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Web Survey’s Completion Rates: Effects of Forced Responses, Question Display Styles, and Subjects’ Attitude

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  • Chatpong Tangmanee

    (Chulalongkorn University,Bangkok)

  • Phattharaphong Niruttinanon

    (Chulalongkorn University,Bangkok)

Abstract

In anticipating a high completion rate for web surveys, researchers must be attentive to the design features, two of which are the forced responses (i.e., 100%-, 50%, or 0%-forced) and the questionnaire item display (i.e., paging or scrolling). Moreover, the respondents’ favorable attitude towards questionnaires is a key factor driving them to complete the questionnaires. However, no studies have examined the effects of these three variables on web survey completion rates. This research thus attempts to fill this gap. Using a quasi-experiment, we obtained 401 responses to six (i.e., 3 levels of forced responses x 2 display styles) comparable online questionnaires with identical contents. The analysis confirmed the statistically significant effects of the forced responses, the item display and the subjects’ attitudes toward questionnaires on completion rates. In addition to extending theoretical insights into the factors leading to a web survey’s completion rates, practical recommendations are suggested based on the findings. Key Words: Web Survey, Completion Rates, Forced Responses, Question Display Styles

Suggested Citation

  • 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.
    • Handle: RePEc:rbs:ijbrss:v:8:y:2019:i:1:p:20-29
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    References listed on IDEAS

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    1. Karen Yuan Wang & Dilek Zamantili Nayir, 2009. "Procedural justice, participation and power distance: Information sharing in Chinese firms," Management Research Review, Emerald Group Publishing, vol. 33(1), pages 66-78, December.
    2. Vera Toepoel & Corrie Vis & Marcel Das & Arthur van Soest, 2009. "Design of Web Questionnaires," Sociological Methods & Research, , vol. 37(3), pages 371-392, February.
    3. Gao, Baojun & Li, Xiangge & Liu, Shan & Fang, Debin, 2018. "How power distance affects online hotel ratings: The positive moderating roles of hotel chain and reviewers’ travel experience," Tourism Management, Elsevier, vol. 65(C), pages 176-186.
    4. Stefan Stieger & Ulf‐Dietrich Reips & Martin Voracek, 2007. "Forced‐response in online surveys: Bias from reactance and an increase in sex‐specific dropout," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1653-1660, September.
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