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Web Survey Bibliography

Title When to Email or Not?: Determining the Best Day of the Week to Send Evites For Participation in a Web Survey.
Year 2010
Access date 30.06.2011
Abstract

Over the last decade, there has been an increasing popularity in using Web surveys to study various populations. In particular, high usage of the Web among college students lends itself as a cost-effective data collection strategy for this population (Carini, Hayek, Kuh, Kennedy, & Ouimet, 2003). As a result, researchers have focused on whether web surveys deliver comparable data to paper surveys, finding that differences in data quality are usually minimal (Carini et al., 2003), though concerns about data security and nonresponse bias remain (Smith 1997). Still, given using Web surveys as the main mode of a data collection is relatively new, many important questions related to when and how often to contact
respondents to ensure high response rates remain unanswered. For example, should email invitations (evites) be sent on a particular day of the week; which day yields the highest same-day response? These questions form the basis of the proposed study.
Specifically, we will use data from 5 completed mix-mode data collection efforts of college students (Web-Telephone-In-person follow-up) to examine the “best” day to contact respondents (through evites) to obtain completed surveys. Across these 5 studies (with ~1668 Web completes), we will evaluate the following:
1. Sending evites to respondents on which day of the week will yield the greatest number of same-day responses?
2. Sending evites on which day of the week will result in the smallest average number of days between evites and survey completion?
3. Sending evites on which day of the week will result in completed surveys with higher data quality?
Initial results indicate that compared to later in the week , contacting students earlier in the week (Monday and Wednesday) results in a greater number of completed surveys, a shorter time to completion, and that there is no discernable effect on data quality.

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Year of publication2010
Bibliographic typeConferences, workshops, tutorials, presentations
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Web survey bibliography - 2010 (251)

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