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 (317)
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Respondent mode choice in a smartphone survey ; 2017; Conrad, F. G., Schober, M. F., Antoun, C., Yan, H. Y., Hupp, A., Johnston, M., Ehlen, P., Vickers, L...
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- Stable Relationships, Stable Participation? The Effects of Partnership Dissolution and Changes in Relationship...; 2016; Mueller, B.; Castiglioni, L.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- The 2013 Census Test: Piloting Methods to Reduce 2020 Census Costs; 2016; Walejko, G. K.; Miller, P. V.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- Do Polls Still Work If People Don't Answer Their Phones?; 2016; Edwards-Levy, A.; Jackson, N. M.
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Comprehension and engagement in survey interviews with virtual agents; 2016; Conrad, F. G.; Schober, M. F.; Jans, M.; Orlowski, R. A.; Nielsen, D.; Levenstein, R. M.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Mixed mode surveys ; 2015; Burton, J.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- The impact of contact effort on mode-specific selection and measurement bias; 2014; Schouten, B., van der Laan, J., Cobben, F.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- Advantages of a global multimodal print & digital readership survey; 2013; Cour, N., Saint-Joanis, G.
- Relative Mode Effects on Data Quality in Mixed-Mode Surveys by an Instrumental Variable; 2013; Vannieuwenhuyze, J. T. A., Revilla, M.
- A report on the Confirmit Market Research Software Survey 2013; 2013; Macer, T., Wilson, S.
- Mode effect analysis and adjustment in a split-sample mixed-mode Web/CATI survey; 2013; Kolenikov, S., Kennedy, C.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- Methodological, legal and technical perspectives on the feasibility of web survey paradata in German...; 2013; Sattelberger, S.
- Impact of mode design on reliability in longitudinal data; 2013; Cernat, A.
- Exploring patterns of academic usage: A Google Scholar based study of ESS, EVS, WVS and ISSP academic...; 2013; Malnar, B.
- Web questionnaires in official population surveys: Do's and don'ts First experiments and impacts...; 2013; Blanke, K.
- Mode effects in Labour Force Surveys - do they really matter?; 2013; Koerner, T.
- Measuring the same concepts in several modes in the "BIBB/BAuA-Employee-Survey 2011/12" ; 2013; Gensicke, M., Tschersich, N., Hartmann, J.
- What works? Getting the General Population To Go Online in a Mixed Mode Local Health Survey; 2013; Frigault, L.-R., Azzou, S. A. K., Molloy, E. J. K., Ammarguellat, F., Couture, M., Gratton, J.
- Using Technology to Conduct Questionnaire Evaluations with Hard to Reach Populations ; 2013; Ridolfo, H., Ott, K.
- Mode Effects in a National Establishment Survey; 2013; Daley, K., Phillips, B. T.
- Evaluating the Effect of a Non-Monetary Incentive in a Nationally Representative Mixed-Mode Establishment...; 2013; Sengupta, M., Harris-Kojetin, L., Hobbs, M., Greene, A.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- An Evaluation of Internet Versus Paper-based Methods for Public Participation Geographic Information...; 2012; Pocewicz, A.; Nielsen-Pincus, M.; Brown, G.; Schnitzer, R.
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Specialized Tools for Measuring Past Events ; 2012; Belli, R. F.
- Modes of Data Collection; 2012; Tourangeau, R.
- Mode and non-response effects and their treatment; 2012; Chrysanthopoulos, S., Georgostathi, A.
- “I think I know what you did last summer” Improving data quality in panel surveys; 2012; Lugtig, P. J.
- Using Text-to-Speech (TTS) for Audio-CASI; 2012; Couper, M. P., Kirgis, N., Buageila, S., Berglund, P.
- Does Mode Matter? Initial Evidence from the German Longitudinal Election Study (GLES); 2012; Blumenstiel, J. E., Rossmann, J.
- The Representativity of Web Surveys of the General Population compared to Traditional Modes and Mixed...; 2012; Klausch, L. T., Schouten, B., Hox, J.
- Effects of speeding on satisficing in Mixed-Mode Surveys; 2011; Bathelt, S., Bauknecht, J.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- When Referring to Mode, Is Expressed Preference the Same as Reality?; 2011; Denk, K.
- Three Era's of Survey Research; 2011; Groves, R. M.
- Testing a single mode vs a mixed mode design; 2011; Laaksonen, S.