Web Survey Bibliography
Online panels are becoming the standard choice for researchers today. The temptation to use them is overwhelming as they are a less expensive alternative to traditional telephone and face-to-face research and the results are available sooner. Are they the right choice for all research projects? There is no question that considerable effort is being devoted to building better panels. Commonly, however, the “virtues” of panels are demonstrated not by their intrinsic measurement superiority but by their speed and low cost vis à vis other sampling and data collection modes and/or by deficiencies in other types of surveys (e.g., falling response rates in telephone studies because of consumer avoidance techniques and new technologies masking geography etc as well as the growth in cell-only households). Conversely, online panel research limitations are often overlooked (convenience samples, coverage bias etc.) in favour of cost and timing attributes. As broadband Internet access increases, coverage error and potential bias for online surveys will likely decrease but not eliminated. Market research practitioners and users have long recognized that focus groups or shopping mall intercepts are not suitable tools for answering some types of questions. The same applies to online panels. They have their place in the toolbox but purveyors and users are engaged in an ongoing discussion about which types of questions they are best able to answer. Can they replace studies based on a random sample of respondents within a defined universe in which the probability of selection is known? There remains considerable support for the position that when quantitative estimates such as market shares are required, they should be derived from studies that rely on random probability sampling rather than online panels (Chakrapani,2007) Nonetheless, like other services, newspapers are under increasing pressure to be “with it” (a.k.a. be on the web), to reduce data collection costs (a.k.a. be on the web), and to increase reporting ease and speed (a.k.a. be on the web). Since 1986 newspapers in Canada have relied on traditional telephone data capture techniques to estimate readership of daily papers in major markets, to build profiles of readers and to set market parameters and pricing for advertising. Millions of dollars of advertising revenue depend on readership and profile estimates of how many and who reads specific daily newspapers. How are print media and advertising mavens going to determine when or if to move to online panels? As Canada’s newspaper audience measurement agency, the Newspaper Audience Databank Inc. (NADbank) has been monitoring developments in online panel research for some time. In 2006 the organization embarked on a journey to determine if its annual study could be moved from a modified RDD telephone methodology to a web-based survey. The results of this parallel online survey using the TNS Canadian Facts’ web-access panel in Toronto were reported to this symposium in 2007. The results from the first study showed that the demographic profiles of respondents in the online panel differed from the population as a whole and the telephone sample. As well as demographic differences, there were variations in general media behaviour as well as the primary metric being investigated: readership of daily newspapers. As only one online panel was included in the test, there was no way to assess the extent to which profile differences were a function of idiosyncrasies of the single panel and/or were linked to online panel data capture per se. In the fall of 2007 a second, larger scale study was undertaken to further explore the differences between telephone and online protocols; inter-supplier consistency and the potential use of a web-based survey outside of the Toronto market.
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Web Survey Bibliography (6389)
- Examining the Gender Effects of Different Incentive Amounts in a Web Survey; 2013; Boulianne, S. J.
- Online Survey Software; 2013; Baker, J. D.
- How Do Lotteries and Study Results Influence Response Behavior in Online Panels?; 2013; Goeritz, A., Luthe, S. C.
- Mode Effects in Free-list Elicitation: Comparing Oral, Written, and Web-based Data Collection; 2013; Gravlee, C. C., Bernard, H. R., R., Jacobsohn, A., R.Maxwell, C. R.
- Incentives for college student participation in web-based substance use surveys; 2013; Patrick, M. E., Singer, E., Boyd, C. J., Cranford, J. A., McCabe, S. E.
- The effect of short formative diagnostic web quizzes with minimal feedback; 2013; Baelter, O., Enstroem, E., Klingenberg, B.
- Increasing Web Survey Response Rates in Innovation Research: An Experimental Study of Static and Dynamic...; 2013; Sauermann, H.; Roach, M.
- Sample composition discrepancies in different stages of a probability-based online panel; 2013; Bosnjak, M., Haas, I., Galesic, M., Kaczmirek, L., Bandilla, W., Couper, M. P.
- Survey of Cloud Computing; 2013; Furht, B.
- A comparison of data quality and practicality of online versus postal questionnaires in a sample of...; 2013; King, M. T., Butow, P., Olver, I., Smith, A. B.
- Up Means Good: The Impact of Screen Position on Evaluative Ratings in Web Surveys.; 2013; Tourangeau, R., Conrad, F. G., Couper, M. P.
- WebSM Study: Overview of Features of Software Packages: SurveyMonkey, QuestionPro, FluidSurveys, Wufoo...; 2012; Cehovin, G.; Vehovar, V.
- WebSM Study: Speed and efficiency of online survey tools; 2012; Cehovin, G.; Vehovar, V.
- Worldwide online research spending; 2012
- What we can learn from unintentional mobile respondents; 2012; Peterson, G.
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- 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 practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., Smyth, J. D., Mendez, J.
- The cross platform report. Q2 -2012 - US; 2012
- Speed (necessarily) doesn’t kill: A new way to detect survey satisficing; 2012; Garland, P. et al.
- 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.
- Quality in market research. From theory to practice. 2nd Edition; 2012; Harding, D., Jackson, P.
- 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
- Not just playing around; 2012; Ewing, T.
- Norme di qualita' Assirm (Assirm quality rules]; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 2012
- More dirty little secrets of online panel research.; 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 the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S. et al.
- Measuring modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.

