Current Developments in Mobility Survey Methods 2 |
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| Session Organisers |
Professor Caroline Bayart (University Lyon 1) Dr Johannes Eggs (Infas - Institut für angewandte Sozialwissenschaft GmbH) Mrs Dana Gruschwitz (Infas - Institut für angewandte Sozialwissenschaft GmbH) |
| Time | Wednesday 17th July, 11:00 - 12:30 |
| Room | D01 |
Travel surveys collect data on the mobility of populations. Large-scale national household transport 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.
Transport surveys face with a drop of response rates over the world. Even if weighting procedures allow to reduce the incidence of non-response, it is not always possible to postulate that people with some socio-demographic characteristics who do not respond to a survey have the same behaviour than people with the same socio-demographic characteristics who respond and survey non-response might produce bias.
Travel surveys have also some peculiarities, like the focus on trips’ collection for specific days only. They also need a higher number of respondents in comparison to “regular” social surveys, to reach an adequate precision to model and predict travel and transport demand on a regional level. Efforts are made to increase response rate for traditional transport surveys by improving the questionnaire, reducing respondent burden, increasing reminders… Even if results are generally positive, it is in most cases not sufficient. Moreover, implementation of travel surveys is relatively expensive.
New forms of mobility, like car - or bike - sharing that allow passive forms of data collection methods for this specific subgroup, mixed-modes surveys and incorporation of “Big data” are getting increased attention to lower transport survey costs. The potential of new interactive media and Big data seems to be high to improve transport surveys. But the question of data comparability remains. The danger when databases are merged is that a sample selection bias will be created and compromise the accuracy of explanatory models.
The aims of the session will be to discuss the potential of new technologies for mixed modes framework and the opportunity to combine transport survey results with other data sources. It will be possible to characterize bias generated by these methods and to give some perspectives for reduce them. Topics for this session may include (but are not restricted to):
• Survey mode effects in travel survey
• Passive data collection in travel surveys
• Integrating GPS data in trip and survey data
• Improving trip reporting in different modes
• Effects of proxy interviews
• Combining mobility data sources
• Improving household completion rates
• Methods to collect mobility data for specific sociodemographic groups (children)
Keywords: Mixed-modes surveys, combining survey data, mode effects, data comparability, big data
Ms Krisje Wijgergangs (KiM Netherlands Institute for Transport Policy Analysis) - Presenting Author
Dr Sascha Hoogendoorn-Lanser (KiM Netherlands Institute for Transport Policy Analysis)
Last year the tooling of the Netherlands Mobility Panel (MPN) has been updated. The MPN is a household panel on travel behaviour, consisting of an online annual household questionnaire and an individual questionnaire plus a three-day travel diary. In the first five years only limited changes were made. However, during this period, the technology has evolved and the share of respondents using their mobile devices to access the questionnaires increased, while the existing tooling was mainly developed for traditional devices. In order to improve survey experience of respondents and reduce response burden, and therefore the risk of panel attrition, the tooling has been redesigned to a state-of-art online questionnaire and travel diary.
Since continuity is key in longitudinal surveys, changes are not desired. However, not supporting mobile device users is even less desired. Therefore, the main challenge was to improve the design while keeping changes to a minimum. The philosophy of a location-based diary is preserved and the order, type and phrasing of questions asked to the respondents have not changed. Furthermore, an exploratory literature study is done and respondents were closely involved by the development through in-depth interviews. Based on this research well-considered decisions were made concerning adjustments to the tooling.
With the help of a User Experience Designer the new design is made intuitive and user friendly. Furthermore, the tools can be used on all types of devices. For the questionnaires an adaptive design is developed, with large buttons, only vertical scrolling and split-up grid questions for mobile devices. Filling in the diary has become easier since the design gives visual support, so respondents are guided through their days, triggering their memory optimally. Other changes are among others introducing Google Maps for entering addresses, the possibility to adjust earlier entered locations and getting rid of passwords.
