................3
STATUS OF KNOWLEDGE REGARDING THE INFLUENCE OF SOME URBAN FORM VARIABLES ON TRAVELING DISTANCES, MODAL SPLIT AND ENERGY USE................................................................................5
DENSITY............................................................................................................................................................................5LOCATION OF RESIDENTIAL AREAS...................................................................................................................................6LOCATION OF WORKPLACES.............................................................................................................................................7GEOMETRICAL SHAPE.......................................................................................................................................................8REGIONAL DEVELOPMENT PATTERN.................................................................................................................................8PUBLIC TRANSPORT, ROAD SYSTEM AND PARKING POSSIBILITIES..................................................................................10
THE RESOURCES, VALUES AND PREFERENCES OF THE TRAVELERS.............................................................11
THE LIFESTYLE CONCEPT................................................................................................................................................12
RESEARCH ISSUES GIVEN PRIORITY WITHIN THE PROGRAM “TRANSPORTATION AND URBAN PLANNING”......................................................................................................................................................................17
DATA SOURCES..............................................................................................................................................................20
GEOGRAPHICAL AREAS OF INVESTIGATION.........................................................................................................23
STUDY OF THE REGIONAL PATTERN OF DEVELOPMENT..................................................................................................23STUDY OF LIFESTYLE DOMAINS AND TRANSPORTATION.................................................................................................25
PERSONNEL AND WORK SCHEDULE........................................................................................................................25
Transportation and Urban PlanningDescription of a research program at Aalborg University.By Professor Petter Næss, Aalborg University, Department of Development and Planning.Revised February 9, 1999
IntroductionThe theme of the research program “Transportation and Urban Planning” is how physical planning can be used to influence the extent and character of transportation, and thus also energy use for transportation. Combustion of oil, coal and gas causes pollution, which both damages people’s health and the natural environment, and which is probably in the process of bringing the global climate out of balance. Therefore, it is an important goal for environmental protection to limit, and preferably reduce, the energy use in the society. A high extent of transportation also implies a number of other environmental disadvantages, such as traffic accidents, noise and the encroachments of previously unbuilt areas or existing buildings represented by the traffic installations themselves.
By physical planning, we primarily mean planning according to the Danish Act on Planning (Lov om planlægning), particularly preparation of the main structure of the municipality plan with division into country zone and urban zone, and preparation of local plans and regional plans. The program does not aim to evaluate the effectiveness of such planning regarding its actual ability to control land use and building activity. Instead, focus is directed towards the way in which we use land and localize and shape developmental areas, takes part in determining how extensive the transportation will be, with what conveyances it will be made, and how much energy it will require. The program concentrates on transportation of people. This implies that the influence of urban planning factors on freight will not be discussed.
There is a mutual influence between land use and transportation. Changes in land use may cause changes in transportation activity. Such changes may accomplish that it may be considered desirable or necessary to change the transportation system. Land use changes may also influence the transportation system directly, for instance in the form of investments in roads and public transport connections to planned development areas. Changes in the transportation system may, on the other hand, accomplish land use changes, for instance by changing the balance between the attractiveness of different conveyances, or by making it less time consuming to make longer journeys. In addition, changes in the transportation activity may influence land use directly, for instance because reduced travel activity due to considerable increase in fuel prices makes the outskirts less attractive as development areas.
These mutual interactions between land use and transportation is shown schematically in Figure 1. Of the different lines of influence shown in the figure, the program primarily concentrates on one, namely the influence of land use on transportation activity. To some degree, however, the influence of the transportation system on the transport activity will also be investigated.
The geographical distribution and structure of the building stock (the pattern of development), the mutual location of different functions (the location pattern) and the design of the transportation system make important conditions for the extent of transport, the distribution between different conveyances and the energy use for transportation. Yet it cannot be concluded, for instance from the shape and location of a home, how much energy for transportation is actually being used by the inhabitants of this particular building. Very much also depends on the inhabitants’ characteristics, for instance their professional activity, whether there are children in the household, the location of workplaces and relevant schools and shops, and last, but not least, what kind of lifestyle and habits the inhabitants have.
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Changes in transportation activity
Changes in the transportation system
Changes in land use
Figure 1 Relations between changes in transportation system, transportation activity and land use. Adapted from Needham (1977:134)
A basic hypothesis within most research on relations between physical/functional urban structure and transportation is that the material structure in an urban area forms a set of incentives, influencing on people’s transportation activity. It is presumed that people will try to reach their daily activities with the least possible inconvenience. The inconvenience may include economical expenses, time use and other sorts of efforts. As a measure for a person’s total inconveniences by doing a journey, transportation economists have introduced the concept of generalized travel costs. The shorter distance to the destination, and the faster, cheaper and more comfortable means of transportation available, the lower are the generalized travel costs for reaching the destination, and the higher is the accessibility. In addition to the accessibility, the journeys to a locality of course also depend on the reasons people have for going there. Here, factors like the number of and the variety of workplaces and service functions, or the number of inhabitants, will influence the number of travels attracted by a certain locality.
In practice, also a number of factors other than the generalized travel cost influence people’s transportation activity. These factors include both personal conditions (like for instance age, sex, income etc.) as well as people’s standards of value, norms, life style and acquaintances. Human action is influenced by both structural limitations and incentives (of which the material urban structure makes up only one of several categories), and by the individuals’ resources, preferences and wishes. It is not the development structure and the location pattern in themselves that generate transportation, but people living and working in specific places, visiting different destinations or transporting goods. The resulting transportation pattern is dependent on people’s resources, needs and wishes, modified through the limitations and the possibilities caused by the structural conditions of the society (see Figure 2).
The importance of the influence from the physical/structural conditions, as compared to the influence from individual characteristics, on the transportation activity, will be further discussed in the section on methodological considerations later in the paper.
Primarily, it is the local/regional transportation that can be influenced on through physical planning. Altogether, journeys shorter than 30 kilometers represent about half of the total amount of transportation in Norway, measured in kilometers (Rideng 1994). A somewhat older Danish study quotes that 70 percent of the passenger transportation in Denmark consist of journeys shorter than 40 kilometers (Larsen et al 1982b). Transportation over long distances, for instance holiday trips or freight between different parts of the country, is not likely to be much influenced through physical planning1.
1 The need for transportation over longer distances will, of course, depend on the population size and the composition of trades in different parts of the country, but these are relationships which – to the degree that they can be controlled by the authorities – is a subject for economic and regional policies, rather than physical planning. See also below about “the hypothesis of compensation” and “the hypothesis of opportunity”.
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Geographical distribution and structure of the building stock
Transportation system:Road systemProvision of public transportParking conditions
Transportation activity:Extent of transportationModal split
Reduced energy use for transportation may be achieved in three basic ways: By reducing the movement of people and goods. By transfer from energy demanding to more energy efficient means of transportation (for instance from
private cars to public transport) By making the different means of transportation more energy efficient (through improved vehicle
technology, a higher capacity utilization, better traffic flow, a “softer” way of driving etc.).
Land use and settlement planning may particularly contribute to reducing the energy use of transportation in the two first mentioned of these three ways, but also the possibilities of high capacity utilization in the public transport may be influenced on. Furthermore, changes in transportation infrastructure (road building or changes in the supply of public transport) may influence the energy efficiency of the different means of transportation as well as on the distribution of travelers on different conveyances. This research program primarily concentrates on how the development and location pattern influence the extent of transportation and the modal split between different conveyances. The importance of the provision of public transport and the design of the local road and path system will also be discussed.
Figure 2. Transportation activity as a function of urban planning factors, as well as individual characteristics of the travelers.
Distances, accessibility and needsTheoretically, it can easily be shown that it is possible for the inhabitants of densely populated towns to reach their daily tasks with less transportation that what is necessary in towns with scattered, low density development patterns. In Figure 3, the relation between density and average distance between functions is symbolized by dots within circles of different sizes. All three circles contain the same number of dots. We immediately see that the average distance between the dots is shorter in circle b) than in circle a), where the density of dots is lower. It can also easily be seen that the average distance between the dots is further reduced in circle c), where a larger part of the dots is concentrated towards the center.
The mutual location of different functions within the building stock
The actors’ resources, needs, wishes
Macro-level social factors: Income level Dominating
values Social
structures
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Figure 3 Relation between density and average distance between functions, symbolized by dots within circles of different sizes. From Næss (1997).
But as we know, people are not dots. Even if the average distance between different functions like homes, workplaces and service facilities is shorter in dense and concentrated towns, this does not necessarily mean that the transportation actually taking place, is less. With increased accessibility, new needs are generated. The increased accessibility provided by the density and the concentration may therefore be utilized to choose between a broader range of workplaces, shops and dwellings, rather than to reduce the amount of transportation.
The research carried out in this field up to now, however, indicates that even though some of the benefits gained by short distances is “consumed” this way, dense and concentrated towns do contribute to lower energy use for transportation, than towns with a low density, fragmented development pattern. The urban form factors that primarily seem to influence the extent of transportation, the modal split and the energy use for transportation, are density, location of dwellings, location of workplaces, geometrical urban form, regional development pattern and the structure of the transportation system. It is, however, uncertain how great importance each of these factors has in different geographical, social and cultural contexts. For example, it is reasonable to presume that the importance of living or working near the town center will not be the same in a small country town as in a large city. Nor is it sure that the population density will be equally important in large and small towns. Further, there are limitations regarding the extent to which experiences from investigations abroad can be transferred to Danish conditions.
In addition, there is still some uncertainty related to some of the results from the research in this field so far. Among other things, this applies to the transportation energy data in the studies where the energy use is calculated from information about fuel sales within specific geographical areas (see below). It is also desirable to have a closer look into how lifestyle factors affect people’s travel pattern in interplay with urban form and socioeconomic characteristics. Some debaters have hypothesized that the values and attitudes of the inhabitants of different parts of a town, for instance regarding car use, may be different, creating a possible source of error in the research carried out till now.
Another important question arising is whether a modest extent of local transportation will result in extended transportation in other places, as long as the total purchasing power does not change. Is it so – given a certain level of income – that “the sum of vices is constant”, and that households managing on a small everyday transportation consumption, create even heavier environmental strain through for instance week-end trips to a cottage or long-distance holiday trips by plane? In the professional debate, some parties have claimed that people living in high-density, inner-city areas, to a larger extent than their low-density counterparts, will seek out of town in the weekends, for instance to cottages etc., in order to compensate the lack of access to a private garden. In addition to this “hypothesis of compensation” others, including the Swedish mobility researcher Bertil Vilhelmson (1990), have launched a “hypothesis of opportunity” implying that the time and money people save due to shorter distances to daily destinations, probably will be utilized by increasing the length of their leisure journeys. Thus, it will be interesting to examine to which degree the effect of living
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close to the daily destinations is neutralized by longer, more energy demanding leisure journeys among those who have a short distance to the most regularly visited functions.
