Web Survey Bibliography
Relevance & Research Question:
Previous research on clarification features in Web surveys has shown that they are an effective means of improving response quality in open-ended questions. However, little is known about their influence on response quality in closed-ended questions. Results from the literature indicate that respondents use the range and content of response categories as relevant information when generating an answer (scale effects). Given the findings concerning clarification features in open-ended questions we assume (1) that they are similarly effective in closed ended-questions and (2) that they may have a stronger effect on the response process than the range of the response categories potentially reducing scale effects.
Methods & Data:
Experiment 1 and 2 were conducted in two randomized field experimental Web surveys (n=4,620; n=944). Using a between-subjects design we assessed the effectiveness of clarification features in closed-ended frequency questions. Two types of clarification features were tested that aim at either clarifying the question meaning (definitions) or motivating respondents to search their memories for relevant information (motivating statements). Questions and clarification features were designed in a way that respondents in the experimental groups with the clarifications features were expected to provide either higher or lower frequencies than respondents in the control groups with no clarification features.
Experiment 3 was conducted in a randomized field experimental Web survey (n=944). A between-subjects design was implemented in closed-ended questions to test low and high frequency scales without clarification features, with definitions and motivating statements (2 x 3 factorial design). We assessed the magnitude of scale effects as a dependent variable.
Results:
Overall clarification features are effective in influencing responses provided. Results indicate that definitions yield stronger effects than motivating statements. Furthermore, scale effects are lower for respondents receiving clarification features than for respondents of the control group. Again, definitions are more effective in reducing the scale effect than motivating statements.
Added Value:
The use of definitions in closed-ended questions has a positive effect on survey responses and helps improve data quality. Definitions seem to have the potential to counteract scale effects, whereas motivating statements do not show any effect.
Web survey bibliography - Germany (639)
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Who fails and who passes instructed response item attention checks in web surveys?; 2017; Gummer, T.; Rossman, J.; Silber, H.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- Assessing Effects of Mixed-Mode Design in a Longitudinal Household Travel Survey; 2017; Weiss, C.; Chlond, B.; Minster, C.; Joedden, C.; Vortisch, P.
- Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and...; 2017; Ruebsamen, N.; Akmatov, M. K.; Castell, S.; Karch, A.; Mikolajczyk, R. T.
- The Causal Effect of Survey Mode on Students’ Evaluations of Teaching: Empirical Evidence from...; 2017; Treischl, E.; Wolbring, T.
- Mobile Research im Kontext der digitalen Transformation; 2017; Friedrich-Freksa, M.
- Kognitives Pretesting; 2017; Neuert, C.
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Continuity of Web-Survey Completion and Response Behavior; 2017; Karem Hoehne, J.; Schlosser, S.
- Exploring the Influence of Respondents' IT Literacy on Nonresponse in an Online Survey; 2017; Herzing, J. M. E.; Blom, A. G.
- Personalized Feedback in Web Surveys: Does It Affect Respondent Motivation and Data Quality?; 2017; Kuehne, S.; Kroh, M.
- No pay, no gain. The relationship between monetary and non-monetary motivation to participate in web...; 2017; Achimescu, V.; Keusch, F.; Liu, M.
- Understanding mobile respondents and their importance for representative samples: attitudes, behavior...; 2017; Livadic, D.; Badita, M.
- Learning from Mouse Movements: Improving Web Questionnaire and Respondents’ User Experience through...; 2017; Keusch, F.; Brockhaus, S.; Henninger, F.; Horwitz, R.; Kreuter, F.; Schierholz, M.
- Conversational Survey Frontends: How Can Chatbots Improve Online Surveys?; 2017; Harms, C.; Schmidt, S.
- Evaluation of Agree-Disagree Versus Construct-Specific Scales in a Multi-Device Web Survey; 2017; Kunz, T.
- Clarification features in close ended questions and their impact on scale effects; 2017; Metzler, A.; Fuchs, M.
- Focus on mobile surveys: Do the number of scale points and scale order affect rating scale results?; 2017; Kraemer, A.
