Date of Graduation

8-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Business Administration (PhD)

Degree Level

Graduate

Department

Information Systems

Advisor/Mentor

Grover, Varun

Committee Member

Young, Amber G.

Second Committee Member

Sabherwal, Rajiv

Third Committee Member

Aloysius, John A.

Keywords

Algorithmic control; Algorithmic management; Online labor platforms; Workarounds; Worker well-being; Workplace dignity

Abstract

Online labor platforms (OLPs) are transforming the way organizations operate and how people work. Platform work has been characterized as promoting autonomy and flexibility. Workers interact with a platform rather than human managers to accomplish tasks and they have the freedom to decide when, where, and how much to work. Yet, platform workers increasingly bemoan working conditions, revealing that the expected autonomy and flexibility benefits of platform work have not materialized. Current IS research sheds light on this phenomenon by explaining that platform organizations use algorithms to manage and control workers (i.e., algorithmic control). Yet, our understanding of how algorithmic control affects workers and how they react to it remains limited. Anecdotal evidence suggests that platform workers are experiencing deteriorated wellbeing and concerns for humanity of having AI managers are growing. This dissertation aims to address the issues in two essays. In the first essay, we investigate how platform workers react to algorithmic control and associated worker outcomes using a mixed-methods research design. In phase 1, we conduct a netnographic study to extract a rich understanding of workers’ reactions to algorithmic control and develop a taxonomy of workarounds. In phase 2, we conduct a survey of platform workers to test the research model, thus unravel the impact of workarounds on worker welfare. In the second essay, we address a broader question that is becoming a major humanitarian concern in today’s world of AI and algorithms by exploring how algorithmic management affects workplace dignity. We examine this question through a qualitative study in the largest sector in the online labor platforms (ridesharing and delivery). We further examine how algorithmic management affects the effort or engagement workers devote to their work. The two essays provide several theoretical and practical contributions that advance our understanding of the relationship between algorithms and workers.

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