As mentioned earlier, our basic hypothesis is that travel is influenced by both spatial/structural conditions and by the actors’ individual resources, values and preferences. Consequently, the research design must take into consideration structural conditions as well as individual characteristics of the actors. It is, however, not sufficient to discover how traveling patterns vary between residential areas differing in location and physical structure as well as in their composition of lifestyle groups. If the results of the project are to be useful within physical planning, we have to clarify whether any differences in the traveling patterns of the examined residential areas are caused by their physical and locational characteristics, by the socioeconomic and lifestyle characteristics of their inhabitants, or by both. If the differences in transportation turn out to be mainly a result of differences in socioeconomic status, values and attitudes, the results of the project can only to a small degree be used to give recommendations about principles for an energy-conscious urban planning, as it is beyond the reach of physical planning to change people’s socioeconomic resources, values and attitudes. If, on the other hand, clear differences are found between the traveling patterns of residents living in different urban situations, also when controlling for variation in socioeconomic status and other lifestyle factors, the results may have important implications for a physical planning aiming to confine car traffic and energy use for transportation. Consequently, we must try to identify the separate influence of each potential explanatory factor.
Status of knowledge regarding the influence of some urban form variables on traveling distances, modal split and energy use.Below, we will give a short overview of what we have reason to believe today about how the traveling distances, the modal split and the energy use for transportation are influenced by a number of urban planning factors. In a later section, we will discuss some central concepts and theories that may be used when investigating how individual lifestyle factors influence travel.
DensityAs we have already seen from the example with dots within circles of different sizes, a high population density implies shorter average distances between dwellings, workplaces and service functions. The average mutual distance between the dwellings is also reduced when the overall density of the town increases, contributing to shorter traveling distances for visiting relatives and friends within the town. A high density also facilitates more frequent departures and shorter distances to public transport stops. In dense urban areas, there are also usually narrower streets and more shortage on parking places than in less dense areas. Consequently, high density contributes to shorter traveling distances as well as a more extensive use of public and non-motorized means of transport. Both contribute to reduction of the energy use for transportation.
By population density, we here refer to the density of inhabitants within the urban settlement, and not for instance within the administrative territory of the municipality, which may include both urban settlements and large unbuilt or sparsely populated areas.
Investigations in Nordic towns show a clear relationship between density and energy use per capita for transportation. (Næss 1993, 1995a, b; Næss, Sandberg og Røe 1996). This also holds true when controlling for other factors influencing on the energy use, for instance income, car ownership and commuting to and from exurban areas. Keeping constant such factors, the energy use per capita is about 25 percent higher in the least dense than in the densest of the examined cities. These results point in the same direction as Newman and Kenworthy’s (1989a, b) much referred examination of urban structure and energy use for transportation in 32 cities at a worldwide scale. The last mentioned examination however, did only to a small degree control for the influence from socioeconomic factors, although the cities varied strongly in their social, economic, cultural and political conditions2. A clear connection between density and transportation 2 Newman and Kenworthy show, however, that the variation in car use is far larger than what can be explained solely by differences
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pattern has also been found in a recent investigation of different towns within the Paris region (Fouchier 1998). Distinct from this, a comparison of transportation pattern in different “functional urban regions” in Great Britain shows little or no connection between density and transportation (Gorden 1997). It is, however, not clear how the density of these regions was measured in Gordon’s examination, for instance whether continuous, unbuilt areas were also included in the basis of calculation.
In the above mentioned examination of Nordic towns, the energy use was measured by registering the retail sale of gasoline and auto diesel within the boundaries of the urban area of each town, combined with information about the fuel and electricity consumption of the local public transport. As mentioned above, certain sources of error are associated with using data for fuel retail sale within the boundaries of the densely populated area as an indicator of the inhabitants’ consumption of fuel for local transportation3.Even though Næss, Sandberg and Røe took a number of precautions to control for these sources of error in their examination of Nordic towns, it is necessary to supplement and compare this study with investigations where the energy data are based on detailed studies of the inhabitants’ actual travel activity within the urban area. Such a comparison of different data sources for transportation energy may also test out the reliability of data on retail fuel sales within the urban area, as an indicator of the population’s energy use for local transport.
Location of residential areasTraditionally, many European cities have had a concentration of workplaces and service functions (particularly civil service, cultural institutions, restaurants, entertainment and specialized stores) in the central parts. The closer to the center the residential areas of such cities are located, the more workplaces and service functions may be found in a short distance from the dwellings. The result is shorter traveling distances among those who live in the central parts, than among those living in the outskirts of the city.Moreover, short distances make a larger part of the destinations accessible by foot. Investigations in a number of towns confirm that those living in the outer parts travel considerably longer by motorized means of transportation, compared to the residents of inner and central parts of the town (Mogridge 1985a, Newman and Kenworthy 1989a, Synnes 1990, Duun 1994, Schipper et al. 1994, Næss, Røe and Larsen 1995, Nousiainen 1998, Fouchier 1998). Few of these studies have, however, controlled for the influence from socioeconomic factors. Because, among others, income level, household structure and age of the inhabitants often vary between inner and outer parts of the city, there is a risk that differences in the transportation pattern actually caused by such factors are being explained with differences in the location. However, in one of the examinations mentioned, surveying the transportation pattern among households living in different areas within Greater Oslo, socioeconomic factors were controlled for (Næss, Røe and Larsen, ibid.) The correlation between the distance of the dwelling from the city center and the motorized travel distance per capita was present, also when controlling for income, household composition, car ownership and a number of other factors that may influence the transportation activity. The central and peripheral residential areas did not differ much regarding the modal split between car and public transport. Thus, the energy use for transportation varied approximately according to the same pattern as the travel distances.
in income levels. This is also apparent from an updating of the examination’s original 1980 data with data from 1990 (Kenworthy and Laube 1996). 3 First, non-locals (for instance people commuting into town or tourists passing through) buy a part of the fuel sold from the town’s gasoline stations. This contributes to an overestimation of the inhabitants’ energy use per capita. Secondly, parts of the fuel bought by the inhabitants themselves are used for transportation outside the urban area (for instance for commuting out of town, weekend trips and freight over long distances). This too contributes to an overestimation of the inhabitants’ energy use per capita for local transportation. Thirdly, people living in the town occasionally buy their fuel outside the urban area. Some of this fuel may be used within the boundaries of urban settlement, contributing to an underestimation of the inhabitants’ energy use for local transportation. In analyzes of the influence of the urban structure on energy use for transportation, these factors may be a serious source of error if their net effect (i.e. the difference between factors contributing to over- and underestimation) is large, and this net error correlates with the examined urban structure factors in a way that cannot be controlled for through multivariate analyses.
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It is uncertain, however, if the relationships found in Oslo and other larger cities are present to the same extent in smaller and medium sized Danish towns. Further, the situation may be another in towns where workplaces and service are more scattered4. It is also desirable to include the inhabitants’ values and attitudes as possible factors of explanation, in addition to urban form and socioeconomic characteristics. Among others, a hypothesis has been launched that the differences found in car ownership and transportation patterns between inhabitants in inner and outer parts of the town, are due to the fact that those who choose to live in the inner city have other lifestyle preferences than those living at the outskirts of the town area (Kitamura et al. 1997; Westford 1997). Further, as mentioned earlier, hypotheses have been put forward that those who have shorter distances to their daily destinations, and thus ordinarily manage with little transportation, will travel more than other people in weekends and holidays (cf. the earlier mentioned “hypothesis of compensation” and the “hypothesis of opportunity”). Næss, Røe and Larsen’s examination in Greater Oslo did not support these hypotheses. On the contrary, the material indicated that a high level of income as well as address far from the town center contributed to a certain increase in the number of driven kilometers outside Greater Oslo, but none of these effects were strong. The variables of density on residential and town level showed no effect whatsoever on the propensity of car driving outside the urban area of Oslo (Næss 1995a). However, in a study of travel patterns among households with children, living in three different areas in Gävleborg län in Sweden, Tillberg (1998) has found a certain support of the hypothesis that households with low everyday transportation needs make longer leisure journeys instead5.
Furthermore, it is desirable to have a closer look into the relative importance of the dwelling’s location within the urban area, compared to the density within the actual local neighborhood. In the examination in Greater Oslo, the distance of the dwelling from the downtown area as well as the density on a local level, were among the variables examined, but the density was here only calculated on basis of the number of inhabitants. For areas dominated by workplaces and service functions, however, the ratio between the number of inhabitants and the size of the area is less relevant as a measure of density. Therefore, in the planned investigations of the present program, it may be relevant to calculate the density within local neighborhoods as well as residential areas, including both inhabitants and workplaces in the basis of calculation (cf. Fouchier 1998).
In the investigations in Greater Oslo, the standard of the public transport and the availability of local service functions close to the dwelling were among the examined factors. These factors should also be included in the planned studies of Danish towns. In addition, it is desirable to include in the analyses the position of the workplaces’ of the working household members. This may enable us to explain a larger part of the variation in the inhabitants’ travel activity (see below). We would then also be able to throw light on this question: How large proportions of the inhabitants in different parts of the town live and work within the same local area?
Location of workplacesSeveral studies have shown that the number of people traveling to work by car, is considerable lower among employees of workplaces in the town center than among those working at the outskirts of the town (Hanssen 1993, Dasgupta 1994, Næss and Sandberg 1996, Hartoft-Nielsen 1997). Here in Denmark, Peter Hartoft-Nielsen’s research in the Copenhagen area shows that 10-25 % of the employees at offices in the inner town travel to work by car, while the proportion of car traveling is 70-85 % among employees at offices located far from commuter train stations in the outer town areas. The difference in car driving between inner and outer parts of town is, however, considerably less in the provincial towns than in the capital area. In Aalborg, for instance, the proportions traveling to work by car are 64% and 79% respectively, at offices in the town
4 Geometrically, the average distance between dots evenly spread along the periphery of a circle will be longer than the dots’ distance to the center (the radius of the circle). If the inhabitants consider the entire town as one common housing, working and service market, it might, from such a reasoning, be expected that persons living in the periphery of the town would, on average, have a longer distance to the workplace, even if most of the workplaces were located at the outskirts of the town. 5 Tillberg’s study was a pilot investigation, including only 21 households distributed on 3 residential areas. The areas being compared were situated in the region center of Gävle, in a smaller urban area and in a rural area 20 kilometers from the region center. In other words, the comparison did not focus on the influence of the dwelling’s location within each town.
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center and in a suburban area. (Hartoft-Nielsen 1997).
The access by public transport is usually best in the central parts of the town. Besides, congestion and limited parking possibilities in the center make many people leave their cars at home for those reasons. Nor do the employees of workplaces at the outskirts have a shorter average traveling distance to work, as many planners have believed. The investigations made in Nordic towns rather show a tendency for employees at the outskirts to have somewhat longer traveling distances to work than people working in the inner parts of the city. Together with the strong increase in the proportion of car drivers the farther from downtown the workplace is located, this gives a very clear correlation between workplace location and the employees’ energy use for journeys to work.
Few studies of relationships between workplace location and transportation have also included socioeconomic factors in their analyses. This was, however, done in the above-mentioned investigation focusing on the employees’ journeys to six workplaces in Greater Oslo. Here, the relationship between the distance of the workplaces from downtown and the energy use was still strong when controlling for a number of other factors that may influence the commuting pattern, among others car ownership, sex and income (Næss and Sandberg 1996).
