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Respondent Behavior Logging: A Design Science Research Inquiry into Web Survey Paradata

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The Next Wave of Sociotechnical Design (DESRIST 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12807))

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Abstract

This paper introduces a framework for Respondent Behavior Logging (RBL), consisting of static and dynamic models that conceptualize respondent behavior when filling in online questionnaires, and visualization techniques and measurement constructs for RBL data. Web survey design may benefit from paradata logging as a technique for evaluation, since such data may prove useful during the re-design of questionnaires. Although other aspects of online surveys have attracted considerable attention both in the industry and in literature, it is still underexplored how the Web may leverage new and innovative techniques to support survey design. The RBL framework is evaluated using a focus group and through an experimental survey with 120 participants. We elaborate on implications for research and practice in an informed argument.

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Author information

Authors and Affiliations

  1. Department of Informatics and Media, Uppsala University, Uppsala, Sweden

    Mohammad Hafijur Rahman & Jonas Sjöström

Authors
  1. Mohammad Hafijur Rahman
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  2. Jonas Sjöström
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Correspondence to Jonas Sjöström .

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Editors and Affiliations

  1. University of Liechtenstein, Vaduz, Liechtenstein

    Leona Chandra Kruse

  2. University of Liechtenstein, Vaduz, Liechtenstein

    Stefan Seidel

  3. University of Agder, Kristiansand, Norway

    Geir Inge Hausvik

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Rahman, M.H., Sjöström, J. (2021). Respondent Behavior Logging: A Design Science Research Inquiry into Web Survey Paradata. In: Chandra Kruse, L., Seidel, S., Hausvik, G.I. (eds) The Next Wave of Sociotechnical Design. DESRIST 2021. Lecture Notes in Computer Science(), vol 12807. Springer, Cham. https://doi.org/10.1007/978-3-030-82405-1_25

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  • DOI: https://doi.org/10.1007/978-3-030-82405-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82404-4

  • Online ISBN: 978-3-030-82405-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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