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A random extraction method with high market representation for online surveys

Author

Listed:
  • Takumi Kato
  • Noriko Kishida
  • Takahiko Umeyama
  • Yuexian Jin
  • Kazuhiko Tsuda

Abstract

Due to their superior pricing and collection speed when compared to other survey methods, there is significant demand for online surveys in market research. However, online surveys have been reported as being biased. The problem we recognise in this research is that no method to improve accuracy in online surveys has been proposed, even though many types of research on bias have been reported. There are three hypothetical requirements for improving precision: 1) being able to cover the entire population; 2) being able to conduct random sampling; 3) being able to obtain responses without incentives. As a result of examination for the Chinese market, it became clear that the new investigation method satisfying the hypothesis is more accurate than the traditional online panel survey.

Suggested Citation

  • Takumi Kato & Noriko Kishida & Takahiko Umeyama & Yuexian Jin & Kazuhiko Tsuda, 2020. "A random extraction method with high market representation for online surveys," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 22(4), pages 569-584.
    • Handle: RePEc:ids:ijbire:v:22:y:2020:i:4:p:569-584
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    Citations

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    Cited by:

    1. Takumi Kato, 2023. "Paralysis by Inertia “Like†Habit in Social Networking Services: Tendency to Answer Loyalty Questions in Marketing Surveys," SAGE Open, , vol. 13(2), pages 21582440231, May.
    2. Takumi Kato & Taro Miura, 2021. "The impact of questionnaire length on the accuracy rate of online surveys," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 83-98, June.

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