Exceptions from the conclusion that a central workplace location gives the least use of energy, are functions clearly directed towards the local neighborhood – for example grocery stores, post offices, elementary schools, secondary schools and kindergartens. For such functions, short distances for pupils and visitors are more important than the employees’ journeys to work. Thus, these sorts of functions will create least traffic if located close to residential areas, for instance in local centers.
Geometrical shapeIn the history of urban planning, great attention has been devoted to the question of the towns’ geometrical shape (circular, linear, star-shaped etc.). This question has, however, only practical significance if facing possibilities to change the existing shape of the town. In practice this mean a situation where a considerable expansion on the urban area is to be made. In such cases it may be relevant to point out future directions of expansion, for example from considerations of a rational operation of public transport services in the future urban area. Unless a strong increase in population takes place simultaneously, such an area expansion will, however, reduce the town’s population density. And as we have seen above, reduced population density is not favorable when the aim is to reduce energy use for transportation.
Many professionals have claimed that linear development patterns are favorable in order to provide an efficient system of public transport. Linear development also gives shorter average distances to continuous, undeveloped areas, and may therefore perhaps reduce the need of leisure trips by car. The investigation of 22 Nordic towns, made by Norwegian Institute for Urban and Regional Research (NIBR), supports the hypothesis that an urban structure with a great part of the buildings located in narrow ribbons along the public transport routes, form the basis of a good provision of public transport. At the same time, the traveling distances in such towns are longer than in circular towns, and the dependence on motorized transportation is higher. The study indicates that this counterbalances the advantages of an increased standard of public transport in linear towns, and that the geometrical shape of the towns does not influence much on the inhabitants’ average energy use for transportation.
Regional development patternAs mentioned above, it seems favorable to energy conservation to locate both dwellings and workplaces close to downtown. An important question is if the advantages from centralization are also present when we turn from looking at single towns to larger regions (for instance a county). Some professionals answer yes to this, from a line of argument that there will be a lot of crisscrossing transport between the different local communities in regions with a decentralized population pattern. Norwegian travel surveys (among others Simonsen 1996) and Finish registrations of commuting distances (Martamo 1995), however, do not indicate that people in rural districts use more energy for transportation than townspeople. An investigation of fuel
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sales in different Swedish regions, too, weakens the hypothesis that centralization on a regional level gives a lower energy use (Næss 1993, 1995). Instead, this study indicates that a pattern with several dense, self-sufficient urban settlements distributed all over the region contributes to lower energy use than if most of the population is concentrated in one large city. Further, the material suggests that a high degree of urbanization contributes to increase the energy use.
These results are well in accordance with the conclusions from a study made in the beginning of the 1980s here in Denmark (Larsen et al 1982a, b), and with an English model study (Rickaby 1987). Tillberg’s (1998) pilot study in Gävleborg’s län in Sweden may indicate that inhabitants in smaller urban and rural areas make shorter leisure journeys than urbanites, but the number of examined households was so low in this case, that the results have to be interpreted with great caution. Reijo Martamo’s (1995) survey of commuting distances within different parts of Finland shows that people in medium-sized and small urban areas often have a short distance to their workplaces. Martamo found the longest average commuting distances in the marginal areas of the largest cities, not in outskirts.
It may seem a paradox that centralization of dwellings and workplaces turns out to be favorable as long as we stay within the city, while a decentralized structure seem to be the most favorable on a regional level. Within an urban area, however, the distances are often so moderate that people consider the entire city as one common housing, working and service market. On a regional level (for instance within a county) the distances between the different local communities are more often so long that they form a deterrent against extensive transportation between different parts of the region. In that case, different urban areas and local communities within a region may, to a larger degree than a city’s suburbs, be able to function as more or less autonomous units. The energy use for transportation will, according to this, increase when the distance from the home to the city center increases up to a certain number of kilometers. Moving further away from the center, the energy use seems to level out and gradually decrease. How far away from the city center such a “turning point” is located, is difficult to tell. It still seems reasonable to suppose that the turning point will be located further from the urban center in large cities than in smaller towns and villages. The studies of both Martamo (1995) and Larsen et al (1982a, b)6 support such a hypothesis.
The conclusions of the above-mentioned studies are, however, at odds with analyses of data from the nationwide Traffic Surveys (TU) of Statistics Denmark. Here, the longest driving distances were found among the inhabitants of rural areas and small villages (Christensen 1996). Corresponding results were found in an English comparison of town size and energy use (Banister 1992). This study showed that people in scattered areas, and urban areas with a population of less than 3000, had a higher average energy use for transportation compared to the inhabitants of any other category of size among British towns and urban areas. The results neither fit well with findings from Oregon in the USA, where those living in scattered areas around the city of Portland had a very high energy use compared to the inhabitants in the city itself (Davis, Nelson and Dueker 1994). These discrepancies may perhaps be due to variations in lifestyle between different countries7, but they may also be a hint about weaknesses in the energy data used in the study of the Swedish regions. Here, the energy figures were based on statistics on fuel sales on a municipal level, and even though a number of actions were taken to reduce possible sources of error, some uncertainty is attached to the quality of the energy data. Moreover, comparison of fuel data between different regions does not enable us to explain the mechanisms through which the settlement pattern influences on the energy use for transportation, for example regarding traveling purposes and modal split. To get to the root of what influence the development pattern on a regional level has on travel and energy use, there is a need for more thorough investigations of the travel activity among inhabitants in different kinds of local communities.
Public transport, road system and parking possibilities
6 Admittedly, in the study by Larsen et al., the finding of a “turning point” was based on a very weak data material, in particular in the parts of the surroundings of the cities where such a turning point might theoretically be expected to be situated.7 The strong outdoor life traditions in the Nordic countries may, for instance, imply that the distance to recreational areas are of greater importance for the extent of transportation in these countries, than in countries where walking tours and skiing trips in natural environments are less usual.
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Except for the rush hours, public transport in cities has difficulties in competing with the travel time of cars. In the peak periods, cars lose time on congestion (distinct from transit running on a separate lane), while the public transport’s more frequent departures make the average waiting periods shorter. Thus, it is primarily for journeys to and from work that public transport is able to compete with cars. For such journeys, measures reducing travel time by car can make some public transport passengers change their means of transport. Conversely, an improvement of the competitiveness of the public transport regarding travel time can make some car travelers leave their cars at home. Theoretical considerations by, among others, Downs (1962), Thomson (1977) and Mogridge (1985b) indicate that increased road capacity in urban areas may turn out to be an inefficient or even counter-productive measure to reduce door-to-door travel times.
Several professionals have claimed, however, that a field of competition between car and public transport hardly exists (cf., among others, Bly, Johnston and Webster (1987), Klæboe (1994) and Solheim (1994). In that case, increased road capacity in urban areas will lead to better-flowing traffic and less pollution from congestion, but it would not influence, to a degree worth mentioning, the distribution between car travelers and public transport passengers.
Recent investigations in the Oslo region, however, clearly show that a field of competition between car and public transport does exist for journeys to work in the rush hours (Engebretsen 1996, Næss and Sandberg 1998, Næss 1998). The number of travelers sensitive to changes in travel time of the respective modes seems to be considerable. A number of factors influence the travelers’ choice of conveyance, but both the travel time ratio between car and public transport and the parking conditions at the workplace turn out to be important.
It would be desirable to investigate the degree to which the conclusions from the Oslo region are valid also for smaller towns, for instance Danish provincial towns. Furthermore, it is desirable to compare the results with a large city like the Copenhagen area. Such studies should include also the field of competition between non-motorized transportation and cars as well as public transport. Within the program “Transportation and Urban Planning”, however, priority will not be given to this theme. The provision of public transport and the parking conditions near the home will be among the factors to be examined, but measurements of travel time by different modes of transportation between given points of departure and arrival, will not be made. In future Danish transportation research it should, however, be a task of high priority to examine how modal choice, travel time and congestion in towns are influenced by the relative travel times by car, public transport and non-motorized transportation.
It is reasonable to believe that not only the road capacity, but also the road and path structure influence the extent of transportation and the modal split. This issue has not been discussed much in the literature. There is, however, reason to believe that there are differences between traditional urban areas (with a road system designed as a grid or radial net, without a network of paths in separate lanes), urban areas designed according to the SCAFT principles8, and areas with mixed traffic calmed by physical measures. There is also reason to believe that there will be variation between different urban areas developed according to the SCAFT principles, regardless of whether the access by car is from the outside or inside (external or internal car access). A continuous network of footpaths and bikeways connecting different parts of the city coul also be expected to increase the proportion of non-motorized transport. According to Larsen (1998, personal communication), the establishment of a continuous network of footpaths and bikeways in Odense has led to an increase in bicycle traffic by 40 per cent, and in the downtown area as much as 60 to 65 per cent. The road and path structure – primarily on a local level, but also for the town as a whole – will be included in the urban structural factors examined within the program “Transportation and Urban Planning”.
The resources, values and preferences of the travelers
8 A set of recommendations regarding the design of road systems in new development areas worked out by the research group SCAFT at Chalmers Tekniska Högskola (the Chalmers Institute of Technology, Sweden) at the end of the 1960s. The main ideas of the SCAFT principles were traffic differentiation and traffic separation.
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Previous research has shown that the extent of transportation as well as choice of travel mode is to a large degree influenced by the travelers’ socioeconomic situation. High income enables people to pay the price of high mobility, including purchase of vehicles, expenses for maintenance and taxes, purchase of fuel, as well as public transport fares. Therefore, it is no surprise that a number of studies have found that a high income contributes to increasing car use and energy use for transportation (among others Schipper, Deakin and Spearling 1994; Næss, Sandberg and Røe 1996). In urban transportation, however, income does not seem to have a particularly strong influence neither on the extent of transportation nor on the modal split. At the same time, the above mentioned study of journeys to work among employees at 6 workplaces in Oslo indicates that high income may contribute to reducing the daily traveling distances, by enabling people to get a house of a preferred standard closer to their workplace9 (Næss and Sandberg 1996). Such a relationship has also been found in some American urban areas (Cervero 1989).
The composition of the household has also turned out to influence the amount of traveling. Families with children use their cars more than the childless do. This may, among other things, be explained by the fact that the car is often used for bringing children to and from kindergarten, school and leisure activities. These trips also contribute to increase the total traveling distance of the household. Keeping other factors constant, the amount of local transportation is higher among families with children than among the childless ones when calculating the traveling distance per adult household member. If, however, we calculate the extent of transportation per member of the total household, the weekly traveling distance is lower among families with children. This is because children make fewer trips on their own outside the closest neighborhood. (Næss, Røe and Larsen 1995.) The sex of the travelers is also important: Public and non-motorized means of transportation account for a larger proportion of the transportation among women than among men (Jenseth 1987; Hjorthol 1990; Næss, Røe and Larsen, ibid.). This is, for one thing, related to the fact that among couples with one car in the household, it is still most frequently the man who employs the car for his journey to work.
