Web Survey Bibliography
Substantial effort is expended in the design of surveys, including the amount and type of information they contain. However, we often do not know how involved respondents are in reading and processing the informational content of a survey and making choices, and whether different levels of involvement result in systematic differences in estimated models. To address this issue, we recorded response times for each respondent of an internet-based choice experiment for stream restoration. Response times per survey section and for the entire survey were used as proxies for the amount of involvement in reading information provided or answering choice questions. Response times per survey section fell rapidly, possibly signaling learning, use of heuristics, or attempts to quickly dispel with the survey. Response times were found to be independent of demographics and attitudes. Log-likelihood ratio tests failed to reject the null hypotheses of equal coefficients and scale parameters across response time-partitioned data. However, there exists an association between response times and the increasing learning curve or difficult choice trade-offs, suggesting a heuristic response. Additional research on response time effects and survey design is needed, especially with the rise in electronic surveying media.
D'énormes efforts sont investis dans la conception de sondages, notamment pour déterminer la quantité et le type d'information présentée. Toutefois, nous ne savons pas combien de temps les répondants consacrent à la lecture et au traitement de cette information et au choix des réponses, ni si les divers degrés de participation entraînent ou non des différences systématiques dans les modèles estimés. Pour s'attaquer à cette question, nous avons chronométré les personnes qui ont répondu à un sondage en ligne sur la restauration des cours d'eau. Nous avons utilisé le temps de réponse pour chaque section et pour le sondage au complet comme mesure approximative de l'effort des participants pour lire l'information et répondre aux questions. Pour chaque section, le temps de réponse diminuait rapidement, soit en raison des connaissances heuristiques des répondants, soit en raison de leur désir d'effectuer le sondage le plus rapidement possible. Le temps de réponse s'est révélé indépendant des caractéristiques démographiques et des attitudes des répondants. Des tests du rapport de vraisemblance n'ont pas rejeté les hypothèses nulles de coefficients égaux et de paramètres d'échelle de l'ensemble des données cloisonnées. Toutefois, il existe un lien entre le temps de réponse et la courbe d'apprentissage croissante ou la difficulté des choix, ce qui laisse supposer une réponse heuristique. Il faudrait effectuer davantage de recherche sur les effets du temps consacré pour répondre à un sondage et pour le concevoir, en raison du nombre croissant de sondages en ligne.
Journal homepage (abstract)
Web survey bibliography (4086)
- Use of Paradata to Manage a Field Data Collection; 2009; Groves, R. M., Axinn, W., Lepkowski, J. M., Kirgis, N., Mosher, W.
- A Systematic Approach to Debugging in the Blaise Environment: An Author's Perspective; 2009; Sparks, P.
- Paradata and Blaise: A Review of Recent Applications and Research; 2009; O’Reilly, J.
- Development of Survey and Case Management facilities for organisations with minimal survey infrastructure...; 2009; Wensing, F.
- Be mindful of cellphone interviews; 2009; Anonymous
- Growth of Mobile-Only Population in the US and its impact on optimal designs; 2009; Srinivasan, R.
- The 'Functionally Mobile-Only' The true extent of coverage problems with landline only samples; 2009; De Keulenaer, F.
- Preference for Mobile Interview Surveys? Interplay of costs, errors and biases; 2009; Vehovar, V., Slavec, A.
- Mode or Mensch?: Respondent sensitivity to mode changes in data collection methods; 2009; McCutcheon, A. L.
- Generation (of) RDD Improving call efficiency of mobile RDD samples; 2009; Husztik, P.
- Flash Eurobarometer Goes Mobile: A practical review; 2009; Hideg, G.
- Are Respondents Sharing their Mobile Phones? Preliminary results based on a mobile phone panel in Germany...; 2009; Fuchs, M.
- Mobilisation: A general overview; 2009; Manchin, R.
- NOM Print Monitor: gereed voor de toekomst!; 2009; Petric, I., Appel, M.
- Asking Factual Knowledge Questions: Reliability in Web-Based, Passive Sampling Surveys ; 2009; Elo, K.
