Orhan, Mehmet A. and Khelladi, Insaf and Castellano, Sylvaine and Singh, Sanjay Kumar
(2022)
Work experience on algorithm-based platforms: The bright and dark sides of turking.
Technological Forecasting and Social Change, 183 (121907).
pp. 1-10.
ISSN 0040-1625
Abstract
The prevalent use of digital labor platforms has transformed the nature of work globally. Such algorithm-based
platforms have triggered many technological, legal, ethical, and human resource management challenges.
Despite some benefits (i.e., flexibility), the precarious conditions and commodification of jobs are major concerns
in these platform-based employment conditions. The remote-work paradigm shift during the COVID-19
pandemic has made the interplay between technology, digitalization, and precarious workers' well-being a
critical issue to address. This paper focuses on microtask platforms by examining overall well-being associated
with turking as a work experience. Using a sample of 401 Amazon Mechanical Turk workers during the early
stage of the COVID-19 pandemic, data were collected on individual conditions affecting the overall quality of
workers' lives. The results from two structural equation models demonstrated the direct and mediating effects of
task characteristics, excessive working, and financial pressure, mirroring the bright and dark sides of turking.
Greater turking task significance and meaningfulness increase personal growth opportunities, ultimately
improving workers' perceived quality of life. However, excessive work and greater financial pressure decrease
self-acceptance and overall quality of life. This study examines the complicated nature of work experience on
algorithm-based platforms by unpacking individual factors that affect workers' well-being.
| Item Type: |
Article
|
| Keywords: |
MTurk;
Microtasking;
Well-being;
Heavy Work Investment;
Crowdworking;
Algorithm-based platforms; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
17782 |
| Identification Number: |
https://doi.org/10.1016/j.techfore.2022.121907 |
| Depositing User: |
Sanjay Singh
|
| Date Deposited: |
07 Nov 2023 14:31 |
| Journal or Publication Title: |
Technological Forecasting and Social Change |
| Publisher: |
Elsevier |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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