Web Survey Bibliography
Relevance & Research Question: Matrix questions are and have always been a big problem in online fieldwork. On the one hand many statistical procedures suggest the use of matrix questions, whilst on the other hand quite a lot of data quality issues are related to matrix questions, - mainly due to satisficing behavior of respondents. One explanation for such a behavior is the high cognitive burden for the respondent when being confronted with the compact presentation of many options and a lot of text on little space. Steps towards a better data quality thus have to find smarter and more intuitive solutions for collecting the needed data. This contribution compares different alternatives for grid questions and shows how to use them in the right context.
Methods & Data: We conducted a study with five splits in total, each of them with a different alternative for the matrix question. Each split contained the respective alternative twice, one time in the context of brand likeability and one time in the context of general attitudes. These concepts have been compared by different metrics in regard to data quality (e.g. variance, time needed on question, consistency with answers in following questions), comparability of the results among these alternatives and the satisfaction of the respondents with usability of each question type. These differences are controlled by sociodemographic factors.
Results: Our results draw a differentiated picture for each of these question types. It seems that there is no universal solution that applies to all contexts. Nonetheless a bunch of recommendations can be drawn for the appropriate design of a questionnaire and the best practice for each of the presented question types.
Added Value: Especially with the growing importance of mobile research in the market research industry, an appropriate questionnaire design gains more and more importance. Smaller screens and new input devices (such as touchscreens) call for alternatives to conventional solutions during fieldwork. We show that researchers most often can count with more satisfied respondents and a better data quality when avoiding the standard matrix question type. Nonetheless they don’t have to do without valuable data.
GOR Homepage (abstract) / (presentation)
Web Survey Bibliography - Online qualitative research (808)
- Should the third reminder be sent? The role of survey response timing on web survey results; 2013; Rao, K., Pennington, J.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson , J.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.
- Using Internet Panel Surveys for Behavioral Health Surveillance; 2013; Gotway Crawford, C., Okoro, C. A., Dhingra, S., Akcin, H., Zhao, G., Ford, D., Pierannunzi, C.
- Proceedings of The 3rd International Conference: Quantitative And Qualitative Methodologies In The Economic...; 2013; Frangos, C. (ed.)
- Social media data demands a marriage of high-tech and high-touch; 2013; Waldheim, C., Stevens, N.
- Leveraging mobile and online qualitative to get inside shoppers’ heads; 2013; Bryson, J., Ritzo, J.
- A report on the Confirmit Market Research Software Survey 2013; 2013; Macer, T., Wilson, S.
- Thoughts on using the new online qualitative tools; 2013; Freund, N. M.
- Web Panel Representativeness; 2013; Bianchi, A., Biffignandi, S.
- Utilization of High-Technology to Collect Health Risk Assessment Information from Medicare Members:...; 2013; Freedman, D., VanderHorst, N.
- Going online with a face-to-face household panel: initial results from an experiment on the Understanding...; 2013; Jaeckle, A., Lynn, P., Burton, J.
- Best of Both Worlds? Can we make convenience samples representative?; 2013; Doe, P.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Insights into Action Profiling shopping occasions for retailers through mobile and online research; 2013; Churkina, O., Morris, T.
- Explaining Interview Duration in Web Surveys on Political Attitudes and Behavior: A Multilevel Approach...; 2013; Gummer, T., Rossmann, J.
- An Examination of the Relationship Between Pretest Method Results and Data Quality; 2013; Maitland, A.
- Avatare in der Marktforschung: Effekte künst-licher Interviewer im Online-Interview; 2013; Luetters, H.
- Möglichkeiten zur impliziten Messung von Emotionen am Beispiel webcambasierter Gesichtsausdruckserkennung...; 2013; Wachenfeld, A., Moentmann, A., Bernet, F.
- Does It Pay Off to Include Non-Internet Households in an Internet Panel? ; 2013; Leenheer, J., Scherpenzeel, A.
- Video Interviewing: An Exploration of the Feasibility as a Mode of Survey Application; 2013; Jeannis, M., Terry, T. L., Heman-Ackah, R., Price, M.
- The 2012 Confirmit Annual Market Research Software Survey; 2013; Macer, T., Wilson, S.
- Data Collection in Sociolinguistics: Methods and Applications; 2013; Mallinson, C., Childs, B., Van Herk, G.
- Survey Sidekick: Learning & designing scientifically sound surveys; 2013; Hsiao, I.-H., Malhotra, M., Joo, J., Chae, H. S., Natriello, G.
- A probability-based web panel for UK policy research: some initial thoughts from a Government survey...; 2013; Littlechild, J.
- Factors Influencing Survey Participation Rates on an Online, Probability-Based Research Panel; 2013; Wiest, D.
- Effects of Self-Awareness on Disclosure During Skype Survey Interviews; 2013; Feuer, S., Schober, M. F.
- Will Snowball Sampling Leave Your Data in the Cold?; 2013; Cavallaro, K.
- Panel Attrition: Separating Stayers, Sleepers and Other Types of Drop-Out in an Internet Panel; 2013; Lugtig, P. J.
- 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.
- Innovative Retention Methods in Panel Research: Can SmartPhones Improve Long-Term Panel Participation...; 2013; Dayton, J. J., Dyer, A.
- Predicting Survey Breakoff in Internet Survey Panels; 2013; Al Baghal, T., McCutcheon, A. L., Tsabutashvili, D.
- Are You Seeing What I am Seeing? Exploring Response Option Visual Design Effects With Eye-Tracking; 2013; Libman, A., Smyth, J. D., Olson, K.
- Evaluating Interactive Feedback in Computer-Assisted Self-Interviewing (CASI); 2013; Hudson, M. L., Hupp, A., Zhang, C., Schroeder, H. M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Using Web Ex to Conduct Usability Testing of an On-Line Survey Instrument; 2013; Stettler, K.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Research Intentions are Nothing without Technology: Mixed-Method Web Surveys and the Coberen Wall of...; 2013; Ganassali, S., Rodriguez-Santos, C.
- Using Web Surveys for Psychology Experiments: A Case Study in New Media Technology for Research; 2013; Peden, B. F., Tiry , A. M.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- Compared to a small, supervised lab experiment, a large, unsupervised web-based experiment on a previously...; 2013; Ryan, R. S., Wilde, M., Crist, S.
- An approach to selecting online respondents; 2013; Terhanian, G.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.