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.
GOR Homepage (abstract) / (presentation)
Web survey bibliography - General Online Research Conference (GOR) 2013 (34)
- Respondent Rewards: Money for Nothing?; 2013; Martin, P.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- The fish model: What factors affect participants while filling in an online questionnaire?; 2013; Mohamed, B., Lorenz, A., Pscheida, D.
- Interview Duration in Web Surveys: Integrating Different Levels of Explanation; 2013; Rossmann, J., Gummer, T.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Technical and methodological meta-information on current practices in online research: A full population...; 2013; Burger, C., Stieger, S.
- Using interactive feedback to enhance response quality in Web surveys. The case of open-ended questions...; 2013; Emde, M., Fuchs, M.
- Reducing Response Order Effects in Check-All-That-Apply Questions by Use of Dynamic Tooltip Instructions...; 2013; Kunz, T., Fuchs, M.
- 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.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- Research Design as an Influencing Factor for Reliability in Online Market Research; 2013; Wengrzik, J., Theuner, G.
- Ethics, privacy and data security in web-based course evaluation; 2013; Salaschek, M., Meese, C., Thielsch, M.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- Influence of mobile devices in online surveys; 2013; Maxl, E., Baumgartner, T.
- 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.
- Online Survey – Research with children on advertising impact; 2013; Funkenweh, V., Busch, J., Amthor, A. L., Boeer, A., Gaedke, J.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- 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.