ADEKOYA, Olatunji, MORDI, Chima, AJONBADI, Hakeem and WEIFENG, Chen (2023). Implications of algorithmic management on careers and employment relationships in the gig economy – a developing country perspective. Information Technology and People. [Article]
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Algorithmic Management - Accepted Version.pdf - Accepted Version
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Algorithmic Management - Accepted Version.pdf - Accepted Version
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Abstract
Purpose – This article explores the implications of algorithmic management on careers and
employment relationships in the Nigerian gig economy. Specifically, drawing on labour
process theory, we provide an understanding of the production relations beyond the ‘traditional
standard’ to ‘nonstandard’ forms of employment in a gig economy mediated by digital
platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).
Design – We adopted the interpretive qualitative approach and a semi-structured interview of
49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.
Findings – This study addresses the theoretical underpinnings of the labour process theory as
it relates to algorithmic management and control in the digital platform economy. The study
revealed that, despite the ultra-precarious working conditions and persistent uncertainty in
employment relations under algorithmic management, the underlying key factors that motivate
workers to engage in digital platform work include higher job flexibility and autonomy, as well
as having a source of income. We captured the human-digital interface and labour processes
related to digital platform work in Nigeria. Our findings also revealed that algorithmic
management enables a transactional exchange between platform providers and drivers, while
relational exchanges occur between drivers and customers/passengers. Finally, we highlighted
the perceived impact of algorithmic management on the attitude and performance of workers.
Originality – The research presents an interesting case study to investigate the influence of
algorithmic management and labour processes on employment relationships in the largest
emerging economy in Africa.
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