Web Survey Bibliography

Title The good, the bad and the ugly data: using indicators to get high quality survey respondents from online access panels
Year 2017
Access date 13.04.2017
Abstract

Relevance & Research Question: One of the main issues of using online access panel members for surveys is the avoidance of invalid responses. In order to establish quality and to increase trust, indicators for the survey answering behavior called satisficing have been suggested. These include completing surveys in very short amounts of time, answering in patterns and providing inconsistent answers. A lot of research so far has focused on assessing the validity of these indicators. But how do the indicators covariate? And how can surveys be engineered to minimize invalid responses?

Methods & Data: Post-hoc statistical analysis was performed on 20.000 online interviews generated by online surveys on celebrities for the Human Brand Index project, all of them performed in the proprietary MOBROG Online Access Panel. All surveys had the same basic structure, containing five grid questions of different length and a switch in scale direction in the fifth grid. They also provided the possibility for respondents to enter invalid data on their age and the size of their household. Overall interview time was measured.

Results: About 50% of respondents do not score on any indicator of bad data quality. Another 25% exhibit only one sign of invalid answers, often due to inconsistencies caused by the switch of scale direction in the fifth grid. There is a subpopulation of about 10% of online access panel members who will score simultaneously on almost all indicators. 80% of them manage to successfully adapt to the switch in scale direction while speeding and straight lining. Available time is a factor: Answer quality is highest among high school- and college students, pensioners and unemployed people. It is lowest among 30 to 40 year olds with full time employment. Involvement also helps: die-hard fans and haters of celebrities have higher percentages of high quality data.

Added Value: Using several indicators to screen out respondents whose answers are invalid is a more precise and fair way to ensure data quality than using just one. Loaded questions are avoided by most professional survey takers and confuse respondents whose answers exhibit no signs of satisficing otherwise.

Year of publication2017
Bibliographic typeConferences, workshops, tutorials, presentations
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Web survey bibliography - Germany (639)

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