An exploration of a respondent pre-qualifying framework to increase response rates in social media initiated online surveys

Abstract

Listen

Translate article

The use of web-based surveys is currently increasing due to its cost-effectiveness and agility as it provides access to market researchers to web-connected populations who are unlikely to answer through traditional survey methods. However, survey response rates in market research are in general decline and among survey platforms, web-based surveys have the highest rates of non-response. Thus, there is a need to address the declining response rates for web-based surveys particularly unit response rates – the likelihood the respondent would answer the survey. This paper proposes a respondent prequalifying framework that reduces unit non-response rates of web-based non-probabilistic surveys. A checklist of respondent characteristics influencing the likelihood of unit non-response was developed. The framework was then adopted for its applicability by replicating the recruitment phase of two case studies wherein the prequalifying checklist was applied with consideration to the respondent profile requirements of each study. While this paper does not intend to provide robust empirical evidence to the proposed framework, it demonstrates a promising framework that can be used to increase unit non-response rate by comprehensively integrating the pre-qualifying factors in the domain literature and carefully developing such framework to the most plausible direction a web-survey can be implemented. Findings suggest that (1) the proposed respondent prequalifying framework increases the unit response by prequalifying the sample in the recruitment stage, and (2) increasing the threshold value may increase unit response rates with careful consideration to some significant issues such as the weights assigned to the prequalifying factors, the quality of the background information of the respondents in relation to the prequalifying factors, and the sensitivity of the survey topic. The proposed framework is developed with strong theoretical grounding and detailed discussion for its practical use is also provided. The framework benefits market researchers by reducing unit non-response costs and increasing efficiency in social media-based market surveys.