Few Scandinavian studies have investigated the influence of people’s education level on their local transportation. Those few investigations including this factor in their analyses do not indicate that the education level in itself has any influence worth mentioning on the modal split nor the extent of local transportation (see, among others, Næss and Sandberg 1998). By influencing the income level, and possibly also the chance of a company car arrangement, the education level may still have an indirect effect, but beyond this, the length of the education does not seem to have any particular influence on transportation. It may be so, however, that the category of education influences on the traveling pattern, for instance with differences between persons educated within caring work and persons with a technical or economical education. Hartoft-Nielsen (1997) has found that the modal split of the employees’ journeys to work varies considerably between different office businesses, all of which with a high education level among their employees, but dominated by different disciplinary fields. The comparison was made between businesses in the Copenhagen area, situated in quite similar locations within the urban structure.
A number of studies have shown that the transportation pattern is considerably influenced by the car ownership of the households, in particular whether they have got a car at all, and, in case they do, how many cars they have at their disposal. The higher number of cars per adult household member, the longer is the weekly travel distance, and the greater is the part made by car. Car ownership in itself may, however, be influenced by socioeconomic factors (among others income and household composition) as well as urban form factors. An example of the latter is that the number of cars per household member is lower among inhabitants in dense residential areas than in areas of detached housing in Oslo, even when several socioeconomic factors are controlled for (Næss, Røe and Larsen 1995). This is probably due to a combination of the facts that the public transport is usually better and the parking conditions more inconvenient in dense residential areas.
9 Four of the six examined workplaces were located less than 3,5 kilometers from the town center. Households with lower income have to settle in areas further away from downtown to be able to afford the same sort of housing (for instance a detached house) as those with a high income can afford in parts of the town relatively close to the center.
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In addition to the above mentioned socioeconomic factors, a number of studies show that people’s trip frequency, choice of destination and travel mode are influenced by several factors beyond those mentioned above. People may, for instance, have various attitudes towards different travel modes. These attitudes may, again, have connection with different importance being attached to factors like travel speed, comfort, flexibility and the symbolic image attached to various means of transportation. The individual characteristics influencing how people attach different importance to such aspects of traveling, are often referred to as “lifestyle factors” (se closer discussion below). Such factors may influence people’s choice of a number of different destinations, especially regarding leisure journeys, but also for example regarding shopping trips. However, very few, if any, studies have been made to investigate how “lifestyle factors”, in interaction with pattern of development, location pattern and the socioeconomic resources of the travelers, influence transportation activity.
In addition to involving lifestyle as a conducive factor that may help explaining the households’ choices of transportation and total travel distance, we also wish to investigate different lifestyle groups’ needs of transportation in order to reach various facilities and functions of the city (including workplaces, service and leisure facilities, natural areas, etc.). The parts of the city, where a certain lifestyle group frequently moves around and feels “at home”, may be called their domain (Møllgård 1994, Marling 1998). A part of the “Transportation and Urban Planning” program will focus on the degree to which different lifestyle groups vary regarding the size of the geographical areas included in their domains. Investigations will also be made to identify any residential areas, relatively “homogeneous” regarding lifestyle and lifestyle domain, but mutually different (for instance residential areas where the population primarily have their neighborhood as their domain, and areas where the inhabitants make use of a series of facilities spread all over the city). In this connection, it is desirable to investigate the degree to which the local facilities match the needs of the different lifestyle groups, and how the situation evolves in that respect. These analyses will then form a basis for a discussion of whether the various functions and facilities of the city are adequately located from an urban planning and transportation point of view.
Within the program “Transportation and Urban Planning”, studies of whether residential areas characterized by homogeneous lifestyles can be identified, and how the domains of different lifestyle groups are distributed geographically, will make up a relatively modest part, limited to what has a clear relevance to urban and transportation planning. This issue will be discussed to a greater extent within the research program “Urban ecological welfare development”, with which the researchers of “Transportation and Urban Planning” have established a close cooperation. The lifestyle orientation of the inhabitants will, however, be included in our analyses as an important explanatory factor influencing the inhabitants’ traveling distances, modal split and energy use for transportation, along with their socioeconomic status and urban form characteristics of their dwellings. This will be further described below.
The lifestyle conceptThe term of lifestyle is being used to describe various social and cultural aspects regarding the ways people lead their lives (Berge and Nondal 1994). During the last years, the concept of lifestyle has been increasingly used in the current debate in society, but without any unambiguous definition. Within the environmental debate, for instance, it is often claimed that a change of our lifestyle (the western one) is necessary to solve the environmental problems. The statement “to change one’s lifestyle” may, however, be interpreted in many different ways. Some people associate it with a basic change in values and consumption patterns, based on a criticism of the “consumer society”, while others refer to an increased awareness of environmental problems and a gradual change towards more environmentally adapted consumption and practice, but without any element of “dissidence”. (Hallin 1996). The lifestyle concept is also used by the advertising trade to market clothes, cars, food, etc. In this case, the lifestyle concept is connected to products and things that can be bought and sold due to their signal effect (Marling 1998).
In classical sociological theory, the lifestyle concept is connected to consumption in a wide sense. According to the American Torstein Veblen (1899/1976, quoted from Berge and Nondal 1994) the power élite in industrial society has less leisure time than the ruling class of feudalism had. Distinct from the aristocracy,
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who emphasized their status through freedom from work, the power élite of the industrial society uses conspicuous consumption as a sign of wealth and power. Many in the lower classes, however, try to influence their visible status by copying the consumption pattern of the power élite. As a result, the upper class develops new consumption patterns to maintain the signs of their own position. The German sociologist Max Weber (1922/1971, quoted from Berge and Nondal, ibid.) somewhat later used the lifestyle concept about the way individuals systematize their conduct of life in a certain manner. In his social theory, he draws a distinction between classes, categorized according to their relationship to the production and the use of material benefits, and status groups, classified according to their consumption. Belonging to a certain status group is, according to Weber, expressed by choice of clothes, music, art, etc. Another German classic scholar within sociology, Georg Simmel (1902/1998), attached importance to the style of action as a way of making one’s own personality and individuality visible, as a defense against the anonymity and the blasé state of mind characterized by city life.
The theories on lifestyle have been developed further by the Frenchman Pierre Bourdieu (1984, quoted from Berge and Nondal ibid.), who regards lifestyle as a set of dispositions for actions, based on a taste code determined by the symbolic and cultural capital of each individual. These are, to a large extent, a result of hereditary dispositions (class belonging), deciding the footing of the individual and making probable certain action patterns or set of dispositions (habitus). The importance of people’s position in the professional world is also emphasized by Thomas Højrup (1983), who separates between the form of life (livsform) of the wage worker, the self-employed and the career bound form of life. The British sociologist Anthony Giddens (1991) defines lifestyle as a more or less integrated set of practices maintained by an individual, not only because such practices contribute to fulfilling practical needs, but also because in a material form and in a special way, they tell something about people’s self-identity. The Swede Fredrik Miegel (1990, quoted from Berge and Nondal, ibid.) separates between three main groups of factors influencing the phenomena usually included in the concept of lifestyle: The way of life (structurally determined), the form of life (determined by position) and lifestyle (individually determined). Although Miegel reserves the lifestyle concept for what is individually determined, he still thinks that the lifestyle of an individual is influenced by structural and positional conditions as well. According to Miegel, lifestyle is influenced by factors on society level, group level, primary group level (i.e. the household) as well as individual level.
Choices of travel mode, type of residence as well as travel destinations (particularly in connection with leisure activities) are examples of situations where individuals may seek to indicate their belonging to a certain status group, or to signal their own individuality (the latter maybe primarily through the combination of destination choices). Theoretically, it is therefore clearly relevant to include lifestyle factors as supplementary factors of explanation in studies of relationships between urban structure and transportation. As time has gone by, a lot of empirical evidence exists, showing a connection between lifestyle factors and transportation (Berge and Nondal 1994, Berge 1996, Hjorthol and Berge 1997, Jensen 1997a, b, Magelund 1997, Aune 1998). But as mentioned above, hardly any travel surveys have been made, including as factors of explanation physical/spatial conditions, the socioeconomic resources of the travelers as well as their belonging to different lifestyle groups.
In the analyses within the program “Transportation and Urban Planning”, concepts from both Bourdieu and Miegel could preferentially be employed. The part of social reality focused upon is “the transportation culture” in Denmark and the part of people’s traveling taking place within a local area (the town/region). To a certain degree, however, longer journeys made during holidays and leisure time will also be taken into consideration. In connection with the analyses of relationship between lifestyle and transportation, the influence of the lifestyle factors on choice of address and housing category, as well as destinations of work-related, leisure and shopping trips, will be included. Even though “the Danish transportation culture” is relatively homogeneous10, regional differences probably exist, maybe primarily between the largest cities and rural areas. The results from some of the previously mentioned studies of relationship between regional
10 Compared to the differences in transportation culture one may find between different countries, for instance between Denmark and the USA, or between West European and African countries.
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settlement pattern and transportation (Larsen et al. 1982b, Næss 1993) give clues to such a hypothesis. What Miegel calls factors of influence on society level, may, in other words, vary somewhat between different parts of the country, still within the context of “the Danish transportation culture” (which is, in its turn, influenced by the general level of prosperity, public transportation policy, ideals passed on through media, among others). The structurally11 conditioned way of life that characterizes society within this area, will thus have major features of resemblance independent of where in the country we are, but it may still show a lot of regional variation. In our project, this means that the way of life regarding transportation may possibly show some variation between town and countryside, even if the way of life on both occasions is influenced by a number of common factors, prevailing through all Denmark and to a high degree also in Scandinavia and large parts of the western world. Consequently, we assume that people’s lifestyle to a certain degree may vary depending on their living in a town or in the countryside, and independent of their individual position in society, expressed by, among others, class affiliation.
Regarding form of life, according to Miegel this is primarily influenced by the individual’s position in society, in addition to the general influence from the dominating way of life in the society. By factors of influence on group level he alludes to the mutual influence between persons belonging to the same form of life, i.e., an influence contributing to sub-cultural conformity. Like Bourdieu, we consider social class affiliation to be an important part of the positional factors of influence. As indicators of social class affiliation, we propose profession category, educational level and type, income level (personal income as well as total household income per person), and moreover the parents’ professional activity (the latter to include an indicator of the individual’s economic and cultural adolescence conditions). In addition to class affiliation, sex, age, ethnicity and place of adolescence will be included among the factors contributing to determine an individual’s position in society, and which may influence the lifestyle.
Miegel also operates with factors of influence on primary group level (that is, within the household). In our view, these factors may influence both the form of life and the lifestyles manifested by the individuals. The main household-related factors contributing to determine an individual’s position in society, and hence his form of life, are probably marital status and whether there are children in the household. In addition, the household members may influence each other’s values, attitudes and actions (see below).
Regarding the individually determined lifestyles, these may, according to Miegel, be analyzed on value level, attitude level and action level, where the attitudes have their origin in values and are being manifested through action. As action (in the form of transportation) is the dependent variable we wish to find reasons for, it will be problematic to include the same kind of action in the lifestyle concept too (which in the analyses will be included among the potential causal factors). One possibility could be to include only types of actions other than transportation, and examine how transportation might possibly correlate with these other categories of lifestyle-influenced actions. The actions that may be included in such a mapping are the kinds of actions that might act as “lifestyle tags”, i.e. actions symbolizing or indicating affiliation to a certain lifestyle group. Examples of such actions could be purchase of books, video cassettes and CD records, newspaper subscription, outdoor activities, visits to theatre, cinema and restaurant, participation in voluntary organizations, etc12.
