Title: A random extraction method with high market representation for online surveys

Authors: Takumi Kato; Noriko Kishida; Takahiko Umeyama; Yuexian Jin; Kazuhiko Tsuda

Addresses: Business Analytics Section, Honda Motor Co., Ltd., 8-1, Honcho, Wako-shi, Saitama, 351-0114, Japan ' Cross Marketing Inc., Tokyo Opera City Tower, 24F, 3-20-2 Nishishinjuku, Shinjuku-ku, Tokyo 163-1424, Japan ' Cross Marketing Inc., Tokyo Opera City Tower, 24F, 3-20-2 Nishishinjuku, Shinjuku-ku, Tokyo 163-1424, Japan ' Cross Marketing Inc., Tokyo Opera City Tower, 24F, 3-20-2 Nishishinjuku, Shinjuku-ku, Tokyo 163-1424, Japan ' Graduate School of Business Sciences, University of Tsukuba, 3-29-1, Otsuka, Bunkyo, Tokyo 112-0012, Japan

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.

Keywords: marketing research; online survey; market representativeness; random extraction; random domain intercept technology; RDIT; China; automotive market; cultural map.

DOI: 10.1504/IJBIR.2020.109036

International Journal of Business Innovation and Research, 2020 Vol.22 No.4, pp.569 - 584

Received: 29 Oct 2018
Accepted: 15 Mar 2019

Published online: 11 Aug 2020 *

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