Web Survey Bibliography
Being the first chain in the recruiting process, variations of email invitations are known to have a strong impact on response rates and overall performance of online surveys. As different invitation emails lead to different login rates these differences carry on to the end of a survey and affect the overall completion rates (Neubarth, Kaczmirek, Bosnjak, Bandilla & Couper, 2006). Time spent on the construction and design of invitation emails is therefore well spent to ensure an optimal outcome for the whole survey.
Basically three technologies to send out emails may be distinguished. (1) Usually emails are sent in pure text format, i.e. without graphics and the login link visible in its http-format. This corresponds to the actual standard in online survey research. (2) The other two methods use the HTML-format to send out emails. Here, the standard procedure is to store graphics on an external server. When opening the message, the graphics need to be downloaded. As this might be seen as a security breach, graphics are often blocked and need an explicit user action to be shown. Blocked graphics can result in a confusing text layout and might, at best, be ignored. (3) In the third method the pictures themselves are included in the email. Hence, there are no security issues about these graphics and standard email clients display all of them at once.
In a broad series of experiments the effects of the emailing technologies on the re-sponse rate were evaluated. For this purpose the Respondi AG sent out about 18.000 invitation emails, around 6.000 for each of the three techniques stated above. In dif-ferent studies incentives, length of email, the design of the login links and the survey topics were varied among the experiments. Thus, the effect of the email technique could be proven in different frameworks.
The presentation will discuss the strengths and weaknesses of the three stated email techniques. Furthermore, analyses are presented, which point out the effect of each technique on the response rates. In conclusion practical advices on how invitation emails should look like are discussed.
Die Rücklaufquote und der Gesamterfolg einer Online-Umfrage werden bereits durch die Qualität der Einladungs-Mail stark beeinflusst. Unterschiedliche Loginraten auf-grund verschiedener Einladungen setzen sich durch den gesamten Befragungsverlauf bis zum endgültigen Rücklauf fort (Neubarth, Kaczmirek, Bosnjak, Bandilla & Couper, 2006). Daher ist es äußerst wichtig bereits der Einladung einer Umfrage gro-ße Aufmerksamkeit zu widmen. In diesem Beitrag werden experimentell die techni-schen Aspekte beim Mailversand evaluiert.
Für den Versand von E-Mails stehen derzeit im Wesentlichen drei verschiedene Technologien zur Verfügung: (1) Klassisch werden E-Mails in reinem Textformat verschickt. Dies entspricht auch dem aktuellen Standard der Umfrageforschung. (2) Seit einiger Zeit besteht zusätzlich die Möglichkeit E-Mails auch im HTML-Format zu verschicken. Erforderliche Bilder werden dabei von einem externen Server nachge-laden. (3) Eine weitere Variante verschickt ebenfalls HTML-Mails. Hierbei werden die verwendeten Bilder jedoch in die Nachricht eingebunden und müssen daher nicht explizit vom Rezipienten nachgeladen werden. Verbindungen zu weiteren Servern, wie sie von den Standardclients unterbunden werden, sind dabei nicht erforderlich.
In einer umfassenden Experimentalreihe wurde der Einfluss der Mailtechnik auf die Rücklaufquote überprüft. Die Respondi AG verschickte zu diesem Zweck insgesamt ca. 18000 Einladungen, davon jeweils etwa 6000 für jede der drei oben genannten Techniken. Die verschiedenen Studien unterschieden sich außerdem hinsichtlich In-centives, Maillängen, unterschiedlich gestalteter Zugangslinks und letztlich auch in den Umfragethemen. Durch diese Variation weiterer Einflussgrößen, musste sich der Effekt der E-Mail-Technik auf den Rücklauf unter verschiedenen Rahmenbedingun-gen bewähren.
Unser Beitrag erörtert die positiven und negativen Effekte der drei genannten Techni-ken. Weiterhin werden Analysen vorgestellt, die zeigen, wie sich die Rücklaufquote durch den Einsatz der einzelnen Technologien verändert. Im Anschluss werden prak-tische Ratschläge zur Gestaltung von Einladungs-Mails diskutiert.
German Online Research Conference (GOR) 2007 (abstract)
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- 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.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- 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.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- 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.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- 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.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- 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.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- 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.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- 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.