Miegel distinguishes between different types of values: material, esthetical, ethical and metaphysical, with corresponding sets of categories of attitudes: interests, taste, principles and convictions. We consider it too complicated to operationalize such a classification in our project. It is also very difficult (impossible?) to measure values directly by means of a quantitative surveys13. In the qualitative parts of the investigations, a
11 Structural here refers to cultural influences from belonging to the society on a “macro level”. In this connection, we do not include the structural conditions for action given by, for instance, the location of the home and the shape of the residential area. It is exactly the significance of these, more “micro-level” structural conditions to the traveling we wish to compare with the significance of the inhabitants’ lifestyle and socioeconomic characteristics. 12 In survey investigations, it will probably be necessary to choose a small number of action types as indicators, while in qualitative interviews, a wider specter of actions may be included.13 Values are latent, non-observable characteristics of individuals. Studies of people’s values will, in practice, often be made by
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somewhat better knowledge of the interviewees’ values may be obtained, but here too there will be a need of some indicators to help us categorize the values behind the more or less visible attitudes and actions. We therefore have chosen, like the Norwegian transportation researchers Berge and Nondal (1994), to operate with a common set of value and attitude indicators, where admittedly some may be considered more “basic” than other ones. Among the more “basic” value and attitude indicators, I consider political orientation along a right-left axis, attitude towards a set of general environmental policy issues (cf. Næss and Engesæter 1992) and consumer orientation in general14. The more “secondary” value and attitude indicators include arguments for housing preference and travel mode, the view of the symbolic meaning of the home and the conveyance, the attitude towards transportation policy measures and the view of the extent to which passenger transport in Denmark causes environmental problems.
Based upon what is written in the sections above, Figure 4 shows a model of how the lifestyle concept may be operationalized in our studies, and how the lifestyle variables are included along with urban form variables that may contribute to explain differences in the transportation of households. As the model shows, the lifestyle concept also includes several socioeconomic variables that have traditionally been included in travel surveys. What comes in addition, is information on the interviewees’ social and cultural background, a number of value and attitude variables, and some categories of action selected as indicators of the respondents’ lifestyle.
When preparing questionnaires, we will try to make use of experience from previous studies aiming to survey lifestyle factors, among others Berge and Nondal (1994, Hjorthol and Berge (1997), Jensen (1997b) and Kitamura et al. (1997). In the quantitative analyses of how lifestyle factors, together with other conditions, influence people’s actions, it may be current to combine variables into groups of variables, expressing the same dimension. We also have to decide how to handle the fact that the lifestyles are individually determined, while traveling distances by car will be measured for the household as one unit. The solution may perhaps be to use index values for the lifestyle characteristics on household level, calculated by adding up the values of the individual household members on the relevant variables15. In the qualitative case studies of some households’ transportation, it will be possible to take into account a broader specter of lifestyle indicators than those being possible to survey in a questionnaire. But here too, there will be a need of criteria regarding how to divide the examined households into different lifestyle categories.
In France, Pierre Bourdieu has used a special statistical method of analysis, correspondence analysis, to study patterns of cultural taste within different social groups. By means of a similar technique, Ottar Hellevik (1996) has found two main dimensions along which the attitudes of Norwegians can be characterized: materialist – idealist and traditional – modern. Here in Denmark, in the so called Minerva model and by use of similar methods, Henrik Dahl (1997) has produced a system of coordinates, where people’s attitudes and values are being described along the following dimensions: Individuality/renewal vs. conformity/tradition, and materialism/utilitarianism vs. considerateness/spirit of community. Correspondence analysis has also been used by Berge and Nondal (1994) in analyses of more directly transportation-related problems. The main axes used in these analyses are traditional – modern and community oriented – individually oriented, of which the latter also, to a large extent, is considered an axis of environmental attitude. It may be relevant to use one or more of the above-mentioned classifications to distinguish lifestyle variables in the analyses in “Transportation and Urban Planning”, too. Further, it may be
studying their attitudes towards specific phenomena, from a reasoning that these attitudes are influenced by the theoretic variable(s) (values) that we wish to measure (Hellevik 1991, p. 165). 14 By consumer orientation in general, we in particular refer to people’s estimation of getting more material goods enjoying some luxury consumption saving money.It may be relevant to use some of the questions from Norsk Monitor (Norwegian Monitor) (Hellevik 1996) and/or from the project “The dwelling as a basis for sustainable consumption”, carried out in the period 1997-2000 at Western Norway Research Center and Norwegian Institute for Urban and Regional Research in cooperation with Aalborg University. 15 This may possibly be supplemented with variables stating the degree of concurrence between the lifestyle characteristics of the individual household members.
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Theoretical concept:WAY OF LIFE
Operationalized by:Type of residential location: urban (large or medium-size town) vs. rural (village or countryside)
Theoretical concept:FORM OF LIFE
Operationalized by:Class affiliationEducationIncomeSexAgeEthnicityArea of adolescenceComposition of the household
Theoretical concept:LIFESTYLE
Operationalized by:Value and attitude variables:Political orientationEnvironmental attitudesGeneral consumption orientationAttitudes concerning choice of residential area and type of dwellingOpinion on travel as a way of expressing one’s identityAttitude towards transportation policyView of environmental importance of transportationAction variables:Leisure activitiesPurchase of certain types of consumer goodsMembership in voluntary organizations
THE URBAN FORM CONTEXT OF THE DWELLINGDistance to centers on different levelsSituated in urban or rural areaDistance to local service functionsDistance to recreation areasDensity in the local community and the residential areaStandard of public transport facilitiesType of dwellingParking conditions and road and path network
TRANSPORTATIONTraveling distanceModal splitEnergy use for transportation
relevant to investigate how people’s values and attitudes as well as transportation activities are connected with their socioeconomic resources, characterized along, for instance, the dimensions economic and educational assets.
Figure 4 Model where the households’ transportation is shown as a result of the household members’ personal resources, lifestyle and of the urban form context of the dwelling.
Determinedby macro-social- conditions
Determinedby position(inherited andacquired)
Individuallydetermined
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Research issues given priority within the program “Transportation and Urban Planning”As a result of the review of status of knowledge presented above, within the research program “Transportation and Urban Planning” we will give priority to studies directing their main focus towards the extent to which traveling is influenced by the following urban form characteristics: The regional pattern of development, and The urban form context of residential areas within the city
The projects within the program should, however – to an adequate degree – also investigate other relevant urban variables’ importance to the transportation pattern, among others the population density, the location of functions and the transportation system for each separate town or village.
Within the studies of regional patterns of development, we intend to examine, among others, variations in the traveling distances, modal split and energy use for travel among households living in: urban and rural areas towns of different population sizes towns varying in their population density towns situated in different distances from the region center towns with different supply of specialized service functions areas with different supply of local service functions urban settlements with a various degree of balance between workplaces and workforce participants areas located differently in relation to main roads and public transport arteries
The investigations of the influence on travel from the urban form context of residential areas within each separate city, will, among others, look at the following factors potentially influencing the households’ traveling distance, modal split and energy use for transportation: the distance of the dwelling from the town center the density in the local community and the residential area the distance from the dwelling to various local service functions the provision of public transport services near the dwelling the predominant category of buildings in the residential area the parking conditions near the dwelling the road and path system in the residential area and the local community the location of the dwelling in relation to the town’s main road system the location of the workplace of the workforce participants of the household (notably the distance of the
workplaces from downtown)
The main purpose of the program is to produce empirically based knowledge about the above mentioned research problems. In addition, consequences in terms of CO2 and NOx emissions from differences in transportation patterns influenced by urban structure will be calculated. The program also intends to discuss how a transport-reducing physical planning may affect other environmental concerns, and the importance of such planning principles within a strategy for a sustainable urban development. Furthermore, the empirical results will be discussed in a wider social context, with focus on, among others, possibilities and obstacles to the implementation of transportation-reducing measures in physical planning. In this connection, it is also relevant to discuss the degree to which the results are sensitive to social and technological changes, for instance the increased use of information technology, demographic changes, technological development of vehicles and changes in the general mobility in society.
In our program, socioeconomic and other lifestyle factors will primarily be included as control variables in order to improve our understanding of the actual (non-spurious) impacts of urban form characteristics on the traveling activity of the respondents and interviewees16. Besides we will, as mentioned, investigate potential 16 This do not imply an opinion of urban development factors being more “important”, in the sense that people’s transportation
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implications to urban development from the spatial variation in the domains of different lifestyle groups. The ambitions of this program concerning knowledge and theory development are primarily within the subject of urban planning, not in socioeconomic research or lifestyle research per se. Any observations and discoveries of general sociological interest, but without direct relevance to urban planning, will of course be reported and interpreted in the light of relevant theories within the field of competence of the project participants. We do, however, not aim towards making separate studies of theory literature (beyond what we are aquatinted with on beforehand) in order to illuminate empirical observations peripheral to the research area on which the program focuses. Neither do we aim towards a comprehensive testing or further development of theories within substantive areas far away from the field of urban planning.
Having said this, we would like to emphasize the point that the main research issue of the program, namely to what degree people’s traveling activity is influenced by the physical/spatial environment of the residential area, the town and the region, concerns a classical main theme within sociology and the social sciences: the importance to human actions of structural conditions on one side and individual characteristics on the other (see below). Here, we aim to find interesting empirical examples as well as to contribute to theory development.
Methodological considerationsIt is usual to distinguish between two types of conditions for human action: actor-specific conditions and structural conditions. In the scientific debate on relationships between physical structures and human action, there has been considerable disagreement between different disciplinary traditions on the extent of importance of each of these types of conditions. Within sociology, this disagreement is evident in the tension between voluntarism and determinism. Some have assumed that the actions of human beings are to a large extent determined by physical and other external conditions. Others have emphasized the fact that people’s various qualifications and preferences, and our ability to choose our own actions, open up for a multitude of different adaptations to the same structural conditions17.
The part of urban planning research investigating consequences from land use and developmental patterns to people’s use of the physical environment (under which the projects in the program “Transportation and Urban Planning” belong), is based on the assumption that human actions are influenced by actor-specific as
activity is influenced to a higher degree by urban form factors than by their socioeconomic and lifestyle characteristics. It may very well be that the latter factors influence more on the variation in traveling activity of the households, than what does the urban structural situation of the dwellings. In the program “Transportation and Urban Planning”, however, the knowledge primarily sought for is the influence of urban structure on transportation. 17 In particular within parts of sociology and human geography, it was for a long time a dominating view that the physical surroundings have no significant influence on human actions. This attitude may possibly be traced back to the tradition of the sociological classic scholar Emile Durkheim. According to this tradition, social facts can only be explained by linking them to other social facts (as opposed to explanations referring to, e.g., psychological, biological or physical conditions) (Tonboe, 1993, p. 4; Lidskog, 1998, p. 22). The position in part also has its roots in the legacy from Max Weber. Admittedly, the scholars of this tradition emphasize that the actions of all humans are influenced by the way they perceive their surroundings. However, these perceptions are believed to be mainly formed through influence from the surrounding actors, and not from the physical characteristics of the situation (Lidskog, ibid.).The American sociologists Dunlap and Catton (1983, p. 118) summarize the impact of the above-mentioned disciplinary traditions on sociology’s treatment of the physical environment as follows:
“The Durkhemian legacy suggested that the physical environment should be ignored, while the Weberian legacy suggested that it could be ignored, for it was deemed unimportant in social life.”