Dr Stefan Hubrich (Technische Universität Dresden) - Presenting Author
The household travel survey (HTS) “Mobility in Cities – SrV” has been conducted in 2018 for the eleventh time since 1972. More than 180,000 people have been surveyed in 130 German cities and municipalities concerning their travel behavior. SrV 2018 is a year-long, cross-sectional HTS. Based on a city-specific, stratified random samples that have been selected from the municipalities’ population register. All selected persons report characteristics regarding their household and household members as well as all trips for one complete day. The interviews are completed by telephone or online questionnaires.
This contribution provides an overview of the methodological concept of the survey, followed by a section on fieldwork experience — in particular, on the spatially and temporally differentiated response rates, the distribution of responses among the telephone/online survey methods, possible methodological differences between telephone/online responses, and reasons for losses and refusals. For example, as of today, the proportion of online responders is around 60 percent (fieldwork is still ongoing until 02/2019). This represents a further significant increase of online participation compared to the last survey wave in 2013 (43 percent). Furthermore, this current survey is the first to be made available in five languages, providing new experiences addressed in this contribution.
Dr Marcelo Simas (Westat) - Presenting Author
Mr Alexander Cates (Westat)
Mr Anthony Fucci (Westat)
Starting in late 2016, Westat has been integrating smartphone Android and iOS apps that automatically collect GPS traces in all of its household travel surveys. The main motivation for using smartphone apps is to reduce travel underreporting by providing participants a list of the detected stops on their travel date for which the user can then confirm and provide details. As such, these apps fulfill the role that had since the early 2000s been provided by dedicated GPS data loggers. The design of these early GPS-enhanced travel surveys often included randomly pre-selecting a portion of the sample to participate in the GPS sub-sample. Furthermore, the way in which Westat has integrated these smartphone apps into our travel surveys makes it possible for participants to start reporting on the app and then later conclude their participation either via the web or on the phone. Because Westat’s approach to using smartphone apps relies on participants using their own devices, a decision was made not to pre-select households for app use, but instead offer participation by app to all age-qualifying (13+ years) household members. This makes it possible to have “mixed” households in the sample, where only some of the age-qualifying persons use the smartphone apps. This presentation examines sample percentages and socio-demographic characteristics of participants (from both complete and partial households) from six regional US travel surveys, which have recently concluded or in are in the process of concluding. We also review the characteristics of participants who start to use the app and fall into the following groups: complete reporting on the app, complete reporting on the web, or complete reporting over the phone. Finally, we compare both the socio-demographic and travel aspects of complete households and persons who use the app versus
Dr Marcelo Simas (Westat)
Ms Laura Wilson (Westat) - Presenting Author
Over the past two years Westat has used Android and iOS smartphone apps to collect GPS trace data in household travel surveys in the United States (US). The primary goal of using these apps is to minimize travel under-reporting, a goal that was predominantly fulfilled by deploying dedicated GPS loggers to a subset of households in past household travel surveys. The advanced capabilities of modern smartphones make it possible for the apps to go beyond what GPS loggers could traditionally provide, while reducing cost per household given that there is no need to manage dedicated equipment. The Westat DailyTravel smartphone apps allow interested participants to use their own phones to automatically capture their travel and provide the details of the captured stops directly on the app, using what has been coined in the industry as an “in-the-moment” prompted recall questionnaire. In the US, most travel surveys only capture one day of travel from household members ages five and above, but we also encourage app users to keep collecting travel for a full week. To date, Westat has collected smartphone app data from over seven thousand persons across five regions in the United States. This presentation will detail how these smartphone apps have been integrated into existing household travel surveys’ data collection and processing methodologies as well as detail the challenges that have come along with those changes. More specifically, we will address how we invite participants to use the apps, how we obtain consent from participants, how we provide support to app users, and how we merge the data collected across the various modes (app, web, and telephone). Additionally, we will discuss the new data quality assurance and control challenges that come from having data come in from multiple phones along with responses being provided as participants