Web Survey Bibliography
Relevance & Research Question: The intensive use of online survey management tools becomes a common method for data collection. This research identifies key aspects influencing the process of filling in an online questionnaire in order to define what motivates participants to take part in a survey.
Methods & Data: Our metadata is provided by the survey management system Unipark (http://www.unipark.info/). It was collected via online questionnaires of two main related projects (Survey A, n1=140 & Survey B, n2=250) that are running in the frame of the “eScience – Research Network Saxony” project (http://www.escience-sachsen.de/) as well as within a survey run by the central coordination of the project (Survey C n3=765). All projects investigate the usage of Web 2.0 services in terms of an academic task. As a conceptual framework for understanding the scientists’ behaviors, we use the fish model in 4 main dual-related factors as described below (Mohamed, B.; Pscheida, D. & Koehler, T. (2012). The Fish Model: a conceptual framework for enhancing e-research collaboration. (Under reviewing)).
Results: (a) Task-time factor, the main task of filling in an online survey can be splitted into multiple sub tasks (e.g. reading, writing, searching...), these tasks regarding estimated time of filling in, should be considered. (b) Activities-believes: The decision whether or not to take part in and finish an online survey excrete different activities (e.g. communication, breaking up …) which strongly influenced by participants’ beliefs. (c) Support-context: what cultures of disciplines are more aware of Web 2.0 technologies? The disciplines of mathematics-natural science and engineers are clearly winning the subject race for participation. (d) Finally for the Incentive-ethics of what incentives should be provided for participants and protected by ethical research issue? Therefore, the intrinsic motivation of participants was the reason of contribution. Furthermore, the trust issue could drive the process of delivery.
Added Value: The use of the fish model assists our understanding for observing online behaviors of junior and senior scientists during taking part in an online questionnaire. In addition, it provides an approach for how to use meta-data of an online survey to analyze response behavior.
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Web survey bibliography - 2013 (465)
- The role of gamification in better accessing reality and hence increasing data validity ; 2015; Bailey, P.; Kernohan, H.; Pritchard, G.
- Rewarding the Truth; 2015; Puleston, J.
- Tailored fieldwork design to increase representative household survey response: an experiment in the...; 2015; Luiten, A.; Schouten, B.
- Challenges with Online Research for Couples and Families: Evaluating Nonrespondents and the Differential...; 2015; Busby, D. M.; Yoshida, Ke.
- Do Incentives Commoditize Surveys Or Reinforce The Relationship Economy?; 2014; Murphy, L.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Developing an Inclusive Web Survey Design for Respondents with Disabilities; 2013; Jagger, J.; Schaad, A.; Davis, As.; Falcone, A. E.
- The Impact of Survey Communications on Response Rates and Response Quality; 2013; Barlas, F. M.; Falcone, A. E.; Bellamy, N. D.; Mack, A. R.
- The Smartphone Way to Collect Survey Data; 2013; Stapleton, C.
- A Glimpse Inside the Mind of a Respondent: Using Paradata to Improve Online Surveys; 2013; Pape, T.; Barron, S.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Mobile-Mostly Internet Users and Noncoverage in Traditional Web Surveys ; 2013; Antoun, C.; Couper, M. P.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Leuker kunnen wij het wel maken. Online vragenlijst design: standaard matrix of scrollmatrix (We can...; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- A dual-frame sampling methodology to address landline replacement in tobacco control research..; 2013; McMillen, R. C.; Winickoff, J. P.; Wilson, K.; Tanski, S.; Klein, J. D.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Measuring Mobile Phone Use: Self-Report Versus Log Data; 2013; Boase, J., Ling, R.
- How Sliders Bias Survey Data; 2013; Sellers, R.
- Does the first impression count? Examining the effect of the welcome screen design on the response rate...; 2013; Haer, R., Meidert, N.
- Survey Research Response Rates: Internet Technology vs. Snail Mail ; 2013; Lanier, P. A., Tanner, J. R., Totaro, M. W., Gradnigo, G.
- The impact of New Zealand's 2008 prohibition of piperazine-based party pills on young people'...; 2013; Sheridan, J., Dong, C. Y., Butler, R., Barnes, J.
- PRM144 – An adaptable methodology for the design, implementation and conduct of a web-based survey...; 2013; Yeomans, K., Kawata, A. K., Bassel, M., Burk, C. T., Daniels, S. R., Wilcox, T. K.
- The relationships among nurses' job characteristics and attitudes toward web-based continuing learning...; 2013; Chiu, Y.-L., Tsai, C.-C., Fan Chiang, C.-Y.
- Surveillance of patients post-endovascular abdominal aortic aneurysm repair (EVAR). A web-based survey...; 2013; Patel, A., Edwards, R., Chandramohan, S.
- How well do volunteer web panel surveys measure sensitive behaviours in the general population, and...; 2013; Erens, B., Burkill, S., Copas, A., Couper, M. P., Conrad, F.
- Tailoring mode of data collection in longitudinal studies; 2013; Kaminska, O., Lynn, P.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Community Life Survey: Summary of web experiment findings; 2013
- Does Stress Increase the Risk of Atopic Dermatitis in Adolescents? Results of the Korea Youth Risk Behavior...; 2013; Kwon, J. A., Lee, M., Park, E.-C., Park, S., Yoo, K.-B.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- Bringing usability to pretesting of Business Survey Web Forms in Statistics Finland; 2013; Rouhunkoski, J.
- How do we Know Cognitive Interviewing is Any Good?; 2013; Willis, G. B.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- Speeding in Web Surveys: The tendency to answer very fast and its association with straightlining; 2013; Conrad, F. G.; Zhang, Che.
- About the Institute of Public Health - Data aspect; 2013; Zaletel, M.
- Analyzing Paradata to Investigate Measurement Error; 2013; Yan, T., Olson, K.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Can timestamp analyses show the bottlenecks in web surveys?; 2013; Andreadis, I.
- Timing in a web based survey: an influential factor of the response rate; 2013; Paraschiv, D.-C.
- Achieving Synergy Across Survey Modes: Mail Contact and Web Responses from Address-Based Samples; 2013; Dillman, D. A.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Collecting Diary Data on Twitter; 2013; Richards, A., Dean, E., Cook, S.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Sentiment Analysis: Providing Categorical Insight into Unstructured Textual Data; 2013; Haney, C.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.