Web Survey Bibliography
Relevance & Research Question: Self-administered online surveys put respondents into an essentially anonymous and uncontrolled response situation. This raises worries on potentially biased or uninformative answers, such as nondifferentiation – always using the same score on all items offered – which may harm the measurement accuracy of population statistics. Our presentation explores the question which respondents are inclined to give such answers.
Methods & Data: For our study, longitudinal observations from a large commercial online survey panel in The Netherlands were available: the Appreciation Panel (fieldwork by Intomart GfK on behalf of NPO, the Dutch Public Broadcasting Organisation. Nondifferentiation behavior was identified in every single survey of the panel for a time frame of six months in 2009 (totaling to 502,750 completed online questionnaires). In this way a history of panel (nondifferentiation) behavior was created for each of over 7,700 active panel members. Subsequently a cross-sectional online survey was designed to survey possible determinants of response behavior. The survey was conducted post-hoc with a stratified probability sample of 1,200 respondents.
Results: Analyses based on data from a large-scale online panel indicate that not only respondents’ perception of effort caused by a survey explains their behavior. Also more abstract social behavioral norms, individual moral obligations and the norm of ‘honest behavior’ are related to nondifferentiation behavior. However, extrinsic motivation to participate in the panel because of a monetary incentive is found unrelated. These results imply that survey researchers have somewhat limited ways to reduce the effects of factors causing uninformative behaviors. Using monetary incentives to encourage panel participation is not harmful to the quality of answers, but it is recommended to limit respondents’ perception of effort.
Added Value: Very few examples have been published about nondifferentiation in applied online market research. The method presented offers an example of applied research what respondents are inclined to give nondifferentiated responses and how nondifferentiation in combination with other indicators such as response time is used to identify low quality responses in online research.
Conference Homepage (abstract) / (presentation)
Web Survey Bibliography - Internet access Panels (460)
- 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.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- An approach to selecting online respondents; 2013; Terhanian, G.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- 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.
- Measurement effects in mixed-mode panel surveys; 2013; Lugtig, P. J.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- 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.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S. et al.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- More dirty little secrets of online panel research.; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- The war against unengaged online respondents; 2012; Gittelman, S. H., Trimarchi, E.
- By the Numbers: Lessons for using online panels in B2B research; 2012; Elsner, N.
- Recruiting in an Internet panel using respondent driven sampling; 2012; Schonlau, M.
- Multi-Language Multi-Continent B2B Community Panel: How B2B research can effectively span the world; 2012; Morden, M., Accomando, E.
- WebSM Study: Survey software features overview ; 2012; Vehovar, V.; Cehovin, G.; Kavcic, L.; Lenar, J.
- Web Panels; 2012; Bethlehem, J., Biffignandi, S.
- The Problem of Self-Selection; 2012; Bethlehem, J.,Biffignandi, S.
- Does survey experience affect respondents’ reported level of satisfaction?; 2012; Schultz Christensen, A., Ladenburg, J.
- Evaluation of an online (opt-in) panel for public participation geographic information systems surveys...; 2012; Brown, G., Weber, D., Zanon, D., de Bie, K.
- Panel Conditioning in Online Survey Panels: Problems of Increased Sophistication and Decreased Engagemeent...; 2012; Adams, A. N., Atkeson, L. R., Karp, J. A.
- Surveying Rare Populations Using a Probabilitybased Online Panel; 2012; Peugh, J., Wright, G.
- Recruiting A Probability Sample For An Online Panel: Effects Of Contact Mode, Incentives, And Information...; 2012; Scherpenzeel, A., Toepoel, V.
- Innovation der Online-Datenerhebung für wissenschaftliche Forschungen. Das niederländische MESS-Projekt...; 2012; Das, M.
- “I think I know what you did last summer” Improving data quality in panel surveys; 2012; Lugtig, P. J.
- Understanding Society Innovation Panel Wave 4: Results from Methodological Experiments; 2012; Burton, J., Budd, S., Gilbert, E., Jaeckle, A., Kaminska, O., Uhrig, S.C. N., Brown, M., Calderwood,...
- The Propensity of Older Respondents to Participate in a General Purpose Survey; 2012; Lynn, P.
- Online Data Collection in the Agro-Food Sector; 2012; Biffignandi, S., Artaz, R.
- Time use data collection using Smartphones: Results of a pilot study among experienced and inexperienced...; 2012; Scherpenzeel, A., Sonck, N., Fernee, H.
- Effect of different stimulus on data quality in online panels; 2012; Zagar, S., Lozar Manfreda, K.
- GESIS Online Access Panel Pilot Study: Recruitment and Panel Maintenance; 2012; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.