Web Survey Bibliography
Relevance & Research Question: Rewards are ubiquitous in online research. In online access panels the type and value of rewards may not be known to the client. It is generally believed that rewards boost response rates. However response rates in online research are simply poor, with or without rewards. The value to the online access panel supplier is economic not methodological. With increased price compression in online sampling it is timely to consider the methodological implications of manipulating reward levels downwards.
Methods & Data: 20 treatments were undertaken; 5 reward levels by 4 interview lengths. Two cases of zero rewards were considered – one, the reward level is simply absent, the other clearly stated 0 points would be given. Matched samples of 2000 per cell were invited to the study. The body of the questionnaire was a battery to measure altruism (Rushton et al), a series of statements relating to attitudes to survey taking and rewards along with perception questions of the rewards on offer.
Results: The results demonstrated only marginal gains in response resulted from substantial increases in rewards levels. E.g. doubling the incentive from $5 to $10 increased response by a mere 14%. This is partly due to the invisibility of rewards. Only 60% thought they knew how much reward they were getting and, of these, only 60% were correct in their estimate. At the same time sample profiles, in terms of distribution of levels of altruism, were unaffected by rewards or interview length. Whilst this holds out promise for reducing rewards spend without impacting response or sample psychographics it does leave as an open question the problem of expectation of rewards – which is being set at the recruitment stage. We may then “get away” with reducing rewards in the short term, it may have a catastrophic long term impact unless we find new ways of recruiting respondents. That itself may have much more far reaching consequences for sample compositions.
Added Value: This paper enables researchers to make informed choices about rewards; not only the impact on response rates but also sample composition over and above demographics.
GOR Homepage (abstract) / (presentation)
Web survey bibliography - Germany (361)
- 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.
- Web-based data collection yielded an additional response bias—but had no direct effect on outcome...; 2012; Mayr, A., Gefeller, O., Prokosch, H.-U., Pirkl, A., Froehlich, A. de Zwaan, M.
- Passive measurement of online data in Practice - A White Paper Wakoopa; 2012
- 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.
- Challenges of assessing the quality of a prerecruited probability-based panel of internet users in...; 2012; Struminskaya, B., Kaczmirek, L.
- Assessing Cross-National Equivalence of Measures of Xenophobia: Evidence from Probing in Web Surveys; 2012; Behr, D., Braun, M., Kaczmirek, L.
- Comparing Ranking Techniques in Web Surveys; 2012; Blasius, J.
- Design of CAWI Instruments for Social Surveys ; 2012; Blanke, K.
- Enhancing Web Surveys With New HTML5 Input Types; 2012; Funke, F.
- The German Internet Panel: First Results from the Recruitment Phases; 2012; Blom, A. G.
- Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data; 2012; Sakshaug, J. W., Kreuter, F.
- Marktforschung mit dem iPad-Panel von Axel Springer Media Impact; 2012
- Effects of Personalized Versus Generic Implementation of an Intra-Organizational Online Survey on Psychological...; 2012; Mueller, K., Straatmann, T., Hattrup, K., Jochum, M.
- Exploring New Pathways to Survey Recruitment; 2012; Bilgram, V., Stadler, D.Jawecki, G.
- Does Mode Matter? Initial Evidence from the German Longitudinal Election Study (GLES); 2012; Blumenstiel, J. E., Rossmann, J.
- Surveytainment 2.0: Why investing 10 more minutes more in constructing your questionnaire is worth considering...; 2012; Muehle, A., Tress, F., Schmidt, S., Winkler, T.
- Market research online community (MROC) versus focus group; 2012; Zuber, M.
- Data quality in MAWI and CAWI; 2012; Mavletova, A. M., Blasius, J.
- Scrutinizing Dynamics – Rolling panel waves in theory and practice; 2012; Faas, T., Blumenberg, J. N.
- Little experience with technology as a cause of nonresponse in online surveys; 2012; Struminskaya, B., Schaurer, I., Kaczmirek, L., Bandilla, W.
- Continuous large-scale volunteer web-surveys: The experience of Lohnspiegel and WageIndicator; 2012; Oez, F.
- Is Pretesting Established Among Online Survey Tool Users?; 2012
- An Evaluation of Two Non-Reactive Web Questionnaire Pretesting Methods; 2012; Lenzner, T.
- High potential for mobile Web surveys: Findings from a survey representative for German Internet users...; 2012; Funke, F., Wachenfeld, A.
- Can Social Media Research replace traditional research methods?; 2012; Faber, T., Einhorn, M., Hofmann, O., Loeffler, M.
- Bad Boy Matrix Question – Whatcha gonna do when they come for you?; 2012; Tress, F.
- Effects of Static versus Dynamic Formatting Instructions for Open-Ended Numerical Questions in Web Surveys...; 2012; Kunz, T., Fuchs, M.
- FamilyVote – Conducting online surveys with children and families; 2012; Geissler, H., Peeters, H.
- Assessing the Quality of Survey Data ; 2012; Blasius, J.
- Exploring Animated Faces Scales in Web Surveys: Drawbacks and Prospects; 2012; Emde, M., Fuchs, M.
- Reminders in Web-Based Data Collection: Increasing Response at the Price of Retention?; 2012; Goeritz, A., Crutzen, R.
- Effects of speeding on satisficing in Mixed-Mode Surveys; 2011; Bathelt, S., Bauknecht, J.
- Mixing modes in the LFS - Computer-assisted, cost effective and respondent friendly; 2011; Koerner, T., van der Valk, J.
- Establishing Cross-National Equivalence of Measures of Xenophobia: Evidence from Probing in Web Surveys...; 2011; Braun, M., Behr, D., Kaczmirek, L.