Web Survey Bibliography
Online panel providers are confronted with an ever-increasing number of technical devices, operating systems and internet browsers with which panel members access the internet and retrieve emails. Mobile devices such as Smartphones offer a wide variety of innovative research designs by means of new participation modes, interview occasions and data sources. This beneficial “intentional” use of mobile devices as data collection mode is counterbalanced by the potential threat to data quality by “unintentional mobile respondents”.
Unintentional mobile respondents participate in a conventional online survey per mobile device. Especially the limitations inherent to Smartphones in terms of display size and data entry comfort raise concerns regarding the usefulness of mobile participations. But a rejection of mobile survey accesses may decrease the accessibility of surveys causing systematic sample biases.
The few empirical studies available do not yield conclusive results regarding the extent of unintentional mobile participations and their impact on data quality. The paper addresses both validity threats and reports results of four studies conducted in the German section of the online panel of Harris Interactive AG.
Based on its results, the paper comes to the conclusion that unintentional mobile respondents do not inevitably threaten the quality of survey results obtained in online panels. In fact, respondents instructed to participate via Smartphone performed as well as participants taking the survey on a PC in nearly all question and response formats on all quality measures. Furthermore, it took mobile respondents considerably more time to complete the interview, they reported a variety of inconveniences, and many of them completed the survey on a PC against the instruction. Given that mobile participation in a conventional HTML web survey a) does not face major technical hurdles any more but is b) still annoying in terms of usability, the paper recommends the implementation of a transparent and fair survey quality management encouraging panel members to balance pros and cons of thorough mobile survey participation.
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Web survey bibliography - 2014 (234)
- The relationship between nonresponse strategies and measurement error; 2014; Malhotra, N., Miller, J. M., Wedeking, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- An empirical test of the impact of smartphones on panel-based online data collection; 2014; Drewes, F.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- A critical review of studies investigating the quality of data obtained with online panels based on...; 2014; Callegaro, M., Villar, A., Yeager, D. S., Krosnick, J. A.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Improving web survey quality; 2014; Steinmetz, S., Bianchi, S. M., Tijdens, K. G., Biffignandi, S.
- WebSM Study: Survey Software in 2014; 2014; Vehovar, V., Cehovin, G., Mocnik, A.
- Design and Implementation of an Online Questionnaire Tool; 2014; Schaniel, R.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- What are the Links in a Web Survey Among Response Time, Quality, and Auto-Evaluation of the Efforts...; 2014; Revilla, M., Ochoa, C.
- Does Age Matter? The Influence of Age on Response Rates in a Mixed-Mode Survey; 2014; Gigliotti, L. M., Dietsch, A.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Comparison of the quality estimates in a mixed-mode and a unimode design: an experiment from the European...; 2014; Revilla, M.
- Forget gamification; try writing a humanized survey; 2014; Pettit, A.
- Using respondent tweets to fill in survey gaps; 2014; Murphy, J.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Evaluating mixed-mode redesign strategies against benchmark surveys: the case of the Crime Victimization...; 2014; Klausch, L. T., Hox, J., Schouten, B.
- 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.