Food Delivery Eco-System: When Platforms Get Enterprises and Gig-Workers to Implicitly Cooperate Clara Tuco Naver Labs Europe, Meylan, France clara.tuco-intern@naverlabs.com Cécile Boulard Naver Labs Europe, Meylan, France cecile.boulard@naverlabs.com Romane Calleau Naver Labs Europe, Meylan, France romane.calleau-intern@naverlabs.com Shreepriya Shreepriya Naver Labs Europe, Meylan, France shreepriya.shreepriya@naverlabs.com ABSTRACT Abstract: The gig-economy relies on intermediation platforms that connect customers with gig-workers. The food delivery eco-system includes four actors: platform, restaurant, courier and customer. It difers from other well-studied łgigž platforms such as Uber or Amazon Mechanical Turk as it brings together a business and a gig-worker. Based on our qualitative study involving couriers and restaurants, we demonstrate that a cooperation is needed between restaurants and couriers to perform food delivery. The way plat- forms are designed does not support this cooperation as it is afected by the waiting times at the restaurants and the rating system. A dedicated space where both couriers and restaurants could directly give feedback and information could enhance their understanding of the situation and thus enable cooperation. CCS CONCEPTS · : Human-centered computing; Collaborative and social computing; KEYWORDS Online food delivery, Gig-economy, Cooperation, Restaurant, Courier ACM Reference Format: Clara Tuco, Cécile Boulard, Romane Calleau, and Shreepriya Shreepriya. 2021. Food Delivery Eco-System: When Platforms Get Enterprises and Gig-Workers to Implicitly Cooperate. In Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing (CSCW ’21 Companion), October 23ś27, 2021, Virtual Event, USA. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3462204.3481757 1 INTRODUCTION The gig-economy relies on intermediation platforms that connect requesters or customers with łgig-workersž who could be drivers, crowd-workers or couriers [10]. So far, the most studied platforms, such as Amazon Mechanical Turk (AMT), Upwork, Uber or Lyft Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. CSCW ’21 Companion, October 23ś27, 2021, Virtual Event, USA © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM. ACM ISBN 978-1-4503-8479-7/21/10. . . $15.00 https://doi.org/10.1145/3462204.3481757 are composed of three major actors. For the crowd-work platforms (AMT, Upwork), the actors are the requesters (companies/entities that ofer micro-tasks to be done), self-employed crowd-workers and the platform [8]. For ride hailing, the three major actors are: cus- tomers requesting a trip, self-employed drivers (using their car) and the platform [3]. However, in the case of food delivery, it involves four actors: customers (ordering food), restaurants (preparing the dishes), self-employed couriers (with their bike, motorcycle or car) and the platform. This new confguration implies a cooperation between a business, i.e. the restaurant and the courier, towards a shared objective of satisfactorily delivering the order to the cus- tomer [5]. In this contribution, we explore how global food delivery platforms such as Uber Eats, Deliveroo or Just Eat support this type of cooperation of couriers with restaurants and what are the side efects. The prior knowledge on the relationship between gig-workers and platforms can be applied to the relationship between food de- livery platforms and self-employed couriers. Here we refer to the way couriers are incentivized to work for some time and place, the lack of transparency on the consequences of rating and the assign- ment of tasks [4]. Similarly, the self-employed status of couriers puts them in a precarious situation [7]. In the delivery eco-system, the couriers must also include the constraint of other workers (the restaurants) in their activity. 2 METHOD In order to understand the functioning of the eco-system, we inter- viewed 16 couriers, 7 restaurant managers and did observations of the couriers (2 shifts) as well as the restaurants (5 shifts). Couriers were recruited through an online survey shared on social networks and by approaching them directly on the feld. Restaurants in our (mid-sized French) city were invited and volunteered to participate in the study. Couriers and restaurants worked either with global platforms (such as Uber Eats, Deliveroo, Just Eat, Stuart etc.) or smaller local platforms (enterprises or co-operatives), as indicated in Table 1. All the interviews were transcribed and analyzed from an ethnomethodological perspective. We had no theoretical orienta- tion and were interested in how participants expressed their usage, activities, understandings and opinions about the food delivery ser- vice in their own words [9]. The interviews lasted between 12min to 98min, with an average of 55 minutes. A signifcant observation that stood out was the reported frictions between the couriers and the restaurants showing the diference in the objectives of these actors and how the global platforms poorly support their cooperation. 183