Workshop synthesis: Measuring attitudes and perceptions in large scale (quantitative) surveys

This paper presents the main outcomes of the workshop A5 Measuring attitudes and perceptions in large scale (quantitative) surveys. There is a big need in the community to include more questions about psychological factors in surveys, because the travel behavior is getting more divers. The workshop discussion revealed that while there are different survey methods to capture information about the participants’ psychology, Likert scales are mainly used because they are easy to implement and to fill in. However, the reliability of the results must be assessed in light of the survey method and type of analysis. Further research is needed to combine quantitative surveys with methods to collect psychological information

Social aspects of long-distance travel - a study of two survey designs

Major parts of transportation research focus on everyday travel, including qualitative, quantitative and mixed-methods approaches. However, to find strategies to reduce transport-related emissions on a global scale, studies on long-distance travel require greater consideration. This paper presents and compares two independent mixed-methods research approaches exploring social aspects of long-distance travel. While one study is qualitative dominant and focuses on relational aspects of travel decisions, the other is quantitative dominant and originates from the individuals’ needs. Both studies highlight motivational factors as important stimuli for long-distance travel patterns and that part of long-distance travel is due to social commitment

How the COVID-19 pandemic changes daily commuting routines – Insights from the German Mobility Panel

The COVID-19 pandemic has had a major impact on everyday travel and, by extension, everyday commuting. During the pandemic, some people were able to work from home while others continued commuting. This study examines how commuting behavior changed between 2019 and 2020. In this study, we analyze panel data of the German Mobility Panel, a national household travel survey. We paint a broad picture of the characteristics and behavior of those who commuted during the pandemic. The analyses focus on the intra- and interpersonal differences and are presented in a mostly descriptive way. The results show that people with low income and a low level of education are primarily those who cannot work from home and do not have flexible working hours. The results further show that especially public transport has lost importance in daily commuting. However, those who commuted in 2019 and 2020 did not significantly change their commuting behavior regarding commuting time and commuting mode

Effects of COVID-19 on Telework and Commuting Behavior: Evidence from 3 Years of Panel Data

The COVID-19 pandemic has forced employers and employees to re-evaluate their attitudes toward telecommuting. This induced a change in the sheer number of people who have started to work from home (WFH). While previous studies highlight differences between telecommuters based on their level of telecommuting experience, these effects have not been studied in detail. This may limit the evaluation of implications for post-pandemic times and the transferability of models and predictions based on data collected during the COVID-19 pandemic. This study expands on previous findings by comparing the characteristics and behavior of those who have started to telecommute during the pandemic and those who had already telecommuted before. Furthermore, this study addresses the uncertainty that exists about whether the findings of studies conducted before the pandemic—for example about sociodemographic characteristics of telecommuters—still hold true, or if the pandemic induced a shift in telecommuters’ profiles. Telecommuters show differences when considering their previous experience in WFH. The results of this study suggest that the transition induced by the pandemic was more drastic for new telecommuters compared with experienced telecommuters. The COVID-19 pandemic had an effect on how household configurations are considered in the choice to WFH. With decreased access to child care resulting from school closings, people with children in the household were more likely to choose to telecommute during the pandemic. Also, while people living alone are generally less likely to choose to WFH, this effect was reduced as a result of the pandemic

Mobility Styles and Car Ownership - Potentials for a Sustainable Urban Transport

Decision-makers in cities worldwide have the responsibility to contribute to the reduction of greenhouse gas emissions in urban transport. Therefore, effective measures and policies that allow for a change in people’s mobility towards sustainable mobility must be derived. To understand how different people respond to measures and policies, and to increase the effectiveness of such policies, individual mobility needs and mobility determinants have to be considered. For this, the definition of individual mobility styles as holistic descriptions considering travel behavior, attitudes, as well as life stages is useful. This study presents a segmentation approach that identifies eight urban mobility styles by using data from a multidimensional survey conducted in Berlin and San Francisco. We applied a cluster analysis with both behavioral and attitudinal characteristics as segmentation criteria. By analyzing the characteristics, we identified a mobility style—the Environmentally Oriented Multimodals—that is environmentally oriented, but not yet all people in this cluster are sustainable in their mobility. Thus, they are the group with the highest potential to accept and use sustainable mobility. Additionally, we found that within the Environmentally Oriented Multimodals, the change from one life stage to another is also likely to be accompanied by a car acquisition

