Web Survey Bibliography
Design decisions for Web surveys are restricted by the assumptions about the technologies respondents have available. Measurement problems might occur when fully labeled scales are displayed on small computer screens or when respondents participate via cell phones and other mobile devices such as Netbooks, iPhone, Ipad, or Blackberry. In these cases, the required equidistance of scale points could be violated. Other technologies whose availability are relevant in this context are Flash technology and the respondents‘ connection speed, that are key indicators for successful video presentations, and Java Script which is widely used in automatic data validation procedures. JavaScript is also necessary for all interactive question types such as automatic tally questions or visual analog scales. In the process of designing a survey, the availability of these technologies is then highly relevant for the technical pretest. As pretesting is restricted to the most common combinations of technology, such as specific browsers, mobile devices, and connection speed, it is important to know which combinations really are the most common in the target group. This study provides exactly this data on available technologies for countries with different Internet penetration rates, namely Canada, Denmark, Germany, Hungary, Spain, and the United States (N=480 per country, quotation on age, gender and education). Data was collected automatically, similarly to the collection of paradata, in January 2011 while respondents participated in an Internet survey. The participants were sampled from online access panels. The results provide information about the availability of technology in different demographic groups: How do respondents access online surveys (connection speed, browser, mobile devices)? What technology can survey researchers safely design for (screen size and used window size, Flash, JavaScript)? The study shows that most surveys can use a wide range of design choices, but also that specific groups of respondents need a conservative approach.
Conference Homepage (abstract)
Web survey bibliography (95)
- Virtual reality meets sensory research; 2017; Depoortere, L.
- Methods for Evaluating Respondent Attrition in Web-Based Surveys; 2016; Hochheimer, C. J.; Sabo, R. T.; Krist, A. H.; Day, T.; Cyrus, J.; Woolf, S. H.
- Exploration of Methods for Blending Unconventional Samples with Traditional Probability Samples; 2016; Gellar, J.; Zhou, H.; D.; Sinclair, M. D.
- Ratio of Vector Lengths as an Indicator of Sample Representativeness ; 2016; Shin, H. C.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Validating self-reported mobile phone use in adults using a newly developed smartphone application; 2015; Goedhart, G., Kromhout, H., Wiart, J., Vermeulen, R.
- Innovative Uses of Paradata Across Diverse Contexts ; 2015; Cheung, G.; Pennell, B.-E.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Picking up the Bread Crumbs: Holistic Insights from Social Media; 2014; Souda, P.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- 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.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Doing real time research: Opportunities and challenges; 2013; Back, L., Lury, C., Zimmer, R.
- Digital technology and data collection; 2013; Henriksen, B., Jewitt, C., Price, S., Sakr, M.
- Effects of Self-Awareness on Disclosure During Skype Survey Interviews; 2013; Feuer, S., Schober, M. F.
- Cognitive Interviewing in Online Modes: a Comparison of Data Collected in Second Life and Skype; 2013; Swicegood, J. E., Head, B., Dean, E., Keating, M.
- Effects of Displaying Videos on Measurement in a Web Survey; 2013; Mendelson, J., Gibson, J. L., Romano Bergstrom, J. C.
- Classifying Mouse Movements to Predict Respondent Difficulty; 2013; Horwitz, R.
- Are You Seeing What I am Seeing? Exploring Response Option Visual Design Effects With Eye-Tracking; 2013; Libman, A., Smyth, J. D., Olson, K.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Internet-Mediated Technologies and Mixed Methods Research; Problems and Prospects; 2012; Hesse-Biber, S.; Griffin, A. J.
- An Introduction to Using Video for Research; 2012; Jewitt, C.
- Online Surveys Aren't Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone...; 2012; Buskirk, T. D., Andrus, C.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Specific mixed-mode methodology to reach sensory disabled people in quantitative surveys; 2012; Fontaine, S.
- Facing The Future Webcams as a survey tool in China; 2012; Gordon, A., Llewellyn, T., Gu, E.
- Comfortable in the new medium: How online qual can benefit from our share-happy culture ; 2012; Rubenstein, P.
- Using Collaborative Web Technology to Construct the Health Information National Trends Survey; 2012; Moser, R. P., Beckjord, E. B., Finney Rutten, L. J., Blake, K., Hesse, B. W.
- The Representativity of Web Surveys of the General Population compared to Traditional Modes and Mixed...; 2012; Klausch, L. T., Schouten, B., Hox, J.
- Time use data collection using Smartphones: Results of a pilot study among experienced and inexperienced...; 2012; Scherpenzeel, A., Sonck, N., Fernee, H., Morren, Me.
- Using Webinar Polls to Collect Online Survey Data: The Case of a Behavioral Finance Problem; 2012; Sahu, C.
- The Game Experiments: Researching how gaming techniques can be used to improve the quality of feedback...; 2011; Sleep, D., Puleston, J.
- The benefits and constraints of e-mail interviews and discussions as methods of accessing valid data; 2011; Roberts, An.
- Facial imaging: The new face of online survey research; 2011; Gordon, A., McCallum, D., Sorci, M., Llewellyn, T.
- On Affordances and Technological Intersubjectivity; 2011; Vatrapu, R.
- Building online communities; 2011; Mlačić, B., Milas, G., Mikloušić, I.
- Eye Tracking in testing questionnaires: What’s the added value?; 2011; Tries, S.
- Video enhanced web survey; 2011; Fuchs, M., Kunz, T., Gebhard, F.
- Engagement, Consistency, Reach – why the Technology Landscape Precludes All Three; 2011; Johnson, A., Rolfe, G.
- Twitter mood predicts the stock market.; 2011; Bollen, J., Mao, H., Zeng, X.-J.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- Partnership-Driven Resources to Improve and Enhance Research (PRIMER): A Survey of Community-Engaged...; 2011; Dolor, R. J., Greene, S. M., Thompson, E., Baldwin, L.-M., Neale, A. V.
- Weaving the Web into Personal Communication Networks: A Mobile Phone Based Study of Smartphone Users; 2011; Kobayashi, T., Boase, J.
- Different functioning of rating scale formats – results from psychometric and physiological experiments...; 2011; Koller, M., Salzberger, T.
- Measurement invariance in training evaluation: Old question, new context; 2011; P., Gissel, A., Stoughton, J. W., Whelan, T. J.Clark, A. P.