A similar denial of the importance of the physical/spatial surroundings to human behavior can be found within important traditions of human geography, among others, in the writings of David Harvey and Manuel Castells. According to Castells (1997, quoted from Tonboe, ibid., pp. 4 and 531), space has no meaning independent of its social background. Everything space might possibly mean lies in the social, economical and political powers by which it has been produced. Attributing any importance to space beyond this, is, in Castells’ view, illegitimate space fetishism. In line with this, he refuses to separate the spatial from the social, even for analytical purposes.We of course agree with Castells that the built environment is a result of human actions. But as soon as these buildings and infrastructure systems have been constructed, they become part of the conditions for human behavior. The built environment creates accessibility and barriers, proximity and distance, and it facilitates some activities at the expense of others. Buildings and infrastructure also have a considerable permanence. Buildings often have a life span of 50 – 100 years or more, and today’s roads and other technical infrastructure in older districts of a city often follow the same lines as they have done for several hundred years.
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well as structural conditions (Næss and Saglie 1998). The main research issues in the program can be placed within the part of sociological research often described as environmental sociology, focusing on relationships between social and physical phenomena (Dunlap and Catton 1983). In the research program “Transportation and Urban planning”, knowledge about the actors (the characteristics of the inhabitants) is included as alternative or supplementary explanations, but is not the prime subject of investigation. The main interest is directed towards the influence of the physical/structural conditions (land use, buildings and infrastructure) on people’s behavior. The physical conditions constitute a set of framework conditions contributing to make some types of human activity and actions possible, and other types impossible. Furthermore, within the range of possible actions, the physical surroundings make some forms of behavioral adaptations more likely than other ones, for instance because differences in geographical proximity make some choices more time-consuming, costly or inconvenient than other alternatives.18.
Apart from actions rendered impossible by the laws of physics, it is not possible to formulate laws about relationships between physical structures and human behavior that are absolute and without any exception. Even though a certain kind of adaptation to the physical environment (e.g. traveling a long detour on the journey to work although the shortest route is not congested) would be considered inconvenient and costly by most people, we cannot rule out the possibility that some individuals will nevertheless choose such a way of traveling (e.g. because they have errands to be carried out in connection with their journey to work). Laws without any exception, forming the basis for what Carl Hempel calls deductive-nomological explanations, may perhaps be formulated within the natural sciences, but not about human adaptation to structural conditions. What our ambition may still be, is to arrive at inductive-statistical relationships telling us what kinds of adaptations are the most likely ones. Such probability relationships can be used to predict with a relatively high certainty which type of adaptation will be the dominating among a large number of individuals, but cannot be used to predict which adaptation a specific individual will choose (Rasch 1992, pp. 22-25). However, for many types of planning problems, what planners need knowledge about are just the aggregate behavioral patterns. Therefore, investigations of probability relationships play an important part in planning research.19.
Data sourcesIn principle, a number of different methodical approaches may be used to shed light on research problems concerning the influence of urban structure on transportation. Internationally, studies of relationship between spatial structures and the extent of transportation have usually been made as model simulations of
18 This assumption about the occurrence of influence from the physical environment on human actions does not imply a belief that the physical surroundings determine people’s actions. However, because human actions are not influenced only by actor-specific characteristics, but also from material structures, there is a need of knowledge not only about actors, decision-making processes and institutions, but also about how – and to what extent – built environment and land use influence people’s activities. This view finds support in, among others, the works of theorist of science Jon Elster. According to Elster (1989), within the range of possible actions, human behavior is influenced by rational choices as well as social norms. Given a set of preferences and constraints, the physical framework conditions made up by the developmental pattern, land use and infrastructure can make some behavioral adaptations more rational than other alternatives of action.19 However, we should not expect that a large proportion of the variation in the behavior of individuals, e.g. concerning travel, could be explained by the physical/structural conditions. Firstly, people have different material, economic and knowledge-related resources. This implies, for example, that distance probably will make up a more important deterrent when members of a low-income family without a car choose their travel destinations, than what is the case for a high-income family with several cars in the household. Secondly, people have different objectives, preferences, values and social networks. This influences what each individual considers to be rational choices, both regarding destinations, travel mode and travel frequency. Thirdly, people’s behavior is to a different extent influenced by social norms, and there is also a considerable difference from individual to individual and between different population groups regarding which norms are being attended to. Finally, no action follows by logical necessity from a motive or an intention. There is always a gap between the existing motivations, impulses etc. and the resulting action, and it is the choice that fills this gap (Østerberg 1986, quoted from Rasch 1992, pp. 13-14). Thus, human actions are influenced by a number of circumstances that are difficult or impossible to survey as a basis for statistical analyses, in addition to the factors that may practically be mapped. In analyses of factors influencing the actions of individuals, it must therefore be expected that a considerable, and often dominating, proportion of the variation will be left unexplained. On an aggregate level, for example when comparing different residential areas or cities to each other, much of the individual variations will be leveled out. A larger proportion of the variation in the dependent variable will then be attributable to urban form and socioeconomic variables that may practically be surveyed in the investigations.
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hypothetical development pattern alternatives. However, we do not consider this approach suitable for our purpose. In order to get valid results out of model simulations, the assumptions of the model about causal relationships between different factors must be correct. As we miss knowledge of how and to what degree the urban structure in Danish towns and the regional population pattern influence people’s traveling pattern (the program is established to make up for exactly this lack of knowledge), such an approach based upon model simulation will not be applicable.
Therefore, the studies of the program should be based on empirical investigations. Here, in principle, both cross-sectional and time-series studies will be possible. In the study on regional level, however, it would hardly be possible to carry out a time-series study in order to illuminate the concrete effects moving from one residential situation to another within the region have on the traveling patterns of certain households and individuals. Among others, it would be difficult to find a sufficiently high number of respondents for such a panel investigation. In the region investigation, cross-sectional studies, comparing the traveling patterns among people living in different situations within one or more regions, seem to be the most fruitful strategy. Such investigations will also be important in the studies of how the location of residential areas within each town influences transportation. However, here we have the opportunity to supplement this with pre- and post-studies of households moving into recently completed houses in different locations, for instance in a peripheral low-density area and in an in-fill project in the inner-city.
In empirical studies of relationship between spatial structure and energy use for transportation, two different main strategies may be chosen in order to collect energy data: A direct method, based on a registration of retail fuel sales within certain geographical areas, and an indirect method, where the energy use is calculated from travel survey data combined with figures from previous research on energy use per traveled kilometer by different means of transportation. The direct method was used in the above-mentioned investigation of Swedish commuting regions, and in the comparisons between Nordic cities. In the present program, where we wish to investigate how the pattern of development on a regional level and the urban situation of residential areas within each town influence the households’ extent of transportation, modal split as well as energy use for transportation, the method based on fuel sales figures is not applicable. Thus, the energy data will be collected by means of the indirect method, where information about the traveling activity of the households is obtained through travel surveys. Use of energy for the various journeys will be calculated according to available knowledge about energy use per passenger kilometer with different means of transportation in various situations (Høyer and Heiberg 1993, Høyer and Simonsen 1996, Larsen and Thost 1989) 20. To such a degree that information is available from the public transport companies, the calculations of energy use for public transport will include the average complement of passengers on the actual lines.
Existing travel surveys are available, that may perhaps serve as a data source for our investigations, among others the nationwide TU data from Statistics Denmark/Denmark’s Environmental Investigations. Inaccuracy in the specification of traveling distances may, however, be a problem with these statistics. As far
20 We will also think about taking into consideration the variation among different car models regarding fuel consumption per kilometer. Information about such differences is available, among others, in publications from the Norwegian Road Traffic Information Bureau. There is, however, hardly any theoretical reason to expect the weight of the cars, motor power, age etc. to be influenced by urban developmental factors. In our analyses of how energy use for transportation is influenced by urban development factors, the variation in the specific fuel consumption of different vehicles will be a variable that has to be controlled for through multivariate analyses, i.e. the specific fuel consumption will be “kept constant”. Thus, the result of the multivariate analyses will be the same as if we do not include the fuel consumption per kilometer in the calculations of energy use. By including the specific fuel consumption of the different car models in the analysis we would, however, be able to identify how large proportion of the total variation in energy use is caused by urban form characteristics, compared to differences in the specific fuel consumption of each vehicle. Ideally, differences in the motorists’ driving pattern (speed, acceleration, etc.) should also be included in the analyses. It may happen, for instance, that motorists doing a large part of their driving in the inner city have different fuel consumption per kilometer than those driving more in the outer parts of town. Trying to survey such differences will, however, involve vast practical problems. Instead, it may be relevant to perform sensitivity analyses to investigate whether this source of error influences the results significantly. Corresponding sensitivity analyses may also be made concerning the energy use of public transport, where downtown congestion tends to increase fuel consumption per passenger kilometer by bus in the inner city. On the other hand, the number of passengers is usually also at its highest in these parts of the town, tending to reduce the energy use per passenger kilometer.
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as we know, the information about traveling distances is based on a division of the investigated areas into a number of zones, where traveling distances are calculated from a matrix showing the distances between the center points of each zone. In reality, of course, people travel to and from a multitude of origins and destinations in each zone, not only between the center points. Because of the quite large round-off errors brought about by this method, the estimated traveling distances may be at a considerable variance with the factual ones. It may also be difficult to identify the residential addresses of the respondents, which is necessary for the registration of urban form factors connected to the dwelling.
Therefore, we think the best result will be obtained if we do our own travel surveys, “custom-built” to suit the research problems of our program, and with special care taken to get the most exact information possible about the households’ traveling distances. We will still try to utilize the TU-data as a supplement, in order to provide a larger geographical breadth. Emphasis will also be put on building up internal competence at the University regarding the use of the TU-data, both with a view to future research on issues where this information may be useful, and to be able to offer students a large data base for project work.
In the program “Transportation and Urban Planning”, however, the major part of the analyses will be based on data collected by ourselves. In order to obtain reliable figures on the total distance driven by motor vehicles in each household, the respondents will be asked to report the mileage for the household’s car(s) (and any other motor vehicles) before and after an investigation period of one week21 (possibly also to report the mileage every evening/afternoon during the week of investigation). As people’s indication of distances often is relatively imprecise, we would otherwise risk that the data for total traveling distance by car and other motor vehicles would be too inaccurate22.
