Web Survey Bibliography
The main objective of the presentation is to answer the question significant for social survey research why some people participate in a scientific panel survey while others refuse to participate. The so
‐called unit‐nonresponse, i.e. the systematic denial of a person to participate in a scientific survey, might be an important problem in social research, since it can be a crucial source of selective sampling. Meta‐analysis of existing literature on unitnonresponse provide empirical evidence that the empirical analysis of the reasons of unitnonresponse are not driven by testing the theories explaining the individuals’ refuse in participating at a survey but it is based on so‐called ‘variable sociology’. That WAPOR Annual Conference 2009 4 ‐participants have been used to deduce the main reasons for individuals’ unit‐nonresponse in a speculative way. Social decision‐making mechanisms of the respondent’s decisions with some explanation power working behind these distributions thus remain undetected. To answer the central research question, the causes for the participation or non‐participation in surveys have to be uncovered. ‐nonresponse as a result of an individual decision of the respondents. In traditional panel surveys, there is a lack of essential variables explaining the individuals’ participation behaviour; therefore it is necessary to conduct these information in a special research design. ‐mail addresses in order to send the results to them. However, these email addresses has been used to ask the former respondents to participate in an online survey on drug use twice. The actual participation is explained by the previously collected theoretical constructs. The collected data provide following results: At the beginning of a panel survey, considerations of costs (such as fear of data misuse) as well as the factor of the respondent’s currently available time have influences the respondents participation decision. Respondents will take part at the second wave of a panel survey more likely if only a few questions were stressful in the initial wave and, moreover, if the survey topic is of interest for them. These results support the theory of rational action in order to explain unit‐nonresponse. As part of this study on the participation behavior in social science surveys, an experiment was carried out to explore for a mailed questionnaire empirically, whether non‐monetary incentives increases the cooperation of the respondents in an classroom survey and reduces their fear of costs. Therefore, two experiments were carried out. ‐monetary incentives (one 50g Toblerone) had no influence on the cooperation of the respondents, a promised non‐monetary incentive (lottery) leads to the opposite effect. It appeared to be successful for the respondents cooperation, although could not reduce the respondents fear of costs.
means that the distributions of demographic variables of participants and non
One model of participation behavior in social research – the theory of rational action (based on the theory of subjective expected utility) by Esser (1974, 1984, 1986, 1990) – explain the unit
Using an experimental design, the theoretically relevant expectations, evaluations and attitudes toward scientific surveys has been collected. The sample contains about 300 students at the University of Berne (classroom survey; random selection of courses). At the end of the questionnaire, students were asked to provide their e
Students of the first experimental group received the questionnaire combined with a bar of chocolate (here: one 50g Toblerone). Students of the second experimental group were offered the chance to participate in a lottery (here: 2 x 2000g Toblerone). While the use of prepaid non
Conference homepage (abstract)
Web survey bibliography (367)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- 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.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- 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.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Careless Response and Attrition as Sources of Bias in Online Survey Assessments of Personality Traits...; 2017; Meade, A. W.; Ward, M. K.; Alfred, C. M.; Pappalardo, G.; Stoughton, J. W.
- Do Incentives Increase Response Rates to an Internet Survey of American Evaluation Association Members...; 2017; Wilson, L. N.
- Examining Completion Rates in Web Surveys via Over 25,000 Real-World Surveys; 2017; Liu, M.; Wronski, L.
- Data collection mode differences between national face-to-face and web surveys on gender inequality...; 2017; Liu, M.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- An experimental comparison of web-push vs. paper-only survey procedures for conducting an in-depth health...; 2017; McMaster, H. S.; LeardMann, C. A.; Speigle, S.; Dillman, D. A.
- Demographic Question Placement: Effect on Item Response Rates and Means of a Veterans Health Administration...; 2017; Teclaw, R.; Price, M.; Osatuke, K.
- Effects of Applying Multimedia and Dialogue Box to Web Survey Design; 2017; Chen, H.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Comparing data quality and cost from three modes of on-board transit surveys ; 2017; Agrawal, A. W.; Granger-Bevan, S.; W.; Newmark, G. L.; Nixon, H.
- Finding and Investigating Geographical Data Online; 2017; Martin, D.; Cockings, S.; Leung, S.
- Three Methods for Occupation Coding Based on Statistical Learning; 2017; Geweon, H.; Schonlau, L.; Blohum, M.; Steiner, St.
- Dynamic Question Ordering in Online Surveys; 2016; Early, K.; Mankoff, J.; Fienberg, S. E.
- How to use online surveys to understand human behaviour concerning window opening in terms of building...; 2016; Fabbri, K.
- Impact of satisficing behavior in online surveys on consumer preference and welfare estimates; 2016; Gao, Z.; House, L. A.; Bi, X.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Can we assess representativeness of cross-national surveys using the education variable?; 2016; Ortmanns, V.; Schneider, S.
- Methodological Aspects of Central Left-Right Scale Placement in a Cross-national Perspective; 2016; Scholz, E.; Zuell, C.
- Fieldwork Effort, Response Rate, and the Distribution of Survey Outcomes: A Multilevel Meta-analysis; 2016; Sturgis, P.; Williams, Jo.; Brunton-Smith, I.; Moore, J.
- Comparison of Face-to-Face and Web Surveys on the Topic of Homosexual Rights; 2016; Liu, M.; Wang, Yic.
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Web-Based Statistical Sampling and Analysis; 2016; Quinn, A.; Larson, K.