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Design of Web Questionnaires

Author

Listed:
  • Vera Toepoel

    (Tilburg University, Netherlands, V.Toepoel@uvt.nl)

  • Corrie Vis

    (Tilburg University, Netherlands)

  • Marcel Das

    (Tilburg University, Netherlands)

  • Arthur van Soest

    (Tilburg University, Netherlands)

Abstract

In this article, an information-processing perspective is used to explore the impact of response categories on the answers respondents provide in Web surveys. Response categories have a significant effect on response formulation in questions that are difficult to process, whereas in easier questions (where responses are based on direct recall) the response scales have a smaller effect. In general, people with less cognitive sophistication are more affected by contextual cues. The Need for Cognition and the Need to Evaluate indexes for motivation account for a significant part of the variance in survey responding. Interactions of ability to process information and motivation combine in regulating responses for questions that are more difficult to process. The results hint at a substantial role of satisficing in Web surveys.

Suggested Citation

  • Vera Toepoel & Corrie Vis & Marcel Das & Arthur van Soest, 2009. "Design of Web Questionnaires," Sociological Methods & Research, , vol. 37(3), pages 371-392, February.
  • Handle: RePEc:sae:somere:v:37:y:2009:i:3:p:371-392
    DOI: 10.1177/0049124108327123
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    References listed on IDEAS

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    1. Menon, Geeta & Raghubir, Priya & Schwarz, Norbert, 1995. "Behavioral Frequency Judgments: An Accessibility-Diagnosticity Framework," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(2), pages 212-228, September.
    2. Lynch, John G, Jr & Chakravarti, Dipankar & Mitra, Anusree, 1991. "Contrast Effects in Consumer Judgments: Changes in Mental Representations or in the Anchoring of Rating Scales?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(3), pages 284-297, December.
    3. Michael D. Hurd & Daniel McFadden & Harish Chand & Li Gan & Angela Menill & Michael Roberts, 1998. "Consumption and Savings Balances of the Elderly: Experimental Evidence on Survey Response Bias," NBER Chapters, in: Frontiers in the Economics of Aging, pages 353-392, National Bureau of Economic Research, Inc.
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    3. Chatpong Tangmanee & Phattharaphong Niruttinanon, 2015. "Effects of Forced Responses and Question Display Styles on Web Survey Response Rates," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 4(2), pages 54-62, April.
    4. Lindhjem, Henrik & Navrud, Ståle, 2011. "Using Internet in Stated Preference Surveys: A Review and Comparison of Survey Modes," International Review of Environmental and Resource Economics, now publishers, vol. 5(4), pages 309-351, September.
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    6. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    7. Chatpong Tangmanee & Phattharaphong Niruttinanon, 2019. "Web Survey’s Completion Rates: Effects of Forced Responses, Question Display Styles, and Subjects’ Attitude," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 8(1), pages 20-29, January.
    8. Neuert Cornelia E. & Roßmann Joss & Silber Henning, 2023. "Using Eye-Tracking Methodology to Study Grid Question Designs in Web Surveys," Journal of Official Statistics, Sciendo, vol. 39(1), pages 79-101, March.
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    13. de Bruijne, M.A., 2015. "Designing web surveys for the multi-device internet," Other publications TiSEM 19e4d446-a62b-4a95-8691-8, Tilburg University, School of Economics and Management.
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