Web Survey Bibliography
Transportation is an important part of urban policy and precise knowledge about the population’s travel practices is needed in order to develop sustainable transport policies. However, the increasing ‐selection or a selection decision by the study managers. When mixed survey modes are used, individuals choose to belong to one group or another or only respond if the proposed medium suits them. The responses are therefore not comparable, because the sample is no longer random and the presence of respondents is determined by external factors which may also affect the variable of interest in the studied model. This type of selection bias has received considerable coverage in the literature, from both theoretical and empirical standpoints, but as yet little attention has been paid to it with regard to transport surveys. ‐to‐face household travel survey, that is to say individuals who refused to allow an interviewer into their home or who could not be contacted during the first wave of interviews. The results of this survey show that Internet respondents travelled less than the respondents to the face‐to‐face survey. This result subsists even when we limit the socio‐economic differences between the two samples. The comparative analysis is fairly complex as it had to attempt to distinguish between three effects. First, the effect of socioeconomic differences between the Internet respondents and the standard respondents (who answered the face‐to‐face household travel survey), second the effect of any differences in travel between Internet respondents and face‐to‐face respondents, and, third, the effect of differences that were merely due to the survey medium and that did not reflect behavioural differences. It is highly likely that the socioeconomic characteristics and the travel behaviours of the individuals who respond using the Internet are different from those of the individuals who respond to a face‐to‐face interview. To take analysis further, it is necessary to apply econometric techniques that are used for qualitative variables. The sample selection model, whose parameters must be estimated using the two‐stage procedure developed by Heckman provide a promising avenue as, for example, it allows us to isolate the effect on daily travel of socio‐economic differences from that of survey mode. The first stage consists of estimating the survey medium “choice” equation using a probit model. The second stage consists of explaining the differences in travel behaviour using a specific model.
difficulty of obtaining representative data for the target population and the growing complexity of the data that are needed to feed increasingly sophisticated models mean that it is generally not possible to collect all the necessary data in the course of a single survey or with a single method. Combining different data sources has become an extremely important way of increasing knowledge about behaviours and how they are changing as well as improving transport models.
But proposing several data collection modes or methods carries a risk. The collection of information from different sources may provide results that lack comparability. The danger when databases are merged is that a sample selection bias will be created that will compromise the accuracy of explanatory models of travel behaviours. In practice, the selection bias has two sources. It results either from respondent self
The Laboratoire d’Economie des Transports has conducted an Internet survey of no respondents to the 2006 Lyon face
The object of this article is to show that survey mode has an impact on the mobility pattern of respondents. We first present the explanatory variables available for the analysis and estimate an equation of mobility which does not take into account the selection bias. Theoretical developments relative to selection bias follow. Finally, we propose an econometric model that takes into account the selection bias, applied to Lyon household travel survey data.
Conference homepage (abstract)
Web survey bibliography (317)
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Respondent mode choice in a smartphone survey ; 2017; Conrad, F. G., Schober, M. F., Antoun, C., Yan, H. Y., Hupp, A., Johnston, M., Ehlen, P., Vickers, L...
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- Stable Relationships, Stable Participation? The Effects of Partnership Dissolution and Changes in Relationship...; 2016; Mueller, B.; Castiglioni, L.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- The 2013 Census Test: Piloting Methods to Reduce 2020 Census Costs; 2016; Walejko, G. K.; Miller, P. V.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- Do Polls Still Work If People Don't Answer Their Phones?; 2016; Edwards-Levy, A.; Jackson, N. M.
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Comprehension and engagement in survey interviews with virtual agents; 2016; Conrad, F. G.; Schober, M. F.; Jans, M.; Orlowski, R. A.; Nielsen, D.; Levenstein, R. M.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Mixed mode surveys ; 2015; Burton, J.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- The impact of contact effort on mode-specific selection and measurement bias; 2014; Schouten, B., van der Laan, J., Cobben, F.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- Advantages of a global multimodal print & digital readership survey; 2013; Cour, N., Saint-Joanis, G.
- Relative Mode Effects on Data Quality in Mixed-Mode Surveys by an Instrumental Variable; 2013; Vannieuwenhuyze, J. T. A., Revilla, M.
- A report on the Confirmit Market Research Software Survey 2013; 2013; Macer, T., Wilson, S.
- Mode effect analysis and adjustment in a split-sample mixed-mode Web/CATI survey; 2013; Kolenikov, S., Kennedy, C.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- Methodological, legal and technical perspectives on the feasibility of web survey paradata in German...; 2013; Sattelberger, S.
- Impact of mode design on reliability in longitudinal data; 2013; Cernat, A.
- Exploring patterns of academic usage: A Google Scholar based study of ESS, EVS, WVS and ISSP academic...; 2013; Malnar, B.
- Web questionnaires in official population surveys: Do's and don'ts First experiments and impacts...; 2013; Blanke, K.
- Mode effects in Labour Force Surveys - do they really matter?; 2013; Koerner, T.
- Measuring the same concepts in several modes in the "BIBB/BAuA-Employee-Survey 2011/12" ; 2013; Gensicke, M., Tschersich, N., Hartmann, J.
- What works? Getting the General Population To Go Online in a Mixed Mode Local Health Survey; 2013; Frigault, L.-R., Azzou, S. A. K., Molloy, E. J. K., Ammarguellat, F., Couture, M., Gratton, J.
- Using Technology to Conduct Questionnaire Evaluations with Hard to Reach Populations ; 2013; Ridolfo, H., Ott, K.
- Mode Effects in a National Establishment Survey; 2013; Daley, K., Phillips, B. T.
- Evaluating the Effect of a Non-Monetary Incentive in a Nationally Representative Mixed-Mode Establishment...; 2013; Sengupta, M., Harris-Kojetin, L., Hobbs, M., Greene, A.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- An Evaluation of Internet Versus Paper-based Methods for Public Participation Geographic Information...; 2012; Pocewicz, A.; Nielsen-Pincus, M.; Brown, G.; Schnitzer, R.
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Specialized Tools for Measuring Past Events ; 2012; Belli, R. F.
- Modes of Data Collection; 2012; Tourangeau, R.
- Mode and non-response effects and their treatment; 2012; Chrysanthopoulos, S., Georgostathi, A.
- “I think I know what you did last summer” Improving data quality in panel surveys; 2012; Lugtig, P. J.
- Using Text-to-Speech (TTS) for Audio-CASI; 2012; Couper, M. P., Kirgis, N., Buageila, S., Berglund, P.
- Does Mode Matter? Initial Evidence from the German Longitudinal Election Study (GLES); 2012; Blumenstiel, J. E., Rossmann, J.
- The Representativity of Web Surveys of the General Population compared to Traditional Modes and Mixed...; 2012; Klausch, L. T., Schouten, B., Hox, J.
- Effects of speeding on satisficing in Mixed-Mode Surveys; 2011; Bathelt, S., Bauknecht, J.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- When Referring to Mode, Is Expressed Preference the Same as Reality?; 2011; Denk, K.
- Three Era's of Survey Research; 2011; Groves, R. M.
- Testing a single mode vs a mixed mode design; 2011; Laaksonen, S.