Algorithmic management and app‐work in the gig economy: A research agenda for employment relations and HRM

• Author: Anthony McDonnell,Ronan Carbery,James Duggan,Ultan Sherman
• Date: 01 January 2020
• Published date: 01 January 2020
• DOI: http://doi.org/10.1111/1748-8583.12258

REVIEW ARTICLE

Algorithmic management and app-work in the gig

economy: A research agenda for employment

relations and HRM

James Duggan | Ultan Sherman | Ronan Carbery |

Anthony McDonnell

Cork University Business School, University

College Cork, Cork, Ireland

Correspondence

James Duggan, Cork University Business

School, University College Cork, Cork, Ireland.

Email: jamesduggan@umail.ucc.ie

Funding information

Irish Research Council

Abstract

Current understanding of what constitutes work in the

growing gig economy is heavily conflated, ranging from con-

ceptualisations of independent contracting to other forms

of contingent labour. This article calls for a move away from

problematic aggregations by proposing a classification of

gig work into three variants, all based strongly upon key

technological features: app-work, crowdwork, and capital

platform work. Focusing specifically on the app-work vari-

ant, this article's more delineated focus on the textured

dimensions of this work proposes new lines of enquiry into

employment relationships and human resource manage-

ment. Examining the crucial role of algorithmic manage-

ment, we critically discuss the impact of this novel

mediation tool used by gig organisations for the nature of

employment relations within app-work, work assignment

processes, and performance management. In so doing, we

propose a series of research questions that can serve as a

guide for future research in this increasingly important field.

KEYWORDS

algorithmic management, app-work, employment relations, gig

economy, HRM, precarious employment

Received: 30 June 2017 Revised: 1 August 2019 Accepted: 5 August 2019

DOI: 10.1111/1748-8583.12258

114 © 2019 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/hrmj Hum Resour Manag J. 2020;30:114–132.

1|INTRODUCTION

Working arrangements are increasingly precarious, with independent contracting and temporary work becoming

more commonplace (Bonet, Cappelli, & Hamori, 2013; Harvey, Rhodes, Vachhani, & Williams, 2017). The emergence

of the “gig economy”—an economic system that uses online platforms to digitally connect workers, or “individual ser-

vice-providers,”with consumers—represents a new form of contingent labour (Harris, 2017). The “gig”business

model bypasses many of the regular responsibilities and costs of employment, leading to widespread legal ambiguity,

which has resulted in challenges as to whether workers should in fact be classified as employees (Collier, Dubal, &

Carter, 2017; Fabo, Karanovic, & Dukova, 2017). Discourse around work in the gig economy, or “gig work,”traverses

from the positive, with emphasis on the apparent autonomy and flexibility afforded to workers, to the negative, with

critics viewing it as a means by which businesses lower costs and erode employment standards and labour regulation

(Friedman, 2014; Stewart & Stanford, 2017).

The gig economy is disruptive to our traditional understanding of work, as its digital on-demand, or work-as-

required, principle sees personnel, as subordinate workers, becoming increasingly disposable (Todolí-Signes,

2017). It produces less long-term jobs, as people are hired to complete hyper-flexible “gigs,”working to com-

plete tasks for a defined, short period of time, often with low commitment existing between workers and orga-

nisations (Friedman, 2014; Harvey et al., 2017). Gig workers tend to be classified as independent contractors,

with the numbers legally employed by organisations operating in the gig economy significantly smaller (Todolí-

Signes, 2017). For example, Uber, a prominent “ride-hailing”or transportation gig organisation, currently has

almost four million drivers across 700+ cities worldwide (Madrigal, 2019) but only legally employs 22,000 in

total (Uber, 2019). Similarly, Lyft, another ride-hailing service, operates in 600+ locations across the United

States and Canada with almost two million drivers on the platform but employs less than 5,000 (McNeill, 2019).

Likewise, Deliveroo, a food-delivery company, has over 35,000 “riders”in 200 cities but only directly employs

an estimated 2,000 (Hurley, 2018).

Across Europe, Eurofound (2017) estimate that the number of people engaging in gig work as their main labour

market status makes up less than 0.5 per cent of all employment. The United Kingdom has the highest incidence of

gig work within Europe, with estimates of 4.4 per cent, or approximately 2.8 million people, engaged in this form of

work in 2017 (Lepanjuuri, Wishart, & Cornick, 2018). Of these, 25 per cent reported that some form of gig work was

their main job (Eurofound, 2017). Based on these figures, it is suggested that over 5 million people could be working

in the UK's gig economy by 2022 (Dupont, Hughes, Wolf, & Wride, 2018). The United States appears similar to

Europe, with figures of 0.5 per cent estimated to be participating in this form of work as of 2015 (Katz & Krueger,

2019). However, measuring the overall size of this new economy proves difficult because organisations are not

obliged to publish figures, and most gig working arrangements fall outside existing capabilities of labour market mea-

surement tools.

1

Also, despite boasting large worker numbers, little is known regarding how many individuals regu-

larly engage in this work, rather than being one-off or periodic workers.

Uncertainty exists in respect to what gig work does and does not involve, with different forms of contingent

labour commonly subsumed into gig classifications (Bernhardt & Thomason, 2017; Howcroft & Bergvall-

Kåreborn, 2019; Kuhn, 2016). This, we argue, is erroneous. Despite outward similarities with nontraditional

forms of work, key differences exist that warrant specific consideration (e.g., number of parties involved and the

influence of technology). Likewise, there is no one universal work classification or set of “rules”that can be

implemented in the gig economy. Individuals who occasionally boost income by renting out apartments on Air-

bnb, an online platform for property rental, are very different from those who make a living by working for

ride-hailing or food-delivery services like Uber or Deliveroo (Rozzi, 2018). Again, each of these is strikingly dif-

ferent from crowdworking platforms, such as Amazon Mechanical Turk, that connect businesses with skilled

freelance workers (Rozzi