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          <titl xml:lang="en">Replication Data for: "Digital Mobility“ and Data Quality. Consequences of nonresponses as situational behaviour of survey participants when using a smartphone anywhere.</titl>
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        <AuthEnty affiliation="University of Applied Sciences Upper Austria: Campus Linz" xml:lang="en">Wetzelhütter, Daniela
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      <abstract xml:lang="en">A paper and pencil questionnaire is usually filled out at the place of receipt. For a household survey, this is quite often the residential address of respondents. When employment conditions are examined, the survey is often carried out at the workplace. If aspects of education are evaluated, a survey is normally done at the educational institution. Most recently, the same applied to an online questionnaire, which was usually completed at the place of receipt (location of the personal computer) – either at home or at work. Nowadays, potential respondents are more and more “digitally mobile”. They may choose mobile devices to participate in an online survey thanks to technical developments. Therefore, they are able to access the online surveys regardless of device- and location. As a consequence, the interview situation is more changeable regarding where (location) and how (device) the questionnaire is filled out. This variability – as it is assumed – leads to context-related nonresponses, which influences the nature of the data. Based on this, the research question is: ”How crucial is digital mobility, in terms of location and device, due to nonresponses, for the quality of data collected online?” In order to answer this question, the data from an online survey about “participation of students at university” is used. 17,500 students were invited to participate in the survey. 14% of the target group reacted to the invitation, 11% answered at least one question, but just 7% reached the final page. Those response rates or dropout rates differ depending on context-specific characteristics in terms of location and mobile device. The research results show that different situational conditions within the interview should be considered in the course of data processing and analysing – both might contribute to the quality of results.</abstract>
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