Disconnecting labour: The impact of intraplatform algorithmic changes on the labour process and workers' capacity to organise collectively

• Published date: 01 March 2023
• Author: Pedro Mendonça,Nadia K. Kougiannou
• Date: 01 March 2023
• DOI: http://doi.org/10.1111/ntwe.12251

Received: 16 June 2021

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Accepted: 20 June 2022

DOI: 10.1111/ntwe.12251

RESEARCH ARTICLE

Disconnecting labour: The impact of

intraplatform algorithmic changes on the

labour process and workers' capacity to

organise collectively

Pedro Mendonça

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|Nadia K. Kougiannou

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1

Edinburgh Napier University, the

Business School, Edinburgh, UK

2

Nottingham Trent University,

Nottingham Business School,

Nottingham, UK

Correspondence

Pedro Mendonça, Edinburgh Napier

University, the Business School,

Craiglockhart Campus, 219 Colinton Rd,

Edinburgh EH14 1DJ, UK.

Email: p.mendonca@napier.ac.uk

Abstract

This article examines how gig economy platform

companies, via algorithmic management, shape working

conditions and collective organisation of food delivery

couriers. Using qualitative data from one case study

operating in a city in the United Kingdom, the study

captures real‐time intraplatform unilateral changes in

algorithmic management to provide increased flexibility

for couriers. Findings show algorithmic changes generat-

ing a reconfigured, fragmented and compliant workforce.

As a result, couriers demonstrate different interests and

motivations to work for the company, where disparities

in the demands for improved working conditions

hindered efforts for collective organising. This article

argues that intraplatform algorithmic changes create

affordances that companies can exploit to concentrate

power over labour even when conceding some control

over the labour process.

KEYWORDS

algorithmic management, collective organising, gig economy,

labour process, platform work

New Technol Work Employ. 2023;38:1–20. wileyonlinelibrary.com/journal/ntwe

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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and

reproduction in any medium, provided the original work is properly cited.

© 2022 The Authors. New Technology, Work and Employment published by Brian Towers (BRITOW) and John Wiley & Sons Ltd.

INTRODUCTION

The gig economy has become increasingly prevalent in contemporary societies and has

generated considerable scholarly and policy debate (De Stefano, 2016; Griesbach et al., 2019;

Taylor et al., 2017; Woodcock, 2016). The gig economy is broadly defined as people using digital

platforms to sell their labour (Taylor et al., 2017). A platform and algorithm mediate the

capital–labour relationship by controlling worker supply and consumer demand to complete a

small task or ‘gig’(Gandini, 2019). Research has categorised the different types of gig work (see

De Stefano, 2016). This article is particularly concerned with local gig work used to deliver food

that is mediated via platforms and algorithms. Food‐delivery gig work has been characterised as

the ‘last mile of delivery’. Its coordination and cost‐effectiveness, attained via platforms and

algorithms, is key to gaining a competitive advantage (Heiland, 2021).

Recent theoretical accounts have argued that gig economy platform companies constitute a

new governance mechanism for conducting economic transactions (Vallas & Schor, 2020).

Platforms, seen as permissive potentates, rely on technological infrastructure, information

asymmetries and flexible employment to concede some control, but retain most power over the

labour process (Gandini, 2019; Vallas & Schor, 2020). Notably, studies have explored the use of

algorithmic management to examine its impact on reducing indeterminacy of work (Cant,

2019), workers' experiences (Griesbach et al., 2019), autonomy (Shapiro, 2018,2020) and

collective and individual agency (Kougiannou & Mendonça, 2021; Tassinari & Maccarrone,

2020; Veen et al., 2020; Wood & Lehdonvirta, 2021; Wood et al., 2018). Studies have also

examined how the compounded effect between technological control and flexible forms of

employment impact workers' experiences and working conditions (Gregory, 2020; Ivanova

et al., 2018). Finally, some authors explored these dynamics across different gig economy

platform companies and their different impacts on working conditions and workers' capacity to

collectively organise (Griesbach et al., 2019; Ivanova et al., 2018; Tassinari & Maccarrone, 2020;

Veen et al., 2020).

However, less attention has been paid to how intraplatform changes in algorithmic control

(i.e., algorithmic changes that occur within the same digital platform, in opposition to those

observed across digital platforms) influence workers' experiences of the labour process and

impact the collective organisation. By addressing this gap and complementing the growing

research in this area, this article contributes to new knowledge empirically and theoretically.

Empirically, by examining the processes of intraplatform algorithmic management changes and

how these shape labour and the labour process in real‐time. Theoretically, first by furthering

our understanding of gig economy platform companies as permissive potentates where some

control over the labour process is conceded while power remains centralised. Second, by

examining how gig economy platform companies exploit affordances of unilateral algorithmic

changes and their implications for labour and the labour process. Third, by exploring the

significance it has for workers' collective organisation. In so doing, this article asks: how

intraplatform changes in algorithmic management impact couriers' experiences of the labour

process; and how these technological‐workplace dynamics shape couriers' capacity to organise

collectively.

To address these questions, this study investigates two processes through which the gig

economy structures capital–labour relations. First, it intersects labour process theory (LPT)

with the conceptualisation of platforms as permissive potentates to explore the interplay

between algorithmic management strategies, labour process control and its impacts on working

conditions and workers' experiences (Gandini, 2019; Vallas & Schor, 2020; Veen et al., 2020).

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