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 (6374)
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Using multivariate statistics, 6th Edition; 2012; Tabachnick, B. G., Fidell, L. S.
- Unintentional mobile respondents; 2012; Peterson, G.
- Tracking preference expression (DNT); 2012
- The smartphone psychology manifesto; 2012; Miller, G.
- The rise of the "connected viewer"; 2012; Smith, A., Boyles, J. L.
- The practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., Smyth, J. D., Mendez, J.
- The cross platform report. Q2 -2012 - US; 2012
- Speed (necessarily) doesn’t kill: A new way to detect survey satisficing; 2012; Garland, P. et al.
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- 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
- Redeveloping the research section of Meningitis UK's website — A case study report; 2012; Witt, J. et al.
- Quality in market research. From theory to practice. 2nd Edition; 2012; Harding, D., Jackson, P.
- Participation of mobile users in traditional online studies; 2012; Jue, A.
- Online survey statistics for the mobile future. Updated with Q3 2012 data; 2012
- Ofcom technology tracker Wave 3; 2012
- Ofcom technology tracker Wave 2; 2012
- Not just playing around; 2012; Ewing, T.
- Norme di qualita' Assirm (Assirm quality rules]; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 2012
- More dirty little secrets of online panel research.; 2012
- Mobile usability; 2012; Nielsen, J., Budiu, R.
- Mobile email opens report 2nd half 2011; 2012
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Media tracker; 2012
- Measuring the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S. et al.
- Measuring modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Internet use in households and by individual in 2012. Eurostat Statistics in Focus 50/2012; 2012; Seybert, H.
- Internet access - Households and individuals, 2012 part 2; 2012
- Internet access - Households and individuals, 2012; 2012
- Guide to social science data preparation. Best practice throughout the data life cycle; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Global market research 2012; 2012
- Flowing with the mainstream. Is mobile market research finally living up to the hype?; 2012; Townsend, L.
- Explaining rising nonresponse rates in cross-sectional surveys; 2012; Brick, J. M., Williams, D.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Online Surveys 2.0; 2012; Elferink, R.
- The Impact of Academic Sponsorship on Online Survey Dropout Rates; 2012; Allen, P. J., Roberts, L. D.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- Social media as a data collection tool: the impact of Facebook in behavioural research; 2012; Zoppos, E.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.