Web Survey Bibliography
According to a report published in January of 2014 by Pew Research Center, 58% of US adults own a smartphone. Since 2011, smartphone ownership has increased by 23 percentage points. More shockingly, the growth of tablet ownership increased from 3% in 2010 to 42% in 2013. As ownership of these devices increases, it is essential to include these respondents in our samples if the samples are to continue to represent the online population frame. Limited research has been conducted regarding the questionnaire design aspect of online survey research via mobile devices, despite the fact that a growing number of respondents are attempting to take surveys on their mobile devices (Cazes et al. 2011). Previous research suggests that online surveys taken on mobile devices tend to have high drop off rates especially if the survey has not been optimized for mobile devices. In addition, past research demonstrates that respondents who took an online survey via mobile web took longer to complete the survey than those who took the survey using a mobile app or PC web. The most recent contribution to this research was by Nielsen and NPD Group (2013). These studies observed how respondents took surveys on a smartphone versus on a computer. Smartphone users were administered the survey via a survey app which was programmed for all the major smartphone operating systems. Non-smartphone respondents were sent an email invitation containing the survey link to the same questionnaire. The questionnaire contained 24 questions regarding consumer behavior, internet usage and TV viewing habits. Although the questionnaire included short questions and response lists and did not contain any grid type questions, it was not optimized for smartphone web administration. Seven hundred and five respondents completed using the app and 771 complete the survey online. Eighteen percent of respondents who were instructed to take the survey using a PC or laptop completed the survey using a smartphone. In addition, 4.6% of mobile respondents who were instructed to complete the survey via the smartphone app completed the survey using a tablet. Consistent with previous findings, dropout rates were higher among mobile web respondents and mobile app respondents. No significant difference was found between tablet and computer respondents. Findings regarding completion rate were also consistent with previous findings. Mobile web respondents took more time than others to complete the survey. Lastly, the study found no significant differences in item non-response by mode or platform.
Web survey bibliography - Reports, seminars (231)
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2016; 2016
- Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys; 2016
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Establishing the accuracy of online panels for survey research; 2016; Bruggen, E.; van den Brakel, J.; Krosnick, J. A.
- Mixing modes of data collection in Swiss social surveys: Methodological report of the LIVES-FORS mixed...; 2016; Roberts, C.; Joye, D.; Staehli, M. E.
- Assessment of Innovations in Data Collection Technology for Understanding Society; 2016; Couper, M. P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- Evaluating a New Proposal for Detecting Data Falsification in Surveys; 2016; Simmons, K.; Mercer, A. W.; Schwarzer, S.; Courtney, K.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.
- ESOMAR/GRBN Online Research Guideline; 2015
- App vs. Web for Surveys of Smartphone Users: Experimenting with mobile apps for signal-contingent experience...; 2015; McGeeney, K.; Keeter, S.; Igielnik, R.; Smith, A.; Rainie, L.
- On Climbing Stairs Many Steps at a Time: The New Normal in Survey Methodology; 2015; Dillman, D. A.
- Polling Error in the 2015 UK General Election: An Analysis of YouGov’s Pre and Post-Election Polls...; 2015; Wells, A.; Rivers, D.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- Methodology of the RAND Mid-Term 2014 Election Panel; 2015; Carman, K. G; Pollack, S.
- 28 Questions to Help Buyers of Online Samples; 2015; Cape, P. J.; Phillips, A.; Baker, R.; Cooke, M.; Ribeiro, E.; Terhanian, G.
- Understanding Society Innovation Panel Wave 7: Results from Methodological Experiments; 2015; Blom, A. G.; Burton, J.; Booker, C. L.; Cernat, A.; Fairbrother, M.; Jaeckle, A.; Kaminska, O.; Keusch...
- Tips for Creating Web Surveys for Completion on a Mobile Device; 2015; McGeeney, K.
- U.S. Survey Research: Sampling; 2015
- A Comparison of Different Online Sampling Approaches for Generating National Samples; 2014; Heen, M. S. J., Lieberman, J. D., Miethe, T. D.
- FocusVision 2014 Annual MR Technology Report; 2014; Macer, T., Wilson, S.
- The Changing Landscape of Technology and its Effect on Online Survey Data Collection; 2014; Mitchell, N.
- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- The role of email addresses and email contact in encouraging web response in a mixed mode design ; 2014; Cernat, A., Lynn, P.
- Mixed-mode surveys of the general population - Results from the European Social Survey mixed-mode experiment...; 2014; Park, A., Humphrey, A.
- Mixed-Mode Designs bei Erhebungen mit sensitiven Fragen: Einfluss auf das Teilnahme- und Antwortverhalten...; 2014; Krug, G., Kriwy, P., Carstensen, J.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys: Report of the AAPOR...; 2014; Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C.
- The use of within-subject experiments for estimating measurement effects in mixed-mode surveys ; 2014; Klausch, L. T., Schouten, B., Hox, J.
- Measuring well-being: An analysis of different response scales; 2014; van Beuningen, J., van der Houwen, K., Moonen, L.
- The impact of contact effort and interviewer performance on mode-specific nonresponse and measurement...; 2014; Schouten, B., Cobben, F., van der Laan, J., Arends, J.
- Community Life Survey: Summary of web experiment findings; 2013
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Postal recruitment into a longitudinal online panel survey. The effects of different number of reminder...; 2013; Martinsson, J.
- The world in 2013. ICT facts and figures; 2013
- Microsoft Security Intelligence Report, Volume 15; 2013
- A Comparison of Results from a Spanish and English Mail Survey: Effects of Instruction Placement on...; 2013; Wang, K., Sha, M.
- Research Note: Reducing the Threat of Sensitive Questions in Online Surveys?; 2013; Couper, M. P.
- Global market research 2013; 2013
- Exploring the Digital Nation: America’s Emerging Online Experience; 2013
- Advantages of a global multimodal print & digital readership survey; 2013; Cour, N., Saint-Joanis, G.
- Australia: building a 21st century readership survey; 2013; Green, A., White, H.
- The new swiss national readership survey: fit for the future ; 2013; Amschler, H., Hoffmann, J.
- ESS Mixed Mode Experiment Results in Estonia (CAWI and CAPI Mode Sequential Design); 2013; Ainsaar, M., Lilleoja, L., Lumiste, K., Roots, A.
- Using smartphones in survey research: a multifunctional tool Implementation of a time use app; a feasability...; 2013; Sonck, N., Fernee, H.
- Adaptive survey designs to minimize survey mode effects. A case study on the Dutch Labour Force Survey...; 2013; Calinescu, M., Schouten, B.
- Optimal Resource Allocation in Adaptive Survey Designs; 2013; Calinescu, M.