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 - Other (451)
- Cell Phone Mainly Households: Coverage and Reach for Telephone Surveys Using RDD Landline Samples; 2009; Boyle, J., Lewis, F., Tefft, B.
- Cell-Phone-Only Voters in the 2008 Exit Poll and Implications for Future Noncoverage Bias ; 2009; Mokrzycki, M., Keeter, S., Kennedy, C.
- Zero Banks: Coverage Error and Bias in Rdd Samples Based on Hundred Banks with Listed Numbers ; 2009; Boyle, J., Bucuvalas, M., Piekarski, L., Weiss, A.
- National Surveys Via RDD Telephone Interviewing vs. the Internet: Comparing Sample Representativeness...; 2009; Chang, L. C., Krosnick, J. A.
- Internet experiments: methods, guidelines, metadata; 2009; Reips, U. -D.
- Effects of incentives and the Big Five personality dimensions on internet panellists' ratings; 2009; Larson, A. J., Sachau, D. A.
- Best practices in mobile research; 2009; Zahariev, M., Ferneyhough, C., Ryan, C.
- Mobile interviewing; 2009; Lavine, S.
- Web 2.0: Transformational technology or pretty gradients and hype?; 2009; August, S., Ewing, T., Hamelle, A., Ryan, L.
- Innovative online research: The US presidential campaign of Barack Obama case study; 2009; Riley, R.
- A comparison of web-based and telephone surveys for assessing traffic safety concerns, beliefs, and...; 2009; Beck, K. H., Yan, A. F., Qi Wang, M.
- Design of Web Questionnaires: The Effect of Layout in Rating Scales; 2009; Toepoel, V., Das, M., van Soest, A.
- The Impact of Textual Messages of Encouragement on Web Survey Breakoffs: An Experiment ; 2009; Sakshaug, J. W., Crawford, S. D.
- The Coverage Bias of Mobile Web Surveys Across European Countries ; 2009; Fuchs, M., Busse, B.
- Item non-response rates: a comparison of online and paper questionnaires ; 2009; Denscombe, M.
- Young people, the Internet and Political Participation: Findings of a web survey in Italy, Spain and...; 2009; Calenda, D., Meijer, A.
- Using mobile phones for survey research A comparison with fixed phones ; 2009; Vicente, P., Reis, E., Santos, R.
- A Comparison of Different Survey Periods in Online Surveys of Persons with Eating Disorders and Their...; 2009; Wesemann, D., Grunwald, A., Grunwald, M.
- A Comparison of Web-Based and Paper-Based Survey Methods Testing Assumptions of Survey Mode and Response...; 2009; Greenlaw, C., Brown-Welty, S.
- Interactivity in self-administered surveys. Influence on respondents' experience; 2009; Suarez Vazquez, A., Garcia Rodriguez, N., Alvarez, M. B.
- Selecting techniques for use in an internet survey; 2009; B., Han, V., Albaum, G., Thirkell, P.Wiley, J. B.
- Designing Effective Web Survey Forms; 2009; Mitchell, J.
- Web based macroseismic survey: fast information exchange and elaboration of seismic intensity effects...; 2009; De Rubeis, V., Sbarra P., Sorrentino, D., Tosi, P.
- The Effects of the Initial Mode of Contact on the Response Rate and Data Quality in an Internet-Based...; 2009; Wiseman, F.
- Internet-based surveys and urban design education: A community outreach graduate project in Redding,...; 2009; del Rio, V., Levi, D.
- An experimental mixed mode design on a general population survey ; 2009; Eva, G.
- Declining Working Phone Rates Impact Sample Efficiency; 2009; Piekarski, L.
- Using Non-Probability Samples for Confusion Surveys - Mall Intercepts and the Internet; 2009; Ericksen, E. P.
- Using Debit Cards for Incentive Payments: Experiences of a Weekly Survey Study; 2009; Gatny, H. H., Couper, M. P., Axinn, W., Barber, J. S.
- Characteristics of Cell Phone Only, Listed, and Unlisted Telephone Households; 2009; Tarnai, J., , Schultz, R.Moore, D.
- Cell Phone-Only Households: A Good Target for Internet Surveys?; 2009; Bates, N.
- Nonsampling Error Research in Practice; 2009; Brick, J. M., Kalton, G.
- Metrics for panel contribution: a non probabilistic platform; 2009; Gittelmam, S. H., Trimarchi, E.
- Relation between values and topic of a survey in internet panel research; 2009; Vis, C., Marchand, M.
- The potential of mobile research: Implications for the future and the role of industry standards; 2009; Nelson, L.
- Lottery Style Incentives and Response Rates to Online Surveys; 2009; Pearson, J., E., Krosnick, J. A.Levine, R. E.
- Factors Contributing to Participation in Web‐based Surveys among Italian University Graduates; 2009; Cimini, C., Girottu, C., Gasperoni, G.
- Integration of different data collection techniques using the propensity score; 2009; Camillo, F., Conti, V., Ghiselli, S.
- The mixing of survey modes: application to Laon web and face‐to‐face household travel survey...; 2009; Bayart, C., Bonnel, P.
- Reason analysis: an ambitious alternative for mixed‐mode survey design; 2009; Jeøábek, H.
- Unit non‐response in panel surveys: empirical finding from an experiment; 2009; Haunberger, S.
- Do cash incentives helps with RDD studies? Examination of results from a national and a statewide survey...; 2009; Miller, Y., Barger, K., Hearn, D.
- The Potential of a Multi-mode Data Collection Design to Reduce non-response bias. The Case of a Survey...; 2009; Sala, E., Lynn, P.
- Are people sharing their mobile phones? Selection probabilities in cellular telephone surveys; 2009; Fuchs, M., Busse, B.
- Improving Response Rates in Online Business Surveys by Using CATI; 2009; Höglinger, M., Abraham, M., Arpagaus, J.
- Survey cooperation: response to initial and follow-up requests - Recent experiences from the recruitment...; 2009; Bartsch, S., Engel, U., Schnabel, C., Vehre, H.
- Using Mobile Phones to Administer a Working Memory Updating Task in a Survey - Cognitive Performance...; 2009; Schmiedek, F., Riediger, M., Lindenberger, U., Wagner, G. G.
- Accessibility of individuals for mobile phone surveys; 2009; Gabler, S., Häder, S.
- Mixed Modes and Measurement Error: Comparing face-to-face, telephone and web modes ; 2009; Hope, S., Nicolaas, G., Jäckle, A., Lynn, P., Nandi, A., Campanelli, P.
- The Presentation of a Web Survey, Nonresponse and Measurement Error among Members of Web Panel; 2009; Tourangeau, R., Groves, R. M., Kennedy, C., Yan, T.