ESRA 2025 Preliminary Program
All time references are in CEST
Current Developments in Mobility Survey Methods 2 |
| Session Organisers |
Dr Johannes Eggs (infas)
Dr Stefan Hubrich (TU Dresden)
Dr Rico Wittwer (TU Dresden)
|
| Time | Friday 18 July, 11:00 - 12:30 |
| Room |
Ruppert 114 |
Travel surveys collect data on the mobility of populations. Large-scale national household travel surveys are used to estimate key mobility figures on national or sub-national levels, like out of home rates, trips and transport mode rates, and to predict the demand of the population regarding the use of transportation modes. But high respondent burden and sinking response rates are pressing on the established travel survey designs. On the other hand new technologies are available to ease survey participation.
The focus of this session is explicitly wide and aims to gather an overview about the cur-rent developments, challenges and ideas for mobility surveys. Papers matching one of the following aspects are invited to be part of this session (but are not restricted to):
– New technologies for data collection and mixes mode approaches
– Integrating GPS data in trip and survey data
– Gamification in travel surveys
– Survey mode effects in travel survey
– Improving trip reporting in different modes
– Improving household completion rates
– Effects of proxy interviews
– Methods to collect mobility data for specific sociodemographic groups (e.g.children)
– New sample frames and weighting procedures
– Incorporation of big data
Keywords: Survey methods, Survey design, travel, traffic, mobility
Papers
Introducing a digital diary for the England National Travel Survey
Ms Lisa Eyers (Department for Transport) - Presenting Author
Since 1965, England's National Travel Survey (NTS) has collected data from households on their personal travel over a 7 day period using a paper travel diary. The paper diary represents significant printing, logistical and processing costs, adding to the time it takes to process and release NTS data.
In 2018, the Department for Transport commissioned a digital specialist contractor to develop a web-based digital diary to be hosted on the UK government's gov.uk platform. This represents the biggest methodological change to this survey in many years. Digital development has taken place alongside a programme of work to integrate the digital diary into the long-established data collection process which utilises face-to-face interviews in the household.
A large-scale test was conducted in early 2024 to assess the impact of introducing a digital-first approach. The Parallel Run compared response rates, sample composition, parameter estimates and fieldwork procedures between standard paper diary respondents and those offered the digital diary. The test found that the digital diary collects robust data and is integrated well, having no substantial impact on response rates, fieldwork, or processing procedures. Trip data was found to have some statistically significant but small differences, with some indications of under-reporting in the digital condition. Certain socio-demographic factors were systematically related to digital uptake (e.g., age and ethnicity) and proxying rates (e.g., sex, disability, and education).
Encouraging Respondents in Travel Surveys with Classification Results: A Case Study in Improving Data Quality and Engagement
Mr Nicolas Salbach (Karlsruhe Institute of Technology - Institute for Transport Studies) - Presenting Author
Ms Miriam Magdolen (Karlsruhe Institute of Technology - Institute for Transport Studies)
Mr Lukas Burger (Karlsruhe Institute of Technology - Institute for Transport Studies)
Professor Peter Vortisch (Karlsruhe Institute of Technology - Institute for Transport Studies)
Surveys often face challenges like low response rates, high dropout rates, and incomplete data, complicating analysis. Missing data may require imputation, introducing uncertainties, while high dropout rates increase costs and limit scalability. Developing strategies to ensure high data quality and participation is essential.
Our study examined whether returning survey results could enhance respondents’ motivation and data quality, specifically by returning their assigned urban mobility type. The case study was conducted in Dreimühlenviertel, a small, central district in Munich, Germany. The survey work consisted of two parts: first, a travel skeleton survey collecting typical travel behavior, including everyday and long-distance travel, and attitudes towards transport modes (von Behren et al., 2018). Magdolen et al. (2019) segmented respondents into urban mobility types, allowing classification of respondents in subsequent surveys, including those in Dreimühlenviertel. In a customized follow-up survey months later, respondents were asked to self-classify into these urban mobility types. Afterwards, they received feedback in the form of a characterization of their urban mobility type based on their travel skeleton survey report. The study aimed to evaluate incentivizing respondents with personalized results, refine urban mobility types, and assess their clarity and communicability.
Our approach achieved a 46% response rate in the follow-up survey with only two incomplete responses (N = 53). While we cannot separate the effect of feedback from respondents’ intrinsic motivation, the results suggest that informing respondents about their classification outcomes improves data quality and participation. This approach is effective in segmentation studies, where group memberships are easy to communicate. Despite a four-month lag between surveys, respondents remained interested in their results. Sharing results immediately could further boost engagement and satisfaction.
Our study suggests that incentivizing respondents with their classification results can boost motivation, enhance data quality, and increase response rates, ensuring reliable findings.
Quantity versus Quality in Travel Diary studies?: Evaluation of a Smartphone App Collecting Geolocations to Construct Travel Diaries
Ms Danielle Remmerswaal (Utrecht University) - Presenting Author
Dr Jonas Klingwort (Statistics Netherlands)
Professor Barry Schouten (Statistics Netherlands)
Given the limitations of traditional diary studies (measurement errors and nonresponse) and the increased use of smartphones, growing attention is given to smartphone-based travel surveys. Smartphone travel apps can make use of geolocation sensors present on the smartphone to construct a travel diary.
Statistics Netherlands developed a state-of-the-art smartphone app to measure mobility behavior in the Netherlands. The smartphone app automatically compiles a travel diary, consisting of a series of movements and stops, based on passively collected geolocation data. In 2022 and 2023, the app was tested in a large-scale field test (initial sample n=3200, realized sample n = 505). This test aimed to analyze and evaluate design choices such as the data collection strategy (response rate and participation duration), the app sensor tracking implementation (measurement frequency and battery management), the respondent interaction (active-passive trade-offs), the data quality and validation (quality requirements), and the AI-ML predictions (travel mode/motive prediction).
The field test included several randomizations to study these design choices, which we will report on in this paper. In particular, we address an influential choice: the duration of the travel diary. For this choice we look at data quantity and data quality as a function of time in-study. Our conclusions and recommendations have relevance across a wide range of research areas concerning studies on (time-use) behaviour, studies considering similar design choices, and studies using (smartphone) sensors.
