Abstract
The widespread algorithms have deeply reshaped the nature of work, causing new challenges for organizations and individuals. Less studied, however, is the impact of algorithmic management - defined as using self-learning algorithms to make and execute labor-related managerial decisions - on individuals beyond producing economic value. Our symposium aims to explore the questions: (1) what is the role of algorithms in talent management in the gig economy? (2) How do gig workers learn and adapt to certain algorithms to form work norms? (3) How do gig workers handle the challenges associated with algorithms to achieve objective and subjective career success? (4) What are the ups and downs of algorithmic management in the eyes of gig workers and why? Our symposium covers a variety of research methods (a conceptual paper, a big-data driven study, a lab simulation study, and a qualitative study), types of gig work (offline routine work and online non-routine work), samples (web doctors, ridesharing drivers), and theoretical lenses (talent management, norm, emotion, justice). It aims to facilitate cross-division dialogue among Organizational Behavior, Human Resources, and Careers scholars. Talent Management in the Gig Economy? A Conceptual Framework Presenter: Jeroen Meijerink; U. of Twente Presenter: Sandra Fisher; Münster U. of Applied Sciences Presenter: Sharna Lee Wiblen; Sydney Business School, U. of Wollongong Web Doctor’s Compassion: An Unfolding Model of Norm Formation Presenter: Lan Wang; U. of Science and Technology of China Presenter: Chen Chen; Boston U. Driven by High Ratings: Injustice and Emotional Labor in the Ridesharing Context Presenter: Xue Lei; George Mason U. Presenter: John Cliburn; George Mason U. Presenter: Cedric Portea; George Mason U. A Qualitative Study on On-Demand Workers’ Justice Perceptions of Algorithmic Management Presenter: Lian Zhou; Guangdong U. of Technology Presenter: Xue Lei; George Mason U. Presenter: Rui Hou; Guangdong U. of Technology
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