- Device effects on behaviour and participation in mobile-optimised online diaries; 2017; Heeck, A.; Holdt, C.
- Smartphones as digital companions; 2017; Carolus, A.; Schneider, F.; Muench, R.; Schmidt, C.; Binder, J.
- Browsing vs. Searching – Exploring the influence of consumers’ goal directedness on website...; 2017; Dames, H.
- Determinants of Item Nonresponse in the German Internet Panel; 2017; Burgdorf, K.
- Does the Exposure to an Instructed Response Item Attention Check Affect Response Behavior?; 2017; Gummer, T.; Rossmann, J.; Silber, H.
- How Stable is Satisficing in Online Panel Surveys?; 2017; Rossmann, J.
- The good, the bad and the ugly data: using indicators to get high quality survey respondents from online...; 2017; Althaus, D.
- Searching for Equivalence: An Exploration of the Potential of Online Probing with Examples from National...; 2017; Meitinger, K.
- Read It From My Fingertips – Can Typing Behaviour Help Us to Predict Motivation and Answer Quality...; 2017; Hoermann, M.; Bannert, M.
- Pictures in Online Surveys: To Greet or Avoid?; 2017; Schmid, M.; Batinic, B.
- Asking for Consent to the Collection of Geographical Information; 2017; Felderer, B.; Blom, A. G.
- Comparing cross-cultural cognitive interviews and online probing for the assessment of cross-cultural...; 2017; Adriaans, J.; Weinhardt, M.
- Bayesian Combining of Web Survey Data from Probability- and Non-Probability Samples for Survey Estimation...; 2017; Sakshaug, J. W.; Wisniowski, A.; Perez-Ruiz, D.; Blom, A. G.
- Using In-Context-Testing to drive success of online display marketing; 2017; Schoenherr, S.; Lochstet, M.; Glenz, S.; Sommer, J.
- Mobility behaviour and smartphone usage of Millennials - capturing the moment-of-truth; 2017; Sauermann, J. A.; Einhorn, M.; Loeffler, M.
- Real-time-behavioral in sampling field work: Emotional state of the respondent; 2017; Friedrich-Freksa, M.; Luetters, H.; Vitt, S
- An ethical compass regarding privacy within a digital society; 2017; Prinzig, M.
- The role of privacy concerns and computer self-efficacy in online job applications; 2017; Ulfert, A. S.; Ott, M.; Bachmann, R.
- Analysis of the Ad-tech Industry Using Internet Browsing Data; 2017; Simbeck, K.; Malzahn, B.; Herm, S.
- Mapping the Field of Automated Data Collection in the Web. Data Types, Collection Approaches and their...; 2017; Juenger, J.
- The effect of horizontal and vertical scales on the response behavior when switching to a mobile first...; 2017; Brauch, C.; Blom, A. G.; Burgdorf, K.; John, M.; Keusch, F.
- Article Establishing an Open Probability-Based Mixed-Mode Panel of the General Population in Germany...; 2017; Bosnjak, M.; Dannwolf, T.; Enderle, T.; Schaurer, I.; Struminskaya, B.; Tanner, A.; Weyandt, K.
- Effects of Scale Direction on Response Style of Ordinal Rating Scales; 2017; Liu, M.; Keusch, F.
- Socially Desirable Responding in Web-Based Questionnaires: A Meta-Analytic Review of the Candor Hypothesis...; 2016; Gnambs, T.; Kaspar, K.
- Methodological Aspects of Central Left-Right Scale Placement in a Cross-national Perspective; 2016; Scholz, E.; Zuell, C.
- Predicting and Preventing Break-Offs in Web Surveys; 2016; Mittereder, F.
- Incorporating eye tracking into cognitive interviewing to pretest survey questions; 2016; Neuert, C.; Lenzner, T.
- Geht’s auch mit der Maus? – Eine Methodenstudie zu Online-Befragungen in der Jugendforschung...; 2016; Heim, R.; Konowalczyk, S.; Grgic, M.; Seyda, M.; Burrmann, U.; Rauschenbach, T.
- Using Paradata to Predict and Correct for Panel Attrition; 2016