Web Survey Bibliography
The growth of online survey research over about the last 15 years has been truly remarkable. While estimates vary, most agree that online now accounts for somewhere between one third and one half of the total volume of survey data collection being done by US market research firms (See, for example, ESOMAR, 2009). Key to this growth has been the positioning of online as a faster and less expensive method capable of delivering the same or better survey results as traditional methods (telephone, mail, and in-person). Indeed, online often is the least expensive and fastest survey method for studying
a wide range of business problems, although this speed advantage is clearest when samples sizes are large and/or expected incidence is low. It is less certain that the survey results achieved are comparable to other methods, especially in those cases where one of the objectives is to accurately measure some characteristic, attitude, or behavior in a target population, whether it be a customer base, individuals with certain characteristics, or the general population.
This issue of accuracy is the main focus in this paper. In it we offer a framework for evaluating an online design versus a telephone design when a central goal of the research is to produce an accurate estimate of some personal characteristic,
attitude or behavior in a target population. In this context, accuracy means a survey result that is as close as possible to the “true value” in that population. We recognize that not all research has as its goal the development of accurate estimates of population values.
For example, in some instances directional measures may be sufficient. In others we might only want to test hypotheses about the interrelationships among characteristics, attitudes, and buying behavior. Under these and similar circumstances we might well use different criteria than described below to select a data collection method.
Market Strategies International (abstract) / (full text)
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.