Web Survey Bibliography
Relevance & Research Question: During the last five years, qualitative online research methods have evolved constantly. However, it is not always clear how the plethora of different methods subsumed under the term “Market Research Online Communities (MROCs)” can be applied optimally. Today online recruitment of participants for MROCs became almost a ubiquity. MROCs are different from offline qualitative research not least because of higher degree of anonymity and absence of face-to-face conversation. This is especially important because similar to offline qualitative research single respondents in MROC-studies can have a huge impact on the quality of the study as such. The question is to what degree single personality traits affect the individual participation behaviour and if the pre-selection of qualitative master data such as personality traits can help the researcher to compose, moderate and analyse MROCs intentionally.
Methods & Data: Our study compares MROCs consisting of exchange and individual 1-on-1 modules in a split-half design, where the single test groups differ in the composition of the participants with regards to their Big Five personality traits (P. Borkenau & F. Ostendorf). Group 1 group consists of participants with average scores dimension of their personality; hence, group 1 is quite homogenous. Group 2 is composed by participants who score extreme values in one of their personality traits; hence, this group is quite heterogeneous. The personal performance on individual tasks will be assessed, as well as the social behaviour within the community. We will also gather a standardized feedback the participants’ experiences after closing the community.
Results: As fieldwork is still not concluded, final results are not available, yet. We expect strong differences in both, the individual level of engagement and the group dynamics.
Added Value: As is it sometimes difficult to engage with MROC participants due to the specific conditions of the internet, it is key for project success to compose communities with right participants. Our case study sheds light on the practical implications for the researcher, when setting up MROCs, and gives best practice examples for qualitative online moderation of different configurations.
Web survey bibliography (4086)
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- The effectiveness of recruitment strategies on general practitioner's survey response rates - a...; 2014; Pit, S. W., Pyakurel, S., Vo, T.
- Respondent-Driven Sampling of Heterosexuals at Increased Risk of HIV Infection; 2014; Batra, P., Gray, S. C., Krishna, N., Prachand, N., Robinson, W. T., Wejnert, C.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- Social desirability is the same in offline, online, and paper surveys: A meta-analysis; 2014; Dodou, D., de Winter J. C. F.
- The impact of contact effort on mode-specific selection and measurement bias; 2014; Schouten, B., van der Laan, J., Cobben, F.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- User-Generated Online Health Content: A Survey of Internet Users in the United Kingdom; 2014; Ziebland, S., Valderas, J., Lupianiez-Villanueva, F., O'Neill, B.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Social Media and Online Survey: Tools for Knowledge Management in Health Research ; 2014; Merolli, M., Sanchez, F. J. M., Gray, K.
- Using Online Social Media for Recruitment of Human Immunodeficiency Virus-Positive Participants: A Cross...; 2014; Yuan, P., Bare, M. G., Johnson, M. O., Saberi, P.
- 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.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- Modelling ”don’t know” responses in rating scales; 2014; Manisera, M., Zuccolotto, P.
- Do Incentives Commoditize Surveys Or Reinforce The Relationship Economy?; 2014; Murphy, L.
- Does Gamification Work? - A Literature Review of Empirical Studies on Gamification ; 2014; Hamari, J., Koivisto, J., Sarsa, H.
- Clicking vs. Dragging: Different Uses of the Mouse and Their Implications for Online Surveys; 2014; Sikkel, D., Steenbergen, R., Gras, S.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- Completion rates and non-response error in online surveys: Comparing sweepstakes and pre-paid cash incentives...; 2014; LaRose, R., Tsai, H. S.
- The accuracy of self-reported medical history: A preliminary analysis of the promise of internet-based...; 2014; Kelstrup, A. M., Juillerat, P., Korzenik, J.
- Panel Attrition - Separating Stayers, Fast Attriters, Gradual Attriters, and Lurkers; 2014; Lugtig, P. J.
- Dropout Rates and Response Times of an Occupation Search Tree in a Web Survey; 2014; Tijdens, K. G.
- The use of within-subject experiments for estimating measurement effects in mixed-mode surveys ; 2014; Klausch, L. T., Schouten, B., Hox, J.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- Improving the Representativeness of Online Surveys ; 2014; Henning, J.
- GESIS Panel: Sample and Recruitment; 2014
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- WEBDATANET: A Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation...; 2014; Tijdens, K. G., Steinmetz, S., de Pedraza, P., Serrano, F.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- The Effect of De-Contextualisation - A Comparison of Response Behaviour in Self-Administered Surveys; 2014; Wetzelhuetter, D.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Mixed-devices in a probability based panel survey. Effects on survey measurement error; 2014; Toepoel, V., Lugtig, P. J.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- Distress Tolerance as a Predictor of Risky and Aggressive Driving; 2014; Beck, K. H., Ali, B., Daughters, S. B.
- African-American breast cancer survivors’ preferences for various types of physical activity interventions...; 2014; Paxton, R., Nayak, P., Taylor, W., Chang, S., Courneya, K., Schover, L., Hodges, K., Jones, L.