Web Survey Bibliography
The Internet has recently proved to be a very large place where social phenomena can be surveyed and an environment where powerful data collection tool can be used.
However, research reports have paid little attention to the errors affecting different techniques used within web-based surveys.
This paper discusses such issue by considering both sampling and non-sampling errors.
To reach this aim, the first part presents a preliminary review on the most popular web-based data collection techniques, so as to identify the nature and the features of the errors affecting each technique.
The second part focuses on a particular web-based technique – the observational grid – and discusses the advantages and the limits of its uses within web-based surveys.
The third part compares the performances of the observational grid in opposition to a similar tool – the evaluation grid – within the context of a research on tourist destinations websites quality. In particular, the expected advantages deriving from the use of the “less subjective” tool (the observational grid) are tested with specific reference to the production and the control of sampling and non-sampling errors.
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Web Survey Bibliography (6390)
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Internet use in households and by individual in 2012. Eurostat Statistics in Focus 50/2012; 2012; Seybert, H.
- Internet access - Households and individuals, 2012 part 2; 2012
- Internet access - Households and individuals, 2012; 2012
- Guide to social science data preparation. Best practice throughout the data life cycle; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Global market research 2012; 2012
- Flowing with the mainstream. Is mobile market research finally living up to the hype?; 2012; Townsend, L.
- Explaining rising nonresponse rates in cross-sectional surveys; 2012; Brick, J. M., Williams, D.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Online Surveys 2.0; 2012; Elferink, R.
- The Impact of Academic Sponsorship on Online Survey Dropout Rates; 2012; Allen, P. J., Roberts, L. D.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- Social media as a data collection tool: the impact of Facebook in behavioural research; 2012; Zoppos, E.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Snowball Sampling in Online Social Networks; 2012; Raissi, M., Ackland, R.
- The Use of Facebook as a Locating and Contacting Tool; 2012; McCarthy, T.
- How Often Do You Use the App with a Bird on It? Exploring Differences in Survey Completion Times, Primacy...; 2012; Buskirk, T. D.
- Data quality of questions sensitive to social-desirability bias in web surveys; 2012; Lozar Manfreda, K., Zajc, N., Berzelak, N., Vehovar, V.
- Online Questionnaires: Development of ‘basic requirements’; 2012; Tries, S., Blanke, K.
- Social research in online context: methodological reflections on web surveys from a case study; 2012; Pandolfini, V.
- Efficacy of a health-related Facebook social network site on health-seeking behaviors; 2012; Woolley, P., Peterson, M.
- Methods for eliminating skip statements from questionnaire logic; 2012; Canvanough Spencer, S.
- The war against unengaged online respondents; 2012; Gittelman, S. H., Trimarchi, E.
- Qualitatively Speaking: The five absolute, no-excuse must-dos for online qualitative researchers; 2012; Rossow, A.
- By the Numbers: Lessons for using online panels in B2B research; 2012; Elsner, N.
- Improving Survey Website Usability ; 2012; Vannette, D.
- Specialized Tools for Measuring Past Events ; 2012; Belli, R. F.
- Transparency, Access and the Credibility of Survey Research; 2012; Lupia, A.
- Experience Sampling and Ecological Momentary Assessment; 2012; Stone, A.
- Can Microtargeting Improve Survey Sampling? An Assessment of Accuracy and Bias in Consumer File Marketing...; 2012; Pasek, J.
- Anonymity and Confidentiality; 2012; Tourangeau, R.
- Cognitive Evaluation of Survey Instruments: State of the Science (Art?) and Future Directions; 2012; Willis, G. B.
- Oh, Just One More Thing … Leveraging “Leave-Behinds” in Data Collection; 2012; Link, M. W.
- Can Oﬃcial Records Correct Errors in Turnout Self-reports?; 2012; Berent, M., Krosnick, J. A., Lupia, A.
- Paradata; 2012; Kreuter, F.
- Computation of Survey Weights: Bridging Theory and Practice; 2012; Debell, M.
- Optimizing Response Rates; 2012; Brick, J. M.
- Modes of Data Collection; 2012; Tourangeau, R.
- The Use and Effects of Incentives in Surveys; 2012; Singer, E.
- Probability vs. Non-probability Methods; 2012; Langer, G,
- Improving Question Design to Maximize Reliability and Validity; 2012; Krosnick, J. A.
- Respondent Attrition vs Data Attrition and Their Reduction; 2012; Olsen, R. J.
- Survey Interviewing: Deviations from the Script; 2012; Schaeffer, N. C.
- Sampling for Single and Multi-Mode Surveys using Address-Based Sampling; 2012; O'Muircheartaigh, C.
- What Human Language Technology can do for you (and vice versa); 2012; Liberman, M.
- Proxy Reporting; 2012; Cobb, C. L.
- The Impact of Survery Nonresponse on Survey Accuracy; 2012; Keeter, S.
- How accurate are surveys of objective phenomena?; 2012; Chang, L. C., Krosnick, J. A.