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.
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Web survey bibliography (281)
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys; 2016
- Retrospective Measurement of Students’ Extracurricular Activities with a Self-administered Calendar...; 2016; Furthmueller, P.
- Pitfalls, Potentials, and Ethics of Online Survey Research: LGBTQ and Other Marginalized and Hard-to...; 2016; McInroy, L. B.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- A Statistical Approach to Provide Individualized Privacy for Surveys; 2016; Esponda, F.; Huerta, K.; Guerrero, V. M.
- Social Media Analyses for Social Measurement; 2016; Schober, M. F.; Pasek, J.; Guggenheim, L.; Lampe, C.; Conrad, F. G.
- Doing Surveys Online ; 2016; Toepoel, V.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Utilizing iPads in the Field; 2015; Kiser, P.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- The Web Survey Revolution ; 2015; Murray, D.
- Methodology of the RAND Mid-Term 2014 Election Panel; 2015; Carman, K. G; Pollack, S.
- 28 Questions to Help Buyers of Online Samples; 2015; Cape, P. J.; Phillips, A.; Baker, R.; Cooke, M.; Ribeiro, E.; Terhanian, G.
- Ethical decision-making and Internet research 2.0: Recommendations from the AoIR ethics working committee...; 2015; Markham, A.; Buchanan, E. A.
- Doing online research involving university students with disabilities: Methodological issues; 2015; De Cesarei, A.; Baldaro, B.
- Exploring ethical issues associated with using online surveys in educational research; 2015; Roberts, L. D.; Allen, P. J.
- An Introduction to Survey Research; 2015; Cowles, E. L.; Nelson, E.
- Ethical issues in online research; 2015; James, N.; Busher, H.
- Leading Edge Insights: Foundations of Quality 2.0; 2014; Fuguitt, G.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- Tailoring mode of data collection in longitudinal studies; 2013; Kaminska, O., Lynn, P.
- How do we Know Cognitive Interviewing is Any Good?; 2013; Willis, G. B.
- Quality of Web surveys; 2013; Revilla, M.
- Experiments in Obtaining Data Linkage Consent in Web Surveys ; 2013; Sakshaug, J. W., Kreuter, F.
- Response Burden in Official Business Surveys: Measurement and Reduction Practices of National Statistical...; 2013; Giesen, D., Bavdaz, M., Loefgren, T., Raymond-Blaess, V.
- Internet as a new source of information for the production of official statistics. Experiences of Statistics...; 2013; Heerschap, N.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- How Mobile Stacks Up to Traditional Online: A Comparison of Studies; 2013; Knowles, R.
- How to make your questionnaire mobile-ready; 2013; Cape, P. J.
- Phish Rising: How Internet Criminals are Undermining the Viability of Online Survey Research…and...; 2013; Kunovic, K.
- Self-Reported Participation in Research Practices Among Survey Methodology Researchers; 2013; Perez-Vergara, K., Smith, C., Lowenstein, C., Ozonoff, A., Martins, Y.
- Ethics, privacy and data security in web-based course evaluation; 2013; Salaschek, M., Meese, C., Thielsch, M.
- Beyond methodology - some ethical implications of "doing research online"; 2013; Heise, N.
- Code Comparison; 2012
- Evaluation procedures for Survey questions; 2012; Saris, W. E.
- Transparency, Access and the Credibility of Survey Research; 2012; Lupia, A.
- Anonymity and Confidentiality; 2012; Tourangeau, R.
- Cognitive Evaluation of Survey Instruments: State of the Science (Art?) and Future Directions; 2012; Willis, G. B.
- How to provide high data quality in online-questionnaires: Setting guidelines in design; 2012; Tries, S., Nebel, S., Blanke, K.
- Comparability of Survey Measurements; 2012; Oberski, D.
- Classification of Surveys; 2012; Stoop, I., Harrison, E.
- Enhancing Web Surveys With New HTML5 Input Types; 2012; Funke, F.
- Why one should incorporate the design weights when adjusting for unit nonresponse using response homogeneity...; 2012; Kott, P. S.
- Assessing the Quality of Survey Data ; 2012; Blasius, J.
- Designing and Doing Survey Research; 2012; Andres, L.
- Using break-offs in web interviews for predicting web response in mixed mode surveys; 2011; Beukenhorst, D.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2011; 2011