Web Survey Bibliography
Relevance & Research Question
Internet surveys are by far the fastest and cheapest way to gather data, but longitudinal data are also a rich and valuable source of information for researchers and policy makers. Combining the advantages of the Internet and of longitudinal data collection through panels, Internet panels are increasingly used. Much research has been done about the difficulties to reach people for an Internet panel (Feskens et al., 2006, 2007; Schmeets et al., 2003; Stoop, 2005; Vis & Marchand, 2011). However, these studies mainly focused on background variables such as age, social economic status, marital status and origin. This paper investigates the role different personality characteristics play in Internet panels.
Methods & Data
Our research is conducted in the CentERdata LISS panel, which combines a probability sample and traditional recruitment procedure with online interviewing. The panel consists of about 5000 households representative of the Dutch speaking population. A specialty of this panel is that people without Internet access are provided with the necessary equipment so that they are able to participate in the panel.
Results
To investigate whether people with specific personality characteristics are more inclined to end their panel participation we use data from 2008, 2009 and 2010. More specifically, we look at whether people with specific characteristics of the Big V (measured by the 50 item IPIP questionnaire of Goldberg) are more inclined to leave the panel than others. In addition, we analyzed whether people with different personalities on survey attitude (consisting of items on survey enjoyment, survey value and survey burden) are more likely to stop participating. And finally, we look at the Inclusion of Others in the Self scale (Aron & Aron, 1992), which measures interpersonal closeness (and closeness to the panel).
Added Value
A lot of time, energy, and money is spent on building Internet panels. But what happens after that? This paper focuses on which personality traits play a role in panel attrition to optimize panel quality.
Conference Homepage (abstract) / (presentation)
Web Survey Bibliography - Nonresponse (1914)
- 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.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Do I Have Your Full Attention?; 2013; Cape, P. J.
- Optimizing Surveys for Smartphones: Maximizing Response Rates While Minimizing Bias; 2013; Lattery, K., Park Bartolone, G., Saunders, T.
- Solving the Unintentional Mobile Challenge; 2013; Peterson, G., Mechling, J., LaFrance, J., Ham, G.
- Mobile Research Risk: What Happens to Data Quality When Respondents Use a Mobile Device for a Survey...; 2013; Baker-Prewitt, J.
- Challenges for Researchers Investigating Contraceptive Use and Pregnancy Intentions of Young Women Living...; 2013; Herbert, D. L., Loxton, D., Bateson, D., Weisberg, E., Lucke, J. C.
- 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.
- Addressing Survey Nonresponse Issues: Implications for ATE Principal Investigators, Evaluators, and...; 2013; Welch, W. W., Barlau, A. N.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- Examination of the equivalence of self-report survey-based paper-and-pencil and internet data collection...; 2013; Weigold, A., Weigold, I. K., Russell, E. J.
- An Assessment of Incentive Versus Survey Length Trade-offs in a Web Survey of Radiologists; 2013; Ziegenfuss, J. Y., Niederhauser, B. D., Kallmes, D., Beebe, T. J.
- Using Online and Paper Surveys - The Effectiveness of Mixed-Mode Methodology for Populations Over 50; 2013; De Bernardo, D. H., Curtis, A.
- The monetary value of good questionnaire design; 2013; Tress, F.
- 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.
- 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.
- 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.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- 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.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- 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.
- Mixed-mode including web: Recent developments at Statistics Netherlands; 2013; Luiten, A., Schouten, B.
- Surveys on Mobile Devices: Opportunities and Challenges; 2013; Couper, M. P.
- 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.
- Using Web Survey Panels to Estimate Population Characteristics: A Comparison of Alternative Approaches...; 2013; Rivers, D.
- Online Research, Game On!; 2013; Puleston, J.
- The Design of Grids in Web Surveys; 2013; Couper, M. P., Tourangeau, R., Conrad, F. G., Zhang, C.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Virtual Research Methods; 2013; Hine, C.
