Rapid development in the survey methods available on the World Wide Web (WWW) is having a major impact on conventional survey data collection methods. The wide range of opinions has given rise to an ongoing debate regarding the future role of Internet surveys (in particular, Web surveys) based on the role that self-administration will play in research. We started by arranging a practical procedure for electronic data collection on the Web surveys experimentally designed from the viewpoint of "data science." Aiming to verify the applicability, possibilities, and limitations of Web survey methods, we conducted three experimental surveys during the period from 1997 to 2000. They were designed to enable comparison with each other and with traditional methods such as face-to-face interviews and online surveys using conventional sampling procedures. These surveys provided informative results about the characteristics of Web surveys. In the first survey, consisting of 12 continual surveys of a single panel of registrants, we examined the relationship between the response rates and the questionnaire's design, volume and content, as well as response rate differences among the 12 surveys and the discrepancies in repeated surveys. In the second experimental survey, we carried out Web surveys at about the same time on three different sites together with non-internet surveys using conventional sampling methods. Our experimental design enabled objective comparison of the surveys by using as much identical questionnaire design as possible. Our experimental surveys showed that Web survey results are similar to each other while distinctively differing from those of conventional surveys. In the third experimental survey, we simultaneously carried out a series of comparative surveys in order to examine the general characteristics of Web surveys found during the second experimental survey. Except that the number of sites used was two instead of three, the third experimental surveys were carried out in the same way as in the second trial. We confirmed the results that the same characteristics were evident again in the second survey. We also found that how the registrants of the surveys (named "resources") were selected and whether the interval between solicitation and survey was short or long would be factors influencing the answers and response-rate. We also found that the respondents do not necessarily represent the resources. In addition, as an addendum in this paper, we report partly the results of a fourth experimental survey which has been carried out in 2001 to 2002 and compare it with the findings of the previous three trials. In particular, we also analyze the itemized causes of "nonresponse" on the datasets obtained from the tracking procedure of tracing electronically each respondent on the WWW. The fourth survey consists of Web surveys on three separate sites while the other surveys were based on conventional sampling methods (e.g., face-to-face interviews and mail surveys). While we use the same questionnaire design, content, and duration as those used in the past surveys, we also attempt to examine how the questionnaire design has influenced responses. Through these experimental surveys, an appropriate route to how to design a Web survey, evaluate its quality and avoid possible risks or perils in design is proposed from the concept of "data science."
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