By asking about the address of the workplace, we will, moreover, be able to measure the distance of the journey to work precisely. This way, we will gain a better insight into how large part of the households’ total transportation distance their journeys to work represent, than we would obtain if we were left to using the respondents’ own statements about these distances23. For other single trips than the journeys to work, we will have to rely on the respondents’ own reports on distances. The questionnaire will contain questions about traveling mode(s) and total traveling distance within the purpose category in question for the trips made by the household members each of the 7 days in the week of investigation, distributed on different types of travel purposes (trips to/from work/school, shopping trips, leisure journeys, official journeys and other trips). In addition, we will ask the recipients of the questionnaire to fill in a more detailed travel diary for one or two of the days in the investigation period (probably Saturday and possibly the preceding Friday24). Here, the
21 We here think of a questionnaire survey, designed to a large degree according to the same pattern as the Norwegian travel survey among households in 30 residential areas in Greater Oslo (Næss, Røe and Larsen 1995). Here, the respondents reported the mileage for each of the household’s motor vehicles at the beginning of the investigation period, and then again at the end of the investigation period after exactly one week. Official journeys and trips outside the urban area of Greater Oslo were reported separately and subtracted, in order for the analyses only to include local, private, transportation made by the households.22 Instead of asking about the distance of each trip, in some surveys the respondents have been asked to report traveling time. Traveling time, however, is not really fitted as an indicator of traveling distance, as travel speeds vary considerably between different means of transportation, and in many cases also with when and where the trip is done (among others as a consequence of congestion). In the literature on urban structure and transportation there are still a number of examples showing that conclusions have been drawn about the (lack of) effect of urban structure on the extent of transportation, from analyses where traveling time has been used as a dependent variable in stead of traveling distance (see among others Gordon and Richardson 1997, Snellen et al. 1998). In some other studies addressing the same research problem, the daily number of trips per person has been used as an indicator of the extent of transportation (Kitamura et al. 1997, Boarnet and Sarmiento 1998). Distinct from what is the case for traveling distance, there is, however, no theoretical reason to presume that the number of trips per day will be lower among inhabitants in the central parts of town than in the outskirts. On the contrary, in urban situations with a broad specter of facilities within a short distance, one may expect the number of trips to be somewhat higher and the average traveling distance considerably shorter than in areas where the access to such facilities is not so good.23 In addition, the location of the workplace, measured for instance by distance from the town center, will be included among the independent variables of the analysis. 24 In particular, we would like the travel diary to inform about trips where the destinations are not such a matter of routine as the journeys to work, but which may still be influenced by urban structural factors. Examples of such traveling may be shopping trips and local visit and leisure journeys. Therefore, we have chosen to give Saturday first priority as the day of the week for detailed registration of trips. It would still be desirable to be able to compare the traveling activity of Saturday with the traveling pattern on an
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respondents will be asked to state traveling purpose, addresses for origin and destination, traveling mode as well as estimations for traveling distance and time for each journey made during the day(s) included in the travel diary (including non-motorized trips25). For the trips by transit we will ask for the names of the public transport stops used for entering, leaving and changes of conveyances (if any), so that precise calculations can be made regarding the traveling distances of these trips, based on the distance schedules of the transportation companies and/or geographical information systems (GIS). In addition to information on travel activity, the questionnaires will also contain socioeconomic and lifestyle-related questions concerning the households.
The proposed survey studies aim towards obtaining a wide overview regarding relations between traveling and various urban planning, socioeconomic and lifestyle variables. In addition, case studies will be made regarding attitudes, motives and traveling activity among a limited number of households in different residential areas. The aim of these case studies is to achieve a deeper and more comprehensive knowledge about factors influencing people’s traveling pattern, not to facilitate statistical generalization26 (Handy 1997; Røe 1998). This part of the project will be grounded on in-depth interviews, focusing on the options and limitations of the single individual. We expect to interview about 25-30 households in total (including pilot interviews, see below).
Tentatively, we expect the interviews to be carried out in the homes of each of the selected households, in part with the household members separately and in part with the household collected. The participants in the personal interviews should be selected among households having answered the questionnaire, with the intention of getting a desired variation among the interviewees regarding housing location, socioeconomic status, values and attitudes as well as traveling activity27. Still, a few pilot interviews will be made in advance of the survey investigation, in order to improve our knowledge of circumstances about which the questionnaire should provide information. In addition, it may be relevant to select some households from special groups within the population, for instance “green families” (see below). Alternatively or supplementary to interviews in the homes of the research persons, we will also consider using focus groups, where persons representing different housing situations and lifestyles are brought together to discuss with each other and the researchers the premises and motives for their traveling activity. An advantage of such an approach is that it would make it easier to identify differences in premises and motives, compared to the situation where the households are being interviewed one after another.
ordinary weekday. As travel generally varies somewhat from day to day during the working week (among others with some weekend-related journeys on Monday and Friday, and somewhat more errands in the bank on Thursday due to longer opening hours), it would be desirable to choose for example Tuesday or Wednesday as the other day of diary registration. We think, however, that it would be disadvantageous to split up the respondents’ filling in the travel diary. Therefore, the respondents will be asked to fill in the diary for two subsequent days (Friday and Saturday) or maybe only for one day. Another alternative could be to select Sunday as registration day no. 2. We assume that Sunday, to a larger degree than the remaining days of the week, is used for recreational trips outside the urban area. By choosing Sunday, we would gain better insight into, among others, what influence the green structure on a regional level exerts on transportation. This would, however, be at the sacrifice of information about traveling on ordinary weekdays, which to a higher degree may be expected to be influenced by local urban development factors. The extent of leisure journeys outside town will anyway be registered through the more coarse registration, taking place during the whole week. 25 Here, a line of demarcation will have to be drawn to certain types of athletic, exercise and recreation activity. Should bicycle rides be included, primarily made for the purpose of exercise and without any specific errand? What about rides made to see beautiful scenery, without any particular training purpose? What about jogging and running trips? Should these be included, and in that case, does it matter if the running takes place along the roads, in a forest, or as 400-meter rounds on a stadium? As a line of demarcation, we suggest non-motorized trips to be included in the calculated traveling distance per person, only to the extent they are made to reach specific locations, where the primary aim with the trip takes place (workplace/school, shop, the dwelling of the person being visited, a movie theater, stadium, recreational area etc.). A bicycle ride from the dwelling to a forest area in order to go for a walk will then be included in the calculations, while walking in the forest in itself is not included in the household’s total traveling distance. 26 However, the qualitative interviews provide opportunities to discover factors of influence not included in the quantitative analyses, and to assess whether the results of the survey analyses are distorted from the omission of these variables. Hence, the qualitative interviews will contribute that the generalizations of the project are made on a more informed basis.27 It is desirable to compare households that are relatively similar regarding socioeconomic status and lifestyle orientation, extending over different geographical/urban form situations. At the same time, it is also desirable to compare households living in the same residential area, but differing from one another regarding socioeconomic status and lifestyle orientation.
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As a part of the Local Agenda 21-work in the local community of Lindholm in Aalborg, a project has been started with “green families”, where households through guidance and exchange of experience try to reduce their consumption of natural resources and the environmental strain they create. It is desirable to recruit 2-4 of these households as interviewees in the qualitative part of the research program, of which 1-2 households living in parts of the local community close to the city center and 1-2 in a peripheral residential area28. By studying how urban structural conditions create possibilities and limitations for a more environmentally friendly transportation among households who really wish to reduce the environmental load they create, we may perhaps easier identify the degree to which there is a built-in “structural enforcement” for transportation in the physical surroundings.
In addition to information from questionnaires and personal interviews, maps, official statistics and personal impressions during visits in survey areas will be important sources of data.
Geographical areas of investigation
Study of the regional pattern of developmentThe study of how the regional pattern of development influences travel will focus on two Danish regions, of which one (Northern Jutland, with Aalborg as region center) has a pronounced monocentric distribution of the population, while the other (western Middle Jutland, with Herning as region center29) has a clear multi-nuclear structure. The traveling patterns in the two regions will be compared by making a rough survey study of a random selection of persons (probably 1000) in each region.
Within each of the regions, the traveling activity of the households will be analyzed in relation to the location of their homes within the region, emphasizing the locational and geographical factors described above. To some extent, this will be done using data from the above-mentioned survey of a random sample of persons in each of the two regions. However, the main source of our analyses on intra-regional level will be surveys among all households in a number of geographical areas within one of the two regions (Northern Jutland). The areas will be chosen in such a way that they separately represent comparatively homogenous urban form situations. The process of collecting data for this survey will be coordinated with the collecting of data for one of the investigations of how intra-urban travel is influenced by the location and structure of residential areas within the city (in this case, Aalborg), see below. By selecting a limited number of geographical locations, it will be possible to map a large number of physical/structural conditions in each area and include these variables in the survey. The different areas will be chosen with a view to obtaining a good variation in the different urban form variables, mentioned in the section on priority research problems. The study areas will be demarcated in such a way that each location includes about 150 households30. This means that locations with a high population density will be small in area, while scattered rural survey areas will be comparatively large.
The separate study areas will, as mentioned, be selected with a view to include the greatest possible variation in urban form situations within the region, not with the aim to obtain statistical representativeness. In order to make possible a comparison between the monocentric and the multi-nuclear region, it is necessary to know the traveling pattern among a statistically representative selection of the population within each of the two regions. It would, for instance, not provide a satisfactory basis for inter-regional comparison if a similar investigation was conducted in selected geographical areas also within a multi-nuclear region. Therefore, the
28 Not all “green families” focus on reduction of car use and energy use for transportation as a field of effort. The “green families” who may be included as interviewees in the project should, however, be chosen among households having an explicit wish to reduce the environmental strain they cause through traveling. 29 The choice of western Middle Jutland as region no. 2 is provisionally. Instead, it may be relevant to choose the region around Little Belt (with among others the cities of Fredricia, Vejle and Kolding on the Jutland side and the western and middle part of Fyn (including Middelfart, Odense and Assens) on the east side) as an example of a multi-nuclear region. 30 In practice, the number of households will vary somewhat, because in many cases it may be sensible to let the demarcation follow the boundaries of statistical zones.
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relatively thorough mapping within specific locations in one region – as well as a rougher survey of a random sample of persons in both regions – is necessary as a basis for inter-regional comparison. The latter survey will also give a better basis for considering the degree to which the results from the study of single areas within the region can be generalized to the region as a whole and across regions.
Because the questionnaire will be sent to all households in the selected geographical areas, we expect to get a sufficient number of answers from each area to make it possible to give quite reliable and precise figures on average traveling distance, modal split and energy use for transportation among the inhabitants of each area. This will provide a good basis for visualizing relationships between urban structural characteristics and transportation by comparing actual locations, which is an important pedagogical advantage. To some extent, we will also make statistical analyses and qualitative comparative analyses using the sub-areas as units. The main part of the statistical analyses, however, will be made with the separate households (and for the roughest survey – the individuals) as units.
In addition to these analyses, we will probably use existing TU-data on a national scale to execute rough analyses that may illuminate some of the issues focused on in a wider Danish context. It may also be relevant to use information from Statistics Denmark regarding home address and workplace for workforce participants.
In addition to the different types of survey data, our study of the influence of the regional pattern of development on traveling will make use of information from qualitative interviews of households, especially with the purpose to shed light on differences between urban and rural areas.
