MANAGEMENT & ORGANIZATIONS
Adversaries or Cross- Organization Co-workers: Exploring the Relationshp between Gig Workers and
MICHAEL D. MAFFIE ASSISTANT PROFESSOR
Cornell Peter and Stephanie Nolan School of Hotel Administration
Cornell SC Johnson College of Business Cornell University
LINK TO PAPER LINK TO MICHAEL MAFFIE VIDEO
Author • Michael D. Maffie
Summary
Since the earliest days of the online gig economy, scholars and policymak- ers have asked whether employers would replace full-time employees with gig workers to avoid paying employment benefits and undermine workers’ rights. Tis article, however, explores the interaction between gig workers and conventional employees, who frequently come into contact with one another, especially in the service sector. Despite extensive research on the nature of gig work, researchers know very little about how gig workers relate to or shape the working experiences of more conventional service workers.
Drawing on original qualitative and quantitative data from Instacart shop- pers and grocery store staff, this article shows how Instacart’s algorithmic management system pushes professional shoppers to mistreat in-store staff. Yet shoppers who chose to frequently interact with staff are seen to develop cooperative, cross-organization co-worker relationships. Maffie argues that these relationships grant shoppers access to resources typically reserved for store staff, allowing them to navigate the algorithmic constraints that Instacart places on them. Platform companies’ use of algorithmic management tools can spill over to negatively affect the conditions of conventional workers, but gig workers can improve their own conditions by building relationships with their conventional peers.
CONTENTS TO MAIN | RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2024 EDITION 33
Conventional Employees Industrial and Labor Relations Review, 77, 1, January 2024
Assistant Professor, Cornell Peter and Stephanie Nolan
School of Hotel Administration, Cornell SC Johnson College of Business, Cornell University
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