- If You Provide It, Will They Read It? Response Time Effects in a Choice Experiment; 2009; Vista, A. B., Rosenberger, R. S., Collins, A. R.
- Pictures in Web Surveys; 2009; Toepoel, V., Couper, M. P.
- National readership surveys: Moving from probability face-to-face surveys to Internet panels; 2009; Vehovar, V., Slavec, A., Petric, I., Sargac, M.
- Why don’t all Businesses report on Web?; 2009; Haraldsen, G.
- An experiment on the effects of non-response reweighting on estimators' precision in a web survey; 2009; Fabrizi, E., Biffignandi, S., Toninelli, D.
- Dynamic feedback in open-ended questions: Experiments on the visual design language of Web surveys; 2009; Fuchs, M.
- Effects of monetary incentives on participation in a two-wave online survey; 2009; Bandilla, W., Haas, I.
- Response Order and Response Distributions: The Format of the Response Options in a Web Survey; 2009; Tourangeau, R., Conrad, F. G., Couper, M. P., Balter, O.
- Anticipated estimation from a panel Web survey: the case of the presence of tourists in the Province...; 2009; Scaffai, G., Pratesi, M.
- Statistical analysis of on-line courses; 2009; Baelter, O.
- Methodological approaches of Web 2.0; 2009; Neubarth, W.
- Is this e-mail relevant? An eyetracking experiment on how potential respondents read e-mail invitations...; 2009; Kaczmirek, L., Faaß, T., Galesic, M.
- File transfer with built-in editing features; 2009; Erikson, J.
- From paper to internet: Design challenges when mixing modes in longitudinal surveys; 2009; Stax, H.-P., Thomsen, P.
- The Use of Audit Trails in Business Web Surveys; 2009; Snijkers, G., Morren, M.
- Yes, VASs can! Increasing the accuracy of survey measurements with computerized visual analogue scales...; 2009; Funke, F., Reips, U.-D.
- Using Mail Contact to Sample and Encourage Submission of Questionnaire Answers Over the Internet; 2009; Dillman, D. A., Messer, B. L., Millar, M. M.
- Improving the Design of Complex Matrix Questions; 2009; Couper, M. P., Tourangeau, R., Conrad, F. G.
- Use of Web surveys in Official Statistics; 2009; Bethlehem, J.
- Relations between functionality and usability of Web survey software tools: An empirical evaluation; 2009; Berzelak, N., Lozar Manfreda, K.
- Turning Grid Questions into Sequences in Business Web Surveys; 2009; Haraldsen, G., Bergstrøm, Y.
- The Electronic Questionnaire Experience in Business Surveys: mode effects on quality and on response...; 2009; Biffignandi, S., Siesto, G., Zeli, A.
- Reducing Measurement Error in Web Surveys; 2009; Couper, M. P.
- Reducing Measurement Errors in Surveys; 2009; De Leeuw, E. D.
- Mode Effects and Other Potential Biases in Panel-based Internet Surveys: Final Report; 2009; Taylor, P. A., Nelson, N. M., Grandjean, B. D., Anatchkova, B., Aadland, D.
- Findings from consumer surveys on Internet Shopping: A comparison of pre and post study consumer research...; 2009; Anonymous
- Pros and Cons of Internet Surveys Compared to Traditional Survey Methods; 2009; Benjamin, G. D.
- Visual Design Effects on Respondents’ Behavior in Web-Surveys; 2009; Greinoecker, A.
- Using online panels to conduct Web-based research: What works and what doesn’t; 2009; Goeritz, A.
- Balancing the tension between internal and external validity in online intervention research; 2009; Parks-Sheiner, A.
- Ethical Issues in Internet Research ; 2009; McKee, H., Porter, J.
- Making informed technology choices for online research; 2009; Macer, T.
- Practical advice on Internet Research: From Surveys on Social Computing; 2009; Konstan, J. A.
- True Web experiments; 2009; Reips, U.-D.
- Comments on the Articles (3) - Three Key Takeaways from the Zero Bank Debate; 2009; W.Link, M. W.