Study of urban planning factors within the separate townProvisionally, the study of how local travel is influenced by the urban structural situation of residential areas within each town is planned to be made up of investigations in 4-5 towns, covering a broad specter of different town sizes in a Danish context: Frederikshavn, Herning (alternatively: Vejle31), Aalborg, Odense and possibly also the Copenhagen area. The reason for selecting towns of different sizes is, among others, a wish to investigate whether the relationship found in Oslo and some other cities between traveling distance and the distance from the dwelling to downtown, is also present in smaller and larger towns. The chosen research design implies that the examined towns are to a large degree located within the same regions as focused on in the region study.
In each town, 10-20 residential areas will be selected, representing different locations and urban form situation in other respects, and each of them with approximately 150 households. As in the region study, the reason for this strategy is that it makes it possible to map a large number of urban form factors in each area and include these variables in the analyses. The number of selected areas will vary according to the size of the town (a larger number in the largest towns) and with the possibilities of detailed mapping of urban form factors (the best possibilities are found in Aalborg, due to the location of the researchers involved). Like in the region study, all households within each residential area will receive our questionnaire. This will provide good opportunities for a comparison between the areas, in addition to the principal statistical analyses that will be made with the separate households as units.
At the outset, we also intended to facilitate a comparison between different cities, where variations in the extent of transportation and modal split could be explained from differences in urban structural variables on a city level. This might also facilitate a reliability test of the data for energy use from the project “Energy and Built Environment”, where information about fuel sales was used as indicator on the energy use for local transportation in the towns examined (of which 4 Danish: The Copenhagen area, Århus, Randers and Vejle) (Næss, Sandberg and Røe 1996). The project design chosen does not comply with these wishes. We have, after a closer consideration, reached the conclusion that a comparison based on towns as units would demand
31 Whether Herning or Vejle is to be chosen depends on whether the Herning region or the Little Belt region is selected as an example of the multi-nuclear situation.
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considerable work to supply updated urban structural data for the relevant towns, as the mapping in the project “Energy and Built Environment” applied to the situation in 1990. As time has gone by, it will also be less meaningful to compare new data regarding energy use for transportation, based on travel surveys, with the fuel sales data collected in the towns mentioned. Thus, we have chosen not to include in the studies any direct comparison of the extent of transportation in different downs. This also makes it needless to include any survey investigation among a random selection of the population in each town, which would otherwise be necessary. Nor will we be forced to let the consideration of a reliability test between different types of data direct our selection of towns.
Instead, the conclusions from the studies in each town will be compared, among others regarding the importance of the distance of the dwelling from downtown and a number of other urban form variables.
As suggested above, our own geographical location makes it natural to go somewhat more detailed into the situation in Aalborg than in the other examined towns. Therefore, the qualitative interviews of households will be concentrated to this town (and some households in the surrounding region, cf. above)32. Furthemore, we will try to find two areas in Aalborg where new residences will shortly be built, one with a central location and one peripheral. The future inhabitants of these areas may then be asked about their traveling patterns in their original residential situation, with a repetition of the investigation a short time after their moving into the recently developed areas. In order to capture possible adjustments over time, it is also desirable to follow up with a third investigation approximately 2-2½ years later.
Study of lifestyle domains and transportationThis part of the program will take advantage of material from the above-mentioned quantitative and qualitative studies in Aalborg. Material from the recently completed project “Urban Environment Indicators” (Marling and Knudstrup 1998) will also be utilized. In connection with the qualitative interviews it would, among others, be of interest to make the interviewees draw “mental maps”, showing what places and elements in the neighborhood and the physical environment of the town they consider important (cf. Lynch 1960/1996, Pløger 1997). Registration of the actual traveling patterns of the interviewees on ordinary maps will, however, also be made.
A preliminary overview regarding survey areas and selection sizes for the different studies of the program is shown in Table 1.
Personnel and work schedule The program is supervised by Professor, Dr.Ing. Petter Næss, who will also himself carry out parts of the study of how transportation is influenced by the urban form situation of residential areas within the separate town. In addition, Assistant Professor Ole B. Jensen (sociologist) and Assistant Professor Steen Seierup (cultural geographer) take part in the program, the latter on a preliminary basis so far. Seierup will have a special responsibility for the part of the program focusing on different lifestyle groups’ use of various geographical areas (domains) within the town. One 2½-year’s vacant post as Assistant Professor will be filled during the first half of 1999.
Two Ph.D. scholarships are attached to the program. One of these focuses on relationships between regional developmental patterns and travel, and is held by Civil Engineer Hans Henrik Winther Johannsen, who was appointed December 1, 1997. M. Techn. Soc. Thomas Alexander Sick Nielsen is from September 1, 1998 appointed in the other Ph.D. scholarship. The issue of his project is how urban structure, including the location and shape of residential areas, influences the inhabitants’ extent of transportation, modal split and energy use for transportation. A separate project description has been made for each of the two Ph.D. projects (Johannsen 1998, Nielsen 1998). Petter Næss is the main sponsor teacher for both of the Ph.D.-
32 In addition, it may be relevant to interview a few households in the inner areas of Copenhagen, from a hypothesis that urban form factors as well as attitudes towards transportation may here differ somewhat from what we find in the central parts of other Danish towns.
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students.
The program is funded by the Danish Transportation Council. It was formally started in the late autumn of 1997, and was originally scheduled to 3 years. We have, however, found it practical to stretch the program to include a period of 5 years. This is due to the fact that the program did not really get started until the spring 1998 (for instance, the head of the program was not appointed until February 1998), and because the second Ph.D. student did not start until September 1998. It has also turned out to be impossible to achieve such a major research buy-out of employees at Aalborg University as presupposed in the program. We have therefore, after having discussed the matter with the Transportation Council, made a revised time schedule, according to which the program will be finished by the end of 2002. Table 2 roughly shows how the man-months and other resources will be distributed over the period.
Reference groupA reference group has been established for the program. The main function of the reference group will probably be critical reading and commenting on research designs and draft questionnaires, reports and articles from the project. A very limited meeting activity is planned, partly to save travel and accommodation expenses and partly to release as much as possible of the resources available for the reference group to reading and commenting the material received. Nevertheless, one annual meeting should be held in the reference group, preferentially in connection with Trafikdage (Traffic Days) at Aalborg University.
Cooperation with other research projectsAs mentioned above, a close cooperation is planned with the program “Urban ecological welfare development” regarding research problems related to the influence of lifestyle factors on traveling. This program is carried out in cooperation between Aalborg University and the Danish Building Research Institute, with Gitte Marling and Mary-Ann Knudstrup as the main responsible researchers at Aalborg University.
We have also established a cooperation with the project “Sustainable urban structure, land use and transport” at the Danish Research Center on Forest and Landscape (FSL). Parts of this program focus on the same research problems as “Transportation and Urban Planning”, but the program of FSL is generally more user-oriented, with less weight attached to in-depth theory development. Neither does it address the research problems concerning regional pattern of development, and it does not go as deeply into the problems related to the importance of lifestyle and socioeconomic factors, as does “Transportation and Urban Planning”. On the other hand, FSL’s program includes analyses of changes in development structure over the last 40 years in the Copenhagen area, estimation of transportation consequences of different land use scenarios and development of a quantitative EDP model for such consequence estimations. The cooperation between the two programs will take place through exchange of written material and by arranging common seminars for the researchers involved. Furthermore, the program leaders (Gertrud Jørgensen and Petter Næss) represent the two programs in each other’s reference groups.
The reference group consists of the following four persons:Research Manager, Ph.D. Gertrud Jørgensen, the Danish Research Center on Forest and Landscape Civil Engineer, lic.tech. Flemming Larsen, Anders Nyvig Inc.Professor, Dr.Ing. Arvid Strand, Norwegian Institute for Urban and Regional Research, NorwaySecretariat Manager, Civil Engineer Susanne Krawack, the Danish Transportation Council.
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Table 1. Partial investigations, study areas and sample sizes in the program “Transportation and Urban Planning”
Partial investigation: Executed by: Period: Data sources and study areas:Time for interview or questionnaire survey: Sample size:
Regional pattern of development and travelPh.D. student Hans Henrik Winther Johannsen
1998-2000
Survey of a random sample of persons in 2 regions 1999 2x1000Survey of households in selected locations within Northern Jutland
1999approx. 2500(15-20 residential areas, each with approx. 150 households)Furthermore data from investigation of areas in Aalborg (se below).
Qualitative interviews with some households in Northern Jutland
2000 5 - 10
TU-data Already available (Statistics Denmark)
Transportation consequences of the urban form situation of residential areas within the separate town
Professor Petter Næss, Ph.D. student Thomas A. S. Nielsen,Assistant Professor Steen Seierup,Ph.D. student Ole B. Jensen
1998-2002
Survey of households in selected residential areas in Frederikshavn
1999 or 2000approx. 1500(10 areas of approx. 150 households)
Survey of households in selected residential areas in Herning (or Vejle)
1999 or 2000approx. 1500(10 areas of approx. 150 households)
Survey of households in selected residential areas in Aalborg
1999 or 2000approx. 3000(20 areas of approx. 150 households)
Survey of households in selected residential areas in Odense
1999 or 2000approx. 2000(12-15 areas of approx. 150 households)
Possible survey of households in selected residential areas in the Copenhagen area
1999 or 2000approx. 2500(15-18 areas of approx. 150 households)
Qualitative interviews with some households in residential areas in Aalborg (and possibly a few in Copenhagen)
1999 or 2000 approx. 15-20
Lifestyle domains and transportation Assistant Professor Steen Seierup,
1999-2002The above mentioned qualitative and quantitative studies in Aalborg
The program as a whole is headed by Petter Næss, who is also the sponsor teacher of the two Ph.D. students participating in the program. In the qualitative interviews, other researchers than those primarily involved in the partial investigation in question, may also participate.
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Table 2. Draft budget of the program “Transportation and Urban Planning”
Total number of man-months 1997+1998 1999 2000 2001 2002
Figures in DKK
ExpendituresOut of this internally financed
Wages (expenses stated as number of man-months)Scientific personnel in total 74 3.300.000 1.800.000Petter Næss 34 6 7 7 7 7Gitte Marling 3 3Harry Lahrmann 3 3Ole B. Jensen 8 1 2 2 2 1Steen Seierup 2 2Assistant Professor (not yet appointed) 24 4 10 10
The Department’s part DKK 90.000 90.000Contribution to Aalborg University common DKK 1.248.280 1.248.280 556.940
The project in total 7.489.680 3.341.640
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Cooperation has also been established with a Ph.D.-student from Slovenia, Aljaz Plevnik, who works with empirical studies of relationships between urban structure and transportation in the Slovenian town of Maribor. The cooperation will primarily take place through common discussions of methods, theory and empirical finds, and mutual commenting of draft publications. A genuine comparative perspective is not planned, as this would require harmonizing of the survey methods to ensure a maximum degree of comparability and in-depth studies of social structural factors that might possibly explain differences in transportation pattern between the two countries. It will still be interesting to compare the results of our investigations in Danish towns with the results of Plevnik’s study in Slovenia.
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