Assessing bias in online surveys using alternative survey modes. (14th May 2022)

• Record Type: Journal Article
• Authors: Spencer, Neil H.; Syrdal, Dag S.; Coates, Matthew; Huws, Ursula
• Is Part Of: Work, organisation, labour & globalisation. Volume 16:Number 1(2022)
• Page Start: 34
• Page End: 51
• Publication Date: 2022-05-14
• Subjects: bias -- offline surveys -- online surveys -- platform work -- survey mode; Work -- Periodicals; Labor -- Periodicals; Division of labor -- Periodicals; Industrial relations -- Periodicals; Division of labor; Industrial relations; Labor; Work; Periodicals; 331
• DOI: 10.13169/workorgalaboglob.16.1.0034
• Languages: English
• ISSNs: 1745-6428

Abstract

Abstract : Due to concerns that respondents to online surveys are different from populations of interest, parallel offline surveys can be undertaken and results compared. In this article we create a set of principles to compare results from online surveys with those from surveys using other survey modes. Rather than just comparing estimates and confidence intervals from the different modes, these principles consider biases that each survey mode introduces and whether the results obtained are compatible with each other, given these different biases. Using the example of a survey of platform work, we demonstrate that this approach can be used effectively and be applied to a variety of social science studies that use online surveys.