Web Survey Bibliography
The ALMALAUREA Inter
‐university Consortium1 conducts a yearly survey aimed at monitoring the employment opportunities of Italian graduates 1, 3 and 5 years after earning their degree. The survey makes it possible to analyse labour market trends through an examination of university graduates’ career opportunities. The traditional survey carried out via CATI has been integrated during the last few years by use of CAWI survey techniques. This has been made possible by a high and steadily increasing availability of graduates’ e‐mail addresses, which are generally up‐to‐date since they are provided by graduates themselves in their online CVs. Initial uses of CAWI have concerned specific phenomena requiring a short data collection period and low costs. The use of CAWI has become increasingly crucial over time due to the high number of graduates involved in the survey – over 287,000 graduates were interviewed in 2008 – which has mandated a reduction in survey duration and costs. However, in order to achieve the usual, high response rates of ALMALAUREA surveys on employment, CAWI cannot be the only survey technique used. At the moment, in fact, the two survey techniques (CAWI and CATI) coexist in the same survey project. ‐6 weeks each, have produced response rates ranging from 31 to 49 percent. Although the surveys have different characteristics – in terms of topics, question texts, duration of data collection, day of the week and time of day when data collection starts, number of reminders sent, and so on – a preliminary analysis revealed a common trend: the utmost participation of graduates is observed during the first few days immediately after the beginning of the survey itself; afterwards, there is a gradual reduction in participation. Moreover, the contribution given by reminders is valuable and immediate: each time a reminder has been sent there was an increase in the number of questionnaires answered, but they have a limited effect over the course of time. The analysis of response rate trends reveals that the final response rate is particularly connected to the participation rate recorded during the initial days of data collection. ‐selected sample. ‐selection under check by intervening on the most relevant variables.
The frequent use of CAWI over the last few years has determined two needs: firstly, the evaluation of factors that determine the success of the survey in terms of overall participation; secondly, the specification of a model that enables ALMALAUREA to have an ex ante forecast of the final response rate. The analysis presented in this paper will focus on approximately ten CAWI surveys conducted during the last few years. They mostly regard the employment opportunities of graduates one or more years on from graduation. Sometimes ad hoc surveys have also been carried out to explore more specific topics, e.g., graduates’ opinion on interculturalism.
These surveys, which lasted about 3
The first objective of this paper is, therefore, to find a function that calculates the overall response rate achieved during an online survey on the basis of both contextual factors (i.e., the elements that are peculiar to the survey) and individual factors (i.e., the characteristics of the population). Thanks to the wide range of information2 available to ALMALAUREA a preliminary descriptive analysis highlights the fact that respondents of online surveys comprise a self
The second objective of this paper is to develop a logistic regression model in order to identify the variables that most influence graduates’ probability of participating in an online survey and calculate their net effect. In this way it will be possible to maximise the success of the survey and to keep self selection under check by intervening on the most relevant variables.
Conference homepage (abstract)
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.