Web Survey Bibliography
Title Evaluating the Efficacy of Mixed-Mode Intercept Surveys for Complex Questionnaires
Author Puniello, O. T.
Year 2014
Access date 28.08.2014
Abstract
This paper explores mixed-mode intercept survey data collection. The use of intercept surveys is a generally accepted substitute for probability sampling when the study
population cannot be defined. Transportation researchers, in particular, frequently turn to intercept surveys to collect data on public transit riders because those populations are
nearly impossible to define. In an overview study of 52 transit agencies, Schaller (2005), found that difficulty in rider population delimitation compelled the use intercept survey
methods to survey riders in 96% of cases. A 2013 transportation study of the economic benefits of the Prudential Center in Newark, NJ provides the opportunity to test the efficacy of mixed-mode intercept survey data collection. The study required a complex questionnaire that probed respondent travel and spending behavior. Given the cognitive burden of the questionnaire we theorized that providing respondents multiple-modes to complete the questionnaire would increase cooperation. Therefore, the survey protocol allowed a respondent to complete the questionnaire by paper or on the internet. We hypothesized that event participants would respond positively to an internet option because of rapid increase in smartphones, and indeed a number of participants completed the survey at the event on their smartphones. Given this expectation the survey web survey was optimized for viewing on smartphones. However, we are concerned that the mixed-mode data collection for this study would result in significant mode effects. The study examines data collected at three sports/entertainment events at the Prudential Center between October and December 2013 to examine and quantify mode effects. The information from this study will help inform future researchers about the efficacy and appropriateness of mixed-mode data collection in the intercept survey context. Because data collection is still underway, descriptive and analytic results are not yet available.
Access/Direct link
Year of publication2014
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography (4086)
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- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
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- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
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- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
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- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- 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.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- 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.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
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- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
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- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.