Web Survey Bibliography
Relevance and Research question: It is well acknowledged within online survey research that Internet surveys are prone to noncoverage error when panelists are not provided with Internet access. However, even Internet users may differ in their ability and comfort with the Internet technology. This may lead to differential willingness to participate in online surveys within the group of Internet users. If respondents differ in their levels of comfort with the Internet technology from nonrespondents, this may result in a biased sample. We study how experience with technology affects the willingness to participate in an online survey and whether respondents to the online questionnaire differ from nonrespondents in levels of technological sophistication.
Methods and Data: The data were collected in telephone recruitment interviews for a probability-based online panel. The landline and mobile telephone interviews were conducted from February to September 2011. In the course of the interview along with demographic information and some attitudinal questions, Internet-usage related questions were asked. Experience with technology, measured via several questions on Internet proficiency and mobile phone ownership and use, is studied as an addition to a framework for unit nonresponse in surveys (Groves & Couper 1998).
Results: It can be shown that those having lower levels of experience with technology are less likely to be willing to join an online panel. Some of the differences stay significant in the selection step of actual online participation. However, no effect of experience with technology can be found on data quality (marginal effect on breakoff and none for item nonresponse).
Added Value: This study implies the importance of respondents’ experiences with technology for nonresponse in various steps of the recruitment process for a panel. Taking this selectivity aspect into account may prove useful for improving recruitment protocols.
GOR Homepage (abstract) / (presentation)
Web Survey Bibliography - Germany (416)
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Cognitive Probes in Web Surveys: On the Effect of Different Text Box Size and Probing Exposure on Response...; 2013; Behr, D., Bandilla, W., Kaczmirek, L., Braun, M.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- The fish model: What factors affect participants while filling in an online questionnaire?; 2013; Mohamed, B., Lorenz, A., Pscheida, D.
- Interview Duration in Web Surveys: Integrating Different Levels of Explanation; 2013; Rossmann, J., Gummer, T.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Technical and methodological meta-information on current practices in online research: A full population...; 2013; Burger, C., Stieger, S.
- Using interactive feedback to enhance response quality in Web surveys. The case of open-ended questions...; 2013; Emde, M., Fuchs, M.
- Reducing Response Order Effects in Check-All-That-Apply Questions by Use of Dynamic Tooltip Instructions...; 2013; Kunz, T., Fuchs, M.
- Slide to ruin data: How slider scales may negatively affect data quality and what to do about it; 2013; Funke, F.
- Measuring wages via a volunteer web survey – a cross-national analysis of item nonresponse; 2013; Steinmetz, S., Annmaria, B.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Blumenstiel, J. E., Rossmann, J.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Online Mixed Mode Surveying using a Responsive Design; 2013; Kissau, K.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Mobile Research Performance: How Mobile Respondents Differ from PC Users Concerning Interview Quality...; 2013; Schmidt, S., Wenzel, O.
- Who responds to website visitor satisfaction surveys?; 2013; Andreadis, I.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Prison break: Releasing offline experiments from methodological constraints by transforming them into...; 2013; Förstel, H., Manthei, K., Mohnen, A., Berger, G.
- Comparison of psychometric properties of internet versions of the Marlowe-Crowne Social Desirability...; 2013; Vesteinsdottir, V., Reips, U. -D., Joinson, A. N., Porsdottir, F.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- Research Design as an Influencing Factor for Reliability in Online Market Research; 2013; Wengrzik, J., Theuner, G.
- Ethics, privacy and data security in web-based course evaluation; 2013; Salaschek, M., Meese, C., Thielsch, M.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- Influence of mobile devices in online surveys; 2013; Maxl, E., Baumgartner, T.
- E-questionnaire in cross-sectional household surveys; 2013; Karaganis, M.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- Online Survey – Research with children on advertising impact; 2013; Funkenweh, V., Busch, J., Amthor, A. L., Boeer, A., Gaedke, J.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- Metadata on the demographics of online research: Results from a full-range study of available online...; 2013; Burger, C., Stieger, S.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- Beyond methodology - some ethical implications of "doing research online"; 2013; Heise, N.
- Innovation in Data Collection: the Responsive Design Approach; 2013; Bianchi, A., Biffignandi, S.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- How Do Lotteries and Study Results Influence Response Behavior in Online Panels?; 2013; Goeritz, A., Luthe, S. C.
- Sample composition discrepancies in different stages of a probability-based online panel; 2013; Bosnjak, M., Haas, I., Galesic, M., Kaczmirek, L., Bandilla, W., Couper, M. P.
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Online Questionnaires: Development of ‘basic requirements’; 2012; Tries, S., Blanke, K.
- Pros and cons of Internet based User Satisfaction Surveys; 2012; Consoli, A., Matsulevits, L.
- Between demand and reality: Ensuring efficiency and quality in pretesting questionnaires; 2012; Sattelberger, S., Blanke, K.
- How to provide high data quality in online-questionnaires: Setting guidelines in design; 2012; Tries, S., Nebel, S., Blanke, K.
- WebSM Study: Survey software features overview ; 2012; Vehovar, V.; Cehovin, G.; Kavcic, L.; Lenar, J.