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 (367)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- 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.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Careless Response and Attrition as Sources of Bias in Online Survey Assessments of Personality Traits...; 2017; Meade, A. W.; Ward, M. K.; Alfred, C. M.; Pappalardo, G.; Stoughton, J. W.
- Do Incentives Increase Response Rates to an Internet Survey of American Evaluation Association Members...; 2017; Wilson, L. N.
- Examining Completion Rates in Web Surveys via Over 25,000 Real-World Surveys; 2017; Liu, M.; Wronski, L.
- Data collection mode differences between national face-to-face and web surveys on gender inequality...; 2017; Liu, M.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- An experimental comparison of web-push vs. paper-only survey procedures for conducting an in-depth health...; 2017; McMaster, H. S.; LeardMann, C. A.; Speigle, S.; Dillman, D. A.
- Demographic Question Placement: Effect on Item Response Rates and Means of a Veterans Health Administration...; 2017; Teclaw, R.; Price, M.; Osatuke, K.
- Effects of Applying Multimedia and Dialogue Box to Web Survey Design; 2017; Chen, H.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Comparing data quality and cost from three modes of on-board transit surveys ; 2017; Agrawal, A. W.; Granger-Bevan, S.; W.; Newmark, G. L.; Nixon, H.
- Finding and Investigating Geographical Data Online; 2017; Martin, D.; Cockings, S.; Leung, S.
- Three Methods for Occupation Coding Based on Statistical Learning; 2017; Geweon, H.; Schonlau, L.; Blohum, M.; Steiner, St.
- Dynamic Question Ordering in Online Surveys; 2016; Early, K.; Mankoff, J.; Fienberg, S. E.
- How to use online surveys to understand human behaviour concerning window opening in terms of building...; 2016; Fabbri, K.
- Impact of satisficing behavior in online surveys on consumer preference and welfare estimates; 2016; Gao, Z.; House, L. A.; Bi, X.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Can we assess representativeness of cross-national surveys using the education variable?; 2016; Ortmanns, V.; Schneider, S.
- Methodological Aspects of Central Left-Right Scale Placement in a Cross-national Perspective; 2016; Scholz, E.; Zuell, C.
- Fieldwork Effort, Response Rate, and the Distribution of Survey Outcomes: A Multilevel Meta-analysis; 2016; Sturgis, P.; Williams, Jo.; Brunton-Smith, I.; Moore, J.
- Comparison of Face-to-Face and Web Surveys on the Topic of Homosexual Rights; 2016; Liu, M.; Wang, Yic.
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Web-Based Statistical Sampling and Analysis; 2016; Quinn, A.; Larson, K.