Web Survey Bibliography
Title Regular events in travel behaviour research: setup of a longitudinal websurvey
Source SMABS-EAM Conference 2006
Year 2006
Access date 24.09.2006
Abstract One of the leading paradigms in modern travel behaviour research is the activity based approach, which considers travel as a derivative from the activities that individuals and households need or wish to perform. Longitudinal designs provide the required framework for a better understanding of the dynamics of travel behaviour. Longitudinal data can be used to analyze behavioural adjustments some time before (response leads) or after (response lags) the occurrence of an event, or for instance to analyze routine behaviour.
The questionnaire used to collect the data will be an activity diary. The respondents are asked to fill in all their activities performed that day. The diaries have to be filled in at least twice a week. These moments are randomly selected, but in weeks when a special event occurs, the days around this special event are questioned as well. Performing a longitudinal study has certain drawbacks however. The respondent burden can cause different side-effects, such as panel attrition, decreasing representativeness and, reporting errors. Thus, next to refreshing the sample regularly, trying to keep the respondents motivated is essential.
A first step in lowering the respondent burden is to make the activity diaries user-friendly. An internet-based questionnaire makes interaction with respondents possible. The respondent’s current results can be graphically displayed (e.g. geographical map of activity-pattern), potentially awakening or strengthening the interest in the study. Logical rules (e.g. two activities on two different locations require a trip in between) can be formulated, and the interaction with the respondents allows the researcher to get feedback on “strange” answers, or on missing values, thus improving the data quality.
This paper describes some potential paths to minimise sample attrition (e.g. internet-based interaction with respondents) and ways to refresh the sample. These findings are applied to the study of travel behaviour of Flemish households around school holidays.
The questionnaire used to collect the data will be an activity diary. The respondents are asked to fill in all their activities performed that day. The diaries have to be filled in at least twice a week. These moments are randomly selected, but in weeks when a special event occurs, the days around this special event are questioned as well. Performing a longitudinal study has certain drawbacks however. The respondent burden can cause different side-effects, such as panel attrition, decreasing representativeness and, reporting errors. Thus, next to refreshing the sample regularly, trying to keep the respondents motivated is essential.
A first step in lowering the respondent burden is to make the activity diaries user-friendly. An internet-based questionnaire makes interaction with respondents possible. The respondent’s current results can be graphically displayed (e.g. geographical map of activity-pattern), potentially awakening or strengthening the interest in the study. Logical rules (e.g. two activities on two different locations require a trip in between) can be formulated, and the interaction with the respondents allows the researcher to get feedback on “strange” answers, or on missing values, thus improving the data quality.
This paper describes some potential paths to minimise sample attrition (e.g. internet-based interaction with respondents) and ways to refresh the sample. These findings are applied to the study of travel behaviour of Flemish households around school holidays.
Access/Direct link Conference homepage (abstract)
Year of publication2006
Bibliographic typeConferences, workshops, tutorials, presentations
Full text availabilityNon-existant
Web survey bibliography (4086)
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- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
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- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
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- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
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- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
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- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
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- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.