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Web Survey Bibliography

Title More than the digital divide?: Investigating the differences between Internet and non-Internet users
Source Annual Conference of the Midwest Association for Public Opinion Researc
Year 2008
Access date 15.09.2009
Abstract

Even before the internet became popular among the public, researchers had identified the potential problems involved in using a web-based data collection method for survey research. Probability-based web surveys are generally believed to produce data of higher quality than those from non-probability web surveys. Both of these methods, however, are subject to coverage error. This is shown by the fact that in 71% of American households, at least one member uses the internet at any location (including at home), and that only 62% of households have an internet connection from home as of October of 2007. Moreover, some subgroups of the population are more likely to be offline than others. This phenomenon is often referred to as the digital divide. Evidence also suggests that this divide may not be closing quickly enough to be dismissed by researchers who want to study a representative sample of the population. As a solution, Knowledge Networks covers the ISP charges and provides WebTVs and in some cases PC’s to its panelists (i.e., KnowledgePanel® members) who live in a household without internet access, thus closing the digital divide gap. As a result, all panel members recruited by landline RDD are able to complete surveys online, which minimizes the potential bias that can result from ignoring non-internet users. Data from KnowledgePanel® are examined to build a profile of these non-internet users to find out who they are and how they behave. In this paper, demographic characteristics of the offline population are first explored and compared to other research findings. Then, responses to a series of survey questions are analyzed using (multinomial) logistic regressions, to identify whether internet access status still makes a difference when controlled by relevant demographic variables. For example, the analysis reveals that differences in environmental behaviors between internet and non-internet users (e.g., recycling paper and glass) still exist after controlling for the relevant demographic variables.

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Year of publication2008
Bibliographic typeConferences, workshops, tutorials, presentations
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