Affiliation:
1. Michael David Maffieis an Assistant Professor of Management and Organizations in the Nolan School of Hotel Administration, Johnson College of Business at Cornell University
Abstract
This article explores how gig workers interact with more conventional employees. Drawing on original qualitative and quantitative data from Instacart shoppers and grocery store staff, this article shows how Instacart’s algorithmic management system pushes shoppers to mistreat in-store staff. Yet for shoppers who frequently interact with staff, the author finds they develop cooperative, cross-organization co-worker relationships. These relationships grant shoppers access to resources typically reserved for staff, allowing them to navigate the algorithmic constraints that Instacart places on them. Findings show that platform companies’ use of algorithmic management tools can spill over to negatively affect the working conditions of conventional workers; but also, that gig workers can improve their own conditions by building relationships with their conventional peers.
Subject
Management of Technology and Innovation,Organizational Behavior and Human Resource Management,Strategy and Management
Cited by
2 articles.
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