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.
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Web Survey Bibliography - Technology (933)
- The Digital Divide: The internet and social inequality in international perspective; 2013; Ragnedda, M., Muschert, G.
- Survey quality prediction system 2.0; 2013
- PDAs in socio-economic surveys: instrument bias, surveyor bias or both?; 2013; Escobal, J., Benites, S.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Computer science security research and human subjects: Emerging considerations for research ethics boards...; 2013; Buchanan, E. A., Aycock, J., Dexter, S., Dittrich, D., Hvizdak, E. E.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Online Survey Software; 2013; Baker, J. D.
- Survey of Cloud Computing; 2013; Furht, B.
- Worldwide online research spending; 2012
- What we can learn from unintentional mobile respondents; 2012; Peterson, G.
- 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 integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The cross platform report. Q2 -2012 - US; 2012
- 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.
- 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
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 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 modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- 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
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Flowing with the mainstream. Is mobile market research finally living up to the hype?; 2012; Townsend, L.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Ebook readings jumps, print book reading declines; 2012; Rainie, L., Duggan, M.
- Digital Divides: A connectivity continuum for the United States. Data from the 2011 Current Population...; 2012; File, T.
- Developments and the impact of smart technology; 2012; Macer, T.
- Better customer in sight in real time; 2012; Macdonald, E., Wilson, H. N., Konus, H.
- Adult gadget ownership over time (2006-2012); 2012
- 28 Questions to Help Buyers of Online Samples; 2012
