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Understanding experiences of food-delivery-platform workers under algorithmic management using topic modeling

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  • Won, Jongho
  • Lee, Daeho
  • Lee, Junmin

Abstract

With the emergence of COVID-19, the food-delivery market has grown and now employs large numbers of people as drivers. The independent contractors enjoy flexibility, but their schedules are at the mercy of algorithmic management. This study explores the experiences of food-delivery-platform workers with algorithmic management and their perceptions in response to algorithmic decisions. A collection of 1046 posts containing “AI” (for artificial intelligence) and “algorithm” made to online communities frequently used by platform workers is subjected to keyword analysis, semantic network analysis, and topic modeling using latent Dirichlet allocation. Fifteen latent topics are classified into AI matching, driver behavior, and platform system, and discussed using representative posts from online communities. The results highlight the advancement of AI technology and collaboration strategies used by platform operators to generate trust in algorithmic decisions among food-delivery-platform workers. In addition, this study uses using topic modeling to comprehensively and objectively explore how food-delivery-platform workers with experience working under AI algorithmic management perceive that management.

Suggested Citation

  • Won, Jongho & Lee, Daeho & Lee, Junmin, 2023. "Understanding experiences of food-delivery-platform workers under algorithmic management using topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523000549
    DOI: 10.1016/j.techfore.2023.122369
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    1. Sandy Q. Qu & John Dumay, 2011. "The qualitative research interview," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 8(3), pages 238-264, August.
    2. Sandy Q. Qu & John Dumay, 2011. "The qualitative research interview," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 8(3), pages 238-264, August.
    3. Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
    4. Muhammad Umar & Yan Xu & Sultan Sikandar Mirza, 2021. "The impact of Covid-19 on Gig economy," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 2284-2296, January.
    5. Newman, David T. & Fast, Nathanael J. & Harmon, Derek J., 2020. "When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 149-167.
    6. Jonathan Woodside & Tara Vinodrai & Markus Moos, 2021. "Bottom-up strategies, platform worker power and local action: Learning from ridehailing drivers," Local Economy, London South Bank University, vol. 36(4), pages 325-343, June.
    7. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    8. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    9. Andrew Stewart & Jim Stanford, 2017. "Regulating work in the gig economy: What are the options?," The Economic and Labour Relations Review, , vol. 28(3), pages 420-437, September.
    10. Markus Blut & Cheng Wang & Nancy V. Wünderlich & Christian Brock, 2021. "Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 632-658, July.
    11. Cram, Alec W. & Wiener, Martin & Tarafdar, Monideepa & Benlian, Alexander, 2020. "Algorithmic Controls and their Implications for Gig Worker Well-being and Behavior," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124127, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Brian Fabo & Jovana Karanovic & Katerina Dukova, 2017. "In search of an adequate European policy response to the platform economy," Transfer: European Review of Labour and Research, , vol. 23(2), pages 163-175, May.
    13. Arianna Tassinari & Vincenzo Maccarrone, 2020. "Riders on the Storm: Workplace Solidarity among Gig Economy Couriers in Italy and the UK," Work, Employment & Society, British Sociological Association, vol. 34(1), pages 35-54, February.
    14. Sophia Galiere, 2020. "When food‐delivery platform workers consent to algorithmic management: a Foucauldian perspective," Post-Print hal-03131338, HAL.
    15. Jiang, Jennifer & Adam, Martin & Benlian, Alexander, 2021. "Algoactivistic Practices in Ridesharing - A Topic Modeling & Grounded Theory Approach," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126522, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. Lammi, Minna & Pantzar, Mika, 2019. "The data economy: How technological change has altered the role of the citizen-consumer," Technology in Society, Elsevier, vol. 59(C).
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