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Report

Work Schedules, Finances, and Freedom: Work Schedule Fit and Platform Dependence among Gig Workers on Amazon’s Mechanical Turk Platform

Authors:

  • Jeremy Reynolds, Purdue University
  • Daniel Felipe Pinzón Quintero, Purdue University
  • Julieta Aguilar, Purdue University
  • Reilly Kincaid, Purdue University
Publication Date:

Abstract

Formally, gig workers determine their work hours. Gig platforms, however, shape work schedules with many tools, including ratings, deadlines, pay, and competition. The platform dependence perspective suggests that gig workers who rely on platform income are especially vulnerable to manipulation and often fail to fulfill their scheduling preferences. We offer one of the first quantitative tests of this prediction while also examining if the theory applies to highly flexible online gig work. Using a U.S. sample of Amazon Mechanical Turk workers, we find that mismatches between preferred and actual schedules are common and increase with hours worked. As predicted, mismatches are especially prevalent among platform-dependent respondents, but group differences are only significant for the minority of respondents working more than 30 hours per week. More research is needed to understand schedule mismatches among low-hour gig workers and how “strategic neglect” may help generate them