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
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Web survey bibliography (388)
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- 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.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- Enhancing survey participation: Facebook advertisements for recruitment in educational research; 2017; Forgasz, H.; Tan, H.; Leder, G.; McLeod, A.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- “Better do not touch” and other superstitions concerning melanoma: the cross-sectional web...; 2016; Gajda, M.; Kamińska-Winciorek, G.; Wydmański, J.; Tukiendorf, A.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Population Survey Features and Response Rates: A Randomized Experiment; 2016; Guo, Y.; Kopec, J.; Cibere, J.; Li, L. C.; Goldsmith, C. H.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- Can Student Populations in Developing Countries Be Reached by Online Surveys? The Case of the National...; 2016; Langer, A., Meuleman, B., Oshodi, A.-G. T., Schroyens, M.
- How to maximize survey response rates ; 2016; DeVall, R.; Colby, C.
- Impact of Field Period Length and Contact Attempts on Representativeness for Web Survey ; 2016; Bertoni, N.; Turakhia, C.; Magaw, R.; Ackermann, A.
- Have You Taken Your Survey Yet? Optimum Interval for Reminders in Web Panel Surveys ; 2016; Kanitkar, K. N.; Liu, D.
- User Experience and Eye-tracking: Results to Optimize Completion of a Web Survey and Website Design ; 2016; Walton, L.; Ricci, K.; Libman Barry, A.; Eiginger, C.; Christian, L. M.
- A Multi-phase Exploration Into Web-based Panel Respondents: Assessing Differences in Recruitment, Respondents...; 2016; Redlawsk, D.; Rogers, K.; Borie-Holtz, D.
- Exploring the Feasibility of Using Facebook for Surveying Special Interest Populations ; 2016; Lee, C.; Jang, S.
- National Estimates of Sexual Minority Women Alcohol Use through Web Based Respondent Driven Sampling...; 2016; Farrell Middleton, D.; Iachan, R.; Freedner-Maguire, N.; Trocki, K.; Evans, C.
- User Experience Considerations for Contextual Product Surveys on Smartphones ; 2016; Sedley, A.; Mueller, H.
- Web Probing for Question Evaluation: The Effects of Probe Placement ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Berrigan, D.
- Early-bird Incentives: Results From an Experiment to Determine Response Rate and Cost Effects ; 2016; De Santis, J.; Callahan, R.; Marsh, S.; Perez-Johnson, I.
- Effects of an Initial Offering of Multiple Survey Response Options on Response Rates; 2016; Steele, E. A.; Marlar, J.; Allen, L.; Kanitkar, K. N.
- How to Invite? Methods for Increasing Internet Surv ey Response Rate ; 2016; Huang, A. R.; Noel, H.; Hargraves, L.
- Reaching the Mobile Generation: Reducing Web Survey Non-response through SMS Reminders ; 2016; Kanitkar, K. N.; Marlar, J.
- "Don't be Afraid ... We're Researchers!": The Impact of Informal Contact Language...; 2016; Foster, K. N.; Hagemeier, N. E.; Alamain, A. A.; Pack, R.; Sevak, R. J.
- Does Embedding a Survey Question in the Survey Invi tation E-mail Affect Response Rates? Evidence from...; 2016; Vannette, D.
- Communication Channels that Predict and Mediate Self-response ; 2016; Walejko, G. K.
- Ballpoint Pens as Incentives with Mail Questionnaires – Results of a Survey Experiment; 2016; Heise, M.
- Non-Observation Bias in an Address-Register-Based CATI/CAPI Mixed Mode Survey; 2016; Lipps, O.
- Pre-Survey Text Messages (SMS) Improve Participation Rate in an Australian Mobile Telephone Survey:...; 2016; Dal Grande, E.; Chittleborough, C. R.; Campostrini, S.; Dollard, M.; Taylor, A. W.
- Effects of Personalization and Invitation Email Length on Web-Based Survey Response Rates; 2016; Trespalacios, J. H.; Perkins, R. A.
- Assessing targeted approach letters: effects in different modes on response rates, response speed and...; 2016; Lynn, P.
- Refining the Web Response Option in the Multiple Mode Collection of the American Community Survey; 2016; Hughes, T.; Tancreto, J.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- Sample Representation and Substantive Outcomes Using Web With and Without Incentives Compared to Telephone...; 2016; Lipps, O.; Pekari, N.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- “Money Will Solve the Problem”: Testing the Effectiveness of Conditional Incentives for...; 2016; DeCamp, W.; Manierre, M. J.
- Effects of Incentive Amount and Type of Web Survey Response Rates; 2016; Coopersmith, J.; Vogel, L. K.; Bruursema, T.; Feeney, K.
- Effect of a Post-paid Incentive on Response to a Web-based Survey; 2016; Brown, J. A.; Serrato, C. A.; Hugh, M.; Kanter, M. H.; A.; Spritzer, K. L.; Hays, R. D.
- Reminder Effect and Data Usability on Web Questionnaire Survey for University Students; 2016; Oishi, T.; Mori, M.; Takata, E.
- Is One More Reminder Worth It? If So, Pick Up the Phone: Findings from a Web Survey; 2016; Lin-Freeman, L.
- Take the money and run? Redemption of a gift card incentive in a clinician survey. ; 2016; Chen, J. S.; Sprague, B. L.; Klabunde, C. N.; Tosteson, A. N. A.; Bitton, A.; Onega, T.; MacLean, C....
- The effect of email invitation elements on response rate in a web survey within an online community; 2016; Petrovcic, A.; Petric, G.; Lozar Manfreda, K.
- A reliability analysis of Mechanical Turk data; 2016; Rouse, S. V.
- Doing Surveys Online ; 2016; Toepoel, V.
- A Privacy-Friendly Method to Reward Participants of Online-Surveys; 2015; Herfert, M.; Lange, B.; Selzer, A.; Waldmann, U.
- Incentive Types and Amounts in a Web-based Survey of College Students; 2015; Krebs, C.; Planty, M.; Stroop, J.; Berzofsky, M.; Lindquist, C.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.