"At the end of the day, I am accountable": Gig Workers' Self-Tracking for Multi-Dimensional Accountability Management

Hernandez, Rie Helene (Lindy); Song, Qiurong; Kou, Yubo; Gui, Xinning

doi:10.1145/3613904.3642151

Cited by 2 publications

References 85 publications

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Individual accountability of MTurk gig workers: examining the scale dimensionality

Fanoodi,

Ray,

Beu Ammeter

et al. 2024

IJOA

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Purpose This paper aims to build upon the accountability pyramid model by presenting two studies that examine the dimensionality of individual accountability among Amazon Mechanical Turk (MTurk) gig workers. Design/methodology/approach For the first study, aimed at investigating the dimensionality of individual accountability of gig workers, the authors collected data from MTurkers by administering two surveys in the English and Mandarin Chinese languages with 185 respondents. The authors implemented principal component analysis and confirmatory factor analysis to analyse the data. For the second study, aimed at establishing validation of the dimensionality found in the first study, the authors collected data from an additional 148 respondents. Findings The results indicated that the intensity and salience dimensions merged into one factor that the authors labelled Accountability Significance, while the process and outcome dimensions merged into one factor labelled Accountability Focus. Additionally, the authors found that individual accountability is a second-order construct encompassing Accountability Significance and Accountability Focus as first-order factors. The authors validated the findings in the second study. Originality/value To the best of the authors’ knowledge, this research is the first quantitative study investigating the individual accountability of gig workers. The validation of individual accountability in MTurkers offers valuable insights into MTurkers’s Hybrid Accountability Focus and Accountability Significance.

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