Web Survey Bibliography
Title Effects of motivating question types with graphical support in multi channel design studies
Year 2016
Access date 03.08.2016
Full text PDF(1,54MB)
Abstract
Relevance & Research Questions: More and more participants respond on different mobile devices to questionnaires. Research describes this phenomenon as "unintended mobile participation". The drop-out rate in those studies is higher in mobile studies and the response time is considerably longer making research more expensive. While looking for new approaches in the sphere of HTML5 a joint team of researchers compared the behaviour of mobile and desktop respondents when confronted with modern technology with graphical support compared to a standard HTML questionnaire.
Methods & Data: With the support of a professional panel provider and the market research app of a major german TV company the study integrated more than 800 complete interviews in Germany. The recruiting took plave over three major technical channels: PC Browser, Mobile Browser, an Mobile In-App questionnaire. A control group received classic question types while the experimental group received HTML5 supported questiontypes for the identical questionnaire.
The comparisons included:
- Single Choice (without vs. with graphical support)
- Drop-Down (List vs. Graphical Scaling)
- Sorting Task (Drop-Down vs. Graphical Sorting)
- Price-Sensitivity-Meter (Type-In vs. Graphical)
- Analytic Hierarchy Process (Classic vs. HTML 5)
All elements were designed to be functioning device agnostic on all online devices in the same mechanics.
Results: The HTML5 questionnaire design allows faster responses, lowering the burden of mobile responses resulting in less drop-out. Some of the new question types show deviant result patterns compared to the classic approach of asking. While some of the new question types seem to drive research into a direction of higher validity, other ideas did not meet the expectations of the team looking for ways to interview people on all possible channels.
Added Value: The team is willing to share their findings in the field of mobile browser and In-App research approaches for a world with less problematic questionnaires.
Methods & Data: With the support of a professional panel provider and the market research app of a major german TV company the study integrated more than 800 complete interviews in Germany. The recruiting took plave over three major technical channels: PC Browser, Mobile Browser, an Mobile In-App questionnaire. A control group received classic question types while the experimental group received HTML5 supported questiontypes for the identical questionnaire.
The comparisons included:
- Single Choice (without vs. with graphical support)
- Drop-Down (List vs. Graphical Scaling)
- Sorting Task (Drop-Down vs. Graphical Sorting)
- Price-Sensitivity-Meter (Type-In vs. Graphical)
- Analytic Hierarchy Process (Classic vs. HTML 5)
All elements were designed to be functioning device agnostic on all online devices in the same mechanics.
Results: The HTML5 questionnaire design allows faster responses, lowering the burden of mobile responses resulting in less drop-out. Some of the new question types show deviant result patterns compared to the classic approach of asking. While some of the new question types seem to drive research into a direction of higher validity, other ideas did not meet the expectations of the team looking for ways to interview people on all possible channels.
Added Value: The team is willing to share their findings in the field of mobile browser and In-App research approaches for a world with less problematic questionnaires.
Access/Direct link Conference Homepage (Abstract) / (Full text)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography (364)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Comparing acquiescent and extreme response styles in face-to-face and web surveys; 2017; Liu, M.; Conrad, F. G.; Lee, S.
- Respondent mode choice in a smartphone survey ; 2017; Conrad, F. G., Schober, M. F., Antoun, C., Yan, H. Y., Hupp, A., Johnston, M., Ehlen, P., Vickers, L...
- Effects of Mobile versus PC Web on Survey Response Quality: a Crossover Experiment in a Probability...; 2017; Antoun, C.; Couper, M. P.; G. G.Conrad, F. G.
- Methods for Evaluating Respondent Attrition in Web-Based Surveys; 2016; Hochheimer, C. J.; Sabo, R. T.; Krist, A. H.; Day, T.; Cyrus, J.; Woolf, S. H.
- Mobile-only web survey respondents; 2016; Lugtig, P. J.; Toepoel, V.; Amin, A.
- Using official surveys to reduce bias of estimates from nonrandom samples collected by web surveys; 2016; Beresovsky, V.; Dorfman, A.; Rumcheva, P.
- Making use of Internet interactivity to propose a dynamic presentation of web questionnaires; 2016; Revilla, M.; Ochoa, C.; Turbina, A.