Influences of Norm and Excitement on Bike Use Behavior of High-Income People in China

In China, the bicycle had a high relevance in the past. Some decades ago, it was the major mode for most Chinese people. This situation changed with growing wealth and increasing car ownership. Today, as cities are traffic-crowded, the bicycle seems to be an alternative again. At the same time, the government as well as private equity, invest in public bike systems. Previous research indicates that especially people with high-income are less likely to use the bicycle as a mode of transport. The question arises whether the bike is used by high-income people that usually have a car as an alternative. What are the influencing factors to use bicycles? To investigate these aspects, we present results of a study conducted in 8 Chinese cities. The data is analyzed using a structural equation model to investigate influences on bike use behavior of high-income people. This study provides no contribution in the research of psychological characteristics of users or the routes used. Rather, it is intended to provide understanding to ecological norm and excitement regarding usage. The results provides insights into the complex interrelationships of sociodemographic and psychological aspects as well as the modernity of the cities in the context of bike usage. Mainly car ownership and the place of residence show significant effects on the attitudes and norms of people and thus influence the use of bicycles. Our results help to understand the interrelationships between sociodemographic characteristics, spatial characteristics and the attitudes of people while making mobility decisions

Identification of Non-Routine Tours in Everyday Travel Behavior

This paper deals with the distinction between everyday and tourism related travel. As no objective definition exists to differentiate between these two, surveys usually focus only on one aspect. In particular, this does not provide an overall picture of tourism related travel as some tourism activities are also embedded in everyday life, such as day excursions. However, it is of high relevance to distinguish these types of travel as policy measures may influence these aspects of travel differently and motivations and backgrounds to perform such travel are different. According to the World Tourism Organization (UNWTO), tourism activities take place outside the usual environment of people. In this paper, we approach this subjective definition of a personal environment using data of the German mobility panel. Analyzing the data of three reported weeks of everyday travel behavior per person, we calculate personal thresholds to approach an individual usual environment to decide which part of everyday travel behavior is outside of this environment and thus called non-routine. For this decision, we present a stepwise heuristic that finally distinguishes between routine and non-routine behavior for each tour of a person. Using one heuristic version for analysis, we identify 8.56% of all tours as non-routine. This corresponds to 9.57% of all reported trips but accounts for 33.44% of distances travelled in our dataset. Young people and students have the lowest share of non-routine tours. The opposite was found among pensioners and older age groups who have the highest shares of non-routine behavior

Checking Data Quality of Longitudinal Household Travel Survey Data

Ensuring data quality of household travel survey data is often tedious and, thus, time-consuming. To speed up the process of data-checking and to gain an in-depth understanding of the data, data visualization is a practical, fundamental tool. Since 1994, data visualization has been used in the German Mobility Panel (MOP) data-checking process. This paper presents two graphical visualization tools developed for the MOP. Both tools speed up the data checks and ensure high consistency in identifying erroneous data. This paper describes and discusses how the tools provide a continuous data quality assessment

Identifying and understanding long-distance travel demand by combining official transport statistics and survey data

While much is known about everyday travel of the German population, long-distance travel is still underreported. The main data source, the national travel survey “Mobility in Germany (MiD)”, cannot simply be used to describe the demand: complex extrapolations and complementary data are necessary to obtain a consistent picture. The presented approach of ‘data fusion’ integrates different data sources to provide the overall long-distance travel demand. The result reveals that almost half of the total transport performance of the residential population in Germany (46 % of passenger kilometers) is accounted for by trips of at least 100 km (one-way distance)