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In Their Shoes: A Structured Analysis of Job Demands, Resources, Work Experiences, and Platform Commitment of Crowdworkers in China

Published: 04 January 2020 Publication History

Abstract

Despite the growing interest in crowdsourcing, this new labor model has recently received severe criticism. The most important point of this criticism is that crowdworkers are often underpaid and overworked. This severely affects job satisfaction and productivity. Although there is a growing body of evidence exploring the work experiences of crowdworkers in various countries, there have been a very limited number of studies to the best of our knowledge exploring the work experiences of Chinese crowdworkers. In this paper we aim to address this gap. Based on a framework of well-established approaches, namely the Job Demands-Resources model, the Work Design Questionnaire, the Oldenburg Burnout Inventory, the Utrecht Work Engagement Scale, and the Organizational Commitment Questionnaire, we systematically study the work experiences of 289 crowdworkers who work for ZBJ.com - the most popular Chinese crowdsourcing platform. Our study examines these crowdworker experiences along four dimensions: (1) crowdsourcing job demands, (2) job resources available to the workers, (3) crowdwork experiences, and (4) platform commitment. Our results indicate significant differences across the four dimensions based on crowdworkers' gender, education, income, job nature, and health condition. Further, they illustrate that different crowdworkers have different needs and threshold of demands and resources and that this plays a significant role in terms of moderating the crowdwork experience and platform commitment. Overall, our study sheds light to the work experiences of the Chinese crowdworkers and at the same time contributes to furthering understandings related to the work experiences of crowdworkers.

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    cover image Proceedings of the ACM on Human-Computer Interaction
    Proceedings of the ACM on Human-Computer Interaction  Volume 4, Issue GROUP
    GROUP
    January 2020
    405 pages
    EISSN:2573-0142
    DOI:10.1145/3378060
    Issue’s Table of Contents
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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 January 2020
    Published in PACMHCI Volume 4, Issue GROUP

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    Author Tags

    1. china
    2. crowdsourcing
    3. job-demands resources model
    4. oldenburg burnout inventory
    5. utrecht work engagement scale
    6. work design questionnaire
    7. work experience

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    • (2024)The State of Pilot Study Reporting in Crowdsourcing: A Reflection on Best Practices and GuidelinesProceedings of the ACM on Human-Computer Interaction10.1145/36410238:CSCW1(1-45)Online publication date: 26-Apr-2024
    • (2023)Tasks of a Different Color: How Crowdsourcing Practices Differ per Complex Task Type and Why This MattersProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581418(1-15)Online publication date: 19-Apr-2023
    • (2022)GMAP 2022: Workshop on Group Modeling, Adaptation and PersonalizationAdjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3511047.3536351(280-282)Online publication date: 4-Jul-2022
    • (2022)The dawn of crowdfarmsCommunications of the ACM10.1145/349069865:8(64-70)Online publication date: 21-Jul-2022
    • (2021)An Examination of the Work Practices of CrowdfarmsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445603(1-14)Online publication date: 6-May-2021
    • (2020)Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm WorkersProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376473(1-13)Online publication date: 21-Apr-2020

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