Dirk Zumkeller

Who Made Peak Car, and How? A Breakdown of Trends over Four Decades in Four Countries

This paper investigates the contribution of underlying trends to per-capita car travel development since the 1970s in France, Germany, Great Britain, and the USA. In these countries, after a long period of growth, car travel began to show signs of stagnation — or even decrease — after the 1990s. Our paper breaks down underlying demographic and travel trends for two study periods: first, a period of per-capita car travel growth (until the mid-1990s); second, a period of stagnation or decrease in car travel (beginning around the turn of the millennium). Two patterns of development emerge: (1) in France and the USA, the reversal in the trend in car travel per capita was due mainly to trend changes in total travel demand by drivers; (2) in Germany and Great Britain, the levelling off of motorisation, and shifts to other modes, played a much larger role. Ageing has in recent years gained weight in shaping per-capita car travel trends. In Europe, the continued increase of car availability for seniors has had a damping effect on peak car. Even though all age classes have contributed to peak car, young adults stand out in this regard and therefore deserve special attention.

INFRASTRUCTURE DEVELOPMENT IN GERMANY UNDER STAGNATING DEMAND CONDITIONS: A NEW PARADIGM?

Findings from various sources of information, such as mobility panels, permanent road traffic recording devices, and model calculation methods, indicate that for the past few years passenger traffic demand in Germany has not been increasing but has shown notable evidence of stagnation. An analysis of various relevant factors clarifies that this has in fact been an emerging tendency. This is true especially with respect to the demographic changes in Germany and the increased probability of more scarce and definitely more expensive oil resources; further stagnation of traffic demand appears imminent. That leads to the conclusion that infrastructure development must not be based on the idea of everlasting growth with expansions in areas in which the symptoms of traffic growth have been most obvious. It will rather be necessary to identify accurately specific areas of growth or stagnation and to find a suitable scale for further development. Future planning should concentrate on modification rather than on expansion of infrastructure facilities.

Changes in Variations of Travel Time Expenditure

To improve methods of evaluating the benefits from investments in the transport infrastructure, this paper attempts to develop a method for capturing changes in variations in travel time expenditure and shows empirical results from data from the German Mobility Panel, a multiday and multiperiod panel survey. The proposed methodology can simultaneously and explicitly deal with changes and variations. The empirical analysis indicates that over time, travel time expenditures become more dependent on situational attributes than on individual or household attributes; such dependence implies that travel time expenditures change toward diversification and that longer periods of behavioral observation to describe peoples travel time expenditures become more important. The results also imply that understanding of the dynamic aspects of behavior is still important and remains a challenging issue to be revisited, not only for improving forecasting models but also for reconsidering the benefits from investment in transportation infrastructure.

Nonresponse, Selectivity, and Data Quality in Travel Surveys: Experiences from Analyzing Recruitment for the German Mobility Panel

Since 1994, the German Mobility Panel (MOP) has been one of the oldest multiday and multiperiod travel surveys. Along with the need to understand behavioral processes, the demand for such detailed and extensive data is increasing. However, for respondents to take part in a survey like the MOP is often time-consuming. Therefore, with generally declining response rates, it is even more difficult to recruit a suitable sample of test participants for a multiday or multiperiod survey. If a selective nonresponse problem exists, this calls into question the representativeness of such a survey. For the MOP, respondents were recruited in a multistage process that provided an opportunity to study selectivity. The findings indicate that sociodemographics dominate selective nonresponse. There is also some mobility-related selectivity because people for whom mobility is an everyday issue take a stronger interest in the survey topic and are therefore more likely to participate in the survey. It was also found that recr...

Optimal Sampling Designs for Multi-Day and Multi-Period Panel Surveys

Abstract Purpose — This study proposes an optimal survey design method for multi-day and multi-period panels that maximizes the statistical power of the parameter of interest under the conditions that non-linear changes in response to a policy intervention over time can be expected. Design/methodology/approach — The proposed method addresses balances among sample size, survey duration for each wave and frequency of observation. Higher-order polynomial changes in the parameter are also addressed, allowing us to calculate optimal sampling designs for non-linear changes in response to a given policy intervention. Findings — One of the most important findings is that variation structure in the behaviour of interest strongly influences how surveys are designed to maximize statistical power, while the type of policy to be evaluated does not influence it so much. Empirical results done by using German Mobility Panel data indicate that not only are more data collection waves needed, but longer multi-day periods of behavioural observations per wave are needed as well, with the increase in the non-linearity of the changes in response to a policy intervention. Originality/value — This study extends previous studies on sampling designs for travel diary survey by dealing with statistical relations between sample size, survey duration for each wave, and frequency of observation, and provides the numerical and empirical results to show how the proposed method works.

Analysis of PAPI, CATI, and CAWI Methods for a Multiday Household Travel Survey

Abstract Purpose — In this chapter the three household travel survey methods PAPI (paper and pencil interview), CATI (computer-assisted telephone interview), and CAWI (computer-assisted web interview) are compared in order to show well-known and new methodological effects. Methodology/approach — The survey concept in the Stuttgart region with the three methods (PAPI, CAPI, and CAWI) offers the possibility to analyze the differences between these methods. This approach offers various possibilities to compare the subsamples and to evaluate the effects of the different survey methods in order to ensure a high data quality. Findings — The results show a clear tendency that retired people prefer the CATI design instead of CAWI, while younger persons prefer the CAWI design. The PAPI design seems to cover all parts of the population to the same extent and also achieves the same response levels as CATI and CAWI. Originality/value of chapter — The three different survey methods within one survey allow on the one hand methodological analyses without distortion of results by different framework conditions. On the other hand the CATI and CAWI survey methods are relatively new in the field of multiday surveys especially in Germany.

Data Quality and Completeness Issues in Multiday or Panel Surveys

Abstract Purpose — The paper aims at an improvement of the understanding, how mobility is reported in longitudinal surveys and to develop ideas how to assess the completeness of the reported mobility. Methodology/approach — Analyses of data quality and completeness are performed on the multiday and multiperiod data of the German Mobility Panel. Distinctions are made between differing reporting behaviours of individuals who either reported three times, two times or only once. Findings — It can be shown that the reporting behaviours are different depending on the number of repetitions. The results illustrate that on the one hand individuals who repeat the survey in a consecutive wave tend to report with greater motivation, endurance and accuracy. On the other hand, participants who have not reported completely and accurately are more likely to drop out. These effects positively influence the quality and completeness and therefore the reliability of recorded mobility figures in multiperiod mobility surveys. Practical implications — The analytical possibilities of combined multiday and multiperiod data in terms of the assessment of data quality will be demonstrated. Hints to identify such types of survey artefacts are presented.

Moving from Cross-Sectional to Continuous Surveying: Synthesis of a Workshop

This chapter describes how transport policy and infrastructure development is embedded in an overall framework that addresses issues of economic growth, ecological and social sustainability, spatial accessibility and social access to opportunities. The further development of these elements results in often very expensive transport infrastructure that must be viewed from a long-term perspective and that is hardly reversible. Furthermore, these developments show considerable change over time with respect to a globalizing economy, climate change, ageing societies and the social divide. To further develop the transport infrastructure, it is very important to have an understanding of current as well as future travel demand. This should eventually result in a better understanding of processes, including the early identification of growing, declining and stagnating developments. While the understanding of current demand can often be captures by a single survey, the understanding of behavioral processes clearly requires more than isolated snapshots.