The value of online surveys: a look back and a look ahead

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Abstract

Purpose

The purpose of this paper is to present a detailed and critical look at the evolution of online survey research since Evans and Mathur’s (2005) article on the value of online surveys. At that time, online survey research was in its early stages. Also covered are the present and future states of online research. Many conclusions and recommendations are presented.

Design/methodology/approach

The look back focuses on online surveys, strengths and weaknesses of online surveys, the literature on several aspects of online surveys and online survey best practices. The look ahead focuses on emerging survey technologies and methodologies, and new non-survey technologies and methodologies. Conclusions and recommendations are provided.

Findings

Online survey research is used more frequently and better accepted by researchers than in 2005. Yet, survey techniques are still regularly transformed by new technologies. Non-survey digital research is also more prominent than in 2005 and can better track actual behavior than surveys can. Hybrid surveys will be widespread in the future.

Practical implications

The paper aims to provide insights for researchers with different levels of online survey experience. And both academics and practitioners should gain insights.

Social implications

Adhering to a strong ethics code is vital to gain respondents’ trust and to produce valid results.

Originality/value

Conclusions and recommendations are offered in these specific areas: defining concepts, understanding the future role of surveys, developing and implementing surveys and a survey code of ethics. The literature review cites more than 200 sources.

Related collections

Most cited references 185

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Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?

Michael Buhrmester, Tracy Kwang, Samuel D. Gosling (2011)

Amazon's Mechanical Turk (MTurk) is a relatively new website that contains the major elements required to conduct research: an integrated participant compensation system; a large participant pool; and a streamlined process of study design, participant recruitment, and data collection. In this article, we describe and evaluate the potential contributions of MTurk to psychology and other social sciences. Findings indicate that (a) MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods. Overall, MTurk can be used to obtain high-quality data inexpensively and rapidly.