Web Survey Bibliography
Responsive design approaches to data collection are increasingly common within the survey research community, as they afford planned opportunities to modify aspects of the study design to reduce total survey error and control costs through analysis of paradata (Heeringa and Groves, 2006). Researchers are able identify characteristics of unresponsive sample, apply less passive modes of data collection, and tailor outreach methods that are more appealing to them. Researchers are also able to shift resources away from the more responsive categories to focus on sample members more resistant to completing. This practices raises important questions related to how the increased focus on unresponsive sample categories affects overall response rates and cost to complete ratios. For example, does a tailored approach to specific sample categories lead to an increase in response and, thereby reduce nonresponse bias; if so, does that increase come at a response rate decline in other categories; or raise the overall cost per complete ratio so significantly that the benefits of this approach are not worthwhile? These questions form the bases of our case study and proposed poster. Using paradata from a single mix-mode data collection effort of urban, low- income, high-school students and recent high-school graduates (Web-Telephone-In-person follow-up), we demonstrate how a responsive design approach helped control costs, extend data collection, and reach response rate targets while staying within budget with a particularly hard-to-reach population. Design modifications included adjusting our outreach to accommodate the contact information we received, incentive increases, on -campus completion sessions, individualized mailings, and accessing alumni events. Initial results indicate that shifting efforts toward unresponsive sample categories did raise the response rate in those categories without negatively impacting other categories. Although the cost per complete ratio did increase for unresponsive sample categories, shifting resources created cost savings that enabled an extension of the field effort overall.
Web survey bibliography (305)
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- How to Design a Web Survey Using Spring Boot With MYSQL: a Romanien Network Case Study; 2017; Bucea-Manea-Tonis, Ro.; Bucea-Manea-Tonis, Ra.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Mobile-only web survey respondents; 2016; Lugtig, P. J.; Toepoel, V.; Amin, A.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- Are Initial Respondents Different from the Nonresponse Follow-Up Cases? A Study of Probability-Based...; 2016; Zeng, W.; Dennis, J. M.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Why Do Web Surveys Take Longer on Smartphones?; 2016; Couper, M. P.; J. J.Peterson, G. J.
- Web surveys for offline rural communities ; 2016; Gichohi, B. W.
- 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.
- Short and Sweet? Length and Informative Content of Open-Ended Responses Using SMS as a Research Mode; 2016; Walsh, E.; Brinker, J. K.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences...; 2015; Antoun, C.
- Mobile Research Methods: Opportunities and challenges of mobile research methodologies. ; 2015; Toninelli, D. (Ed.); Pinter, R.; de Pedraza, P.
- Web Surveys Optimized for Smartphones: Are there Differences Between Computer and Smartphone Users?; 2015; Andreadis, I.
- Usability of the ACS Internet Instrument on Mobile Devices; 2015; Horwitz, R.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Emerging Technologies: The Rise of Mobile Devices: From Smartphones to Smart Surveys; 2015; Buskirk, T. D.
- PayPal? An Incentive to Check-out?; 2015; Franklin, J.; Rasmussen, C.; Pruitt, J.; Waller, D.
- Designing Bonsai Surveys: The small but perfectly formed survey experience to meet the needs of the...; 2015; Puleston, J.
- Open narrative questions in PC and smartphones: is the device playing a role?; 2015; Revilla, M.; Ochoa, C.
- Recruiting Respondents for a Mobile Phone Panel: The Impact of Recruitment Question Wording on Cooperation...; 2015; Busse, B.; Fuchs, M.
- Internet Research in Psychology; 2015; Gosling, S. D., Mason, W.
- Are Tailored Outreach Efforts Too Costly? An Assessment of a Responsive Design Approach to Control Costs...; 2015; Epps, S. R.; Getman, D. P.; Hall, L. M.; Hunter, J. A.
- Evaluating Visual Design Elements for Data Collection and Panelist Engagement; 2015; Christian, L. M.; Harm, D.; Langer Tesfaye, C.; Wells, T.
- Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour...; 2015; Liebe, U., Glenk, K., Oehlmann, M., Meyerhoff, J.
- When it comes to mobile respondent experience and data quality, survey design matters; 2014; Mitchell, N.
- The Changing Landscape of Technology and its Effect on Online Survey Data Collection; 2014; Mitchell, N.
- The need of and the demand for completing surveys on mobile devices; 2014; Toninelli, D., Revilla, M., Ochoa, C.
- Survey participation via mobile devices in a probability-based online-panel: Prevalence, determinants...; 2014; Poggio, T., Bosnjak, M., Weyandt, K.
- Keeping Surveys Valid, Reliable, and Useful: A Tutorial; 2014; Greenberg, M. R., Weiner, M. D.
- Improving Response Rates and Questionnaire Design for Mobile Web Surveys; 2014; de Bruijne, M., Wijnant, A.
- Does Survey Mode Still Matter? Findings from a 2010 Multi-Mode Comparison; 2014; Ansolabehere, S., Schaffner, B. F.
- Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys; 2014; Atkeson, L. R.; Adams, A. N.; Alvarez, M. R.
- Do Web surveys facilitate reporting less favourable opinions about law enforcement?; 2014; Boivin, R., Cordeau, G.
- Question Grouping and Matrices in Web Surveys: Using Response and Auxiliary Data to Examine Question...; 2014; Bilgen, I., Stern, M. J.
- The Grouping of Items in Mobile Web Surveys; 2014; Mavletova, A. M., Couper, M. P.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- A Comparison of Results from a Spanish and English Mail Survey: Effects of Instruction Placement on...; 2013; Wang, K., Sha, M.
- Intra-individual variation of extreme response style in mixed-mode panel studies; 2013; Aichholzer, J.