- Helping respondents provide good answers in Web surveys; 2016; Couper, M. P.; Zhang, C.
- Gamifying. Not all fun and games; 2016; Stubington, P.; Crichton, C.
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Are sliders too slick for surveys?; 2016; Buskirk, T. D.
- Research gamification for quality pharmaceutical stakeholder insights; 2016; Mondry, B.; Fink, L.
- SurveyTester from Knowledge Navigators ; 2016; Macer, T.
- Simplifying your mobile solution; 2016; Berry, K.
- Effects of motivating question types with graphical support in multi channel design studies; 2016; Luetters, H.; Friedrich-Freksa, M.; Vitt, SGoldstein, D. G.
- Why Do Web Surveys Take Longer on Smartphones?; 2016; Couper, M. P.; J. J.Peterson, G. J.
- Usability Testing within Agile Process; 2016; Holland, T.
- Association of Eye Tracking with Other Usability Metrics ; 2016; Olmsted, E. L.
- Cognitive Probing Methods in Usability Testing – Pros and Cons; 2016; Nichols, E. M.
- Thinking Inside the Box Visual Design of the Response Box Affects Creative Divergent Thinking in an...; 2016; Mohr, A. H.; Sell, A.; Lindsay, T.
- Distractions: The Incidence and Consequences of Interruptions for Survey Respondents ; 2016; Ansolabehere, S.; Schaffner, B. F.
- The Effect of CATI Questions, Respondents, and Interviewers on Response Time; 2016; Olson, K.; Smyth, J. D.
- New Generation of Online Questionnaires?; 2016; Revilla, M.; Ochoa, C.; Turbina, A.
- The Analysis of Respondent’s Behavior toward Edit Messages in a Web Survey; 2016; Park, Y.
- Effects of Data Collection Mode and Response Entry Device on Survey Response Quality; 2016; Ha, L.; Zhang, Che.; Jiang, W.
- Navigation Buttons in Web-Based Surveys: Respondents’ Preferences Revisited in the Laboratory; 2016; Romano Bergstrom, J. C.; Erdman, C.; Lakhe, S.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- A Technical Guide to Effective and Accessible web Surveys; 2016; Baatard, G.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- A Framework of Incorporating Thai Social Networking Data in Online Marketing Survey; 2016; Jiamthapthaksin, R.; Aung, T. H.; Ratanasawadwat, N.
- Creation and Usability Testing of a Web-Based Pre-Scanning Radiology Patient Safety and History Questionnaire...; 2016; Robinson, T. J.; DuVall, S.; Wiggins III, R
- Comprehension and engagement in survey interviews with virtual agents; 2016; Conrad, F. G.; Schober, M. F.; Jans, M.; Orlowski, R. A.; Nielsen, D.; Levenstein, R. M.
- Taming Big Data: Using App Technology to Study Organizational Behavior on Social Media; 2015; Bail, C. A.
- A Meta-Analysis of Breakoff Rates in Mobile Web Surveys; 2015; Mavletova, A. M.; Couper, M. P.
- Optimizing the Decennial Census for Mobile – A Case Study; 2015; Nichols, E. M.; Hawala, E. O.; Horwitz, R.; Bentley, M.
- Using Video to Reinvigorate the Open Question; 2015; Cape, P.
- Are Sliders Too Slick for Surveys? An Experiment Comparing Slider and Radio Button Scales for Smartphone...; 2015; Aadland, D.; Aalberg, T.
- Web Surveys Optimized for Smartphones: Are there Differences Between Computer and Smartphone Users?; 2015; Andreadis, I.
- Designing web surveys for the multi-device internet; 2015; de Bruijne, M.
- Data Quality Standards in Mixed Mode Surveys; 2015; Bremer, J.; Barbulescu, M.; Bennett, J.
- Changing from CAPI to CAWI in an ongoing household panel - experiences from the German Socio-Economic...; 2015; Schupp, J.; Sassenroth, D.
- Rating Scales in Web Surveys: A Test of New Drag-and-Drop Rating Procedures; 2015; Kunz, T.
- A Review of Issues in Gamified Surveys; 2015; Keusch, F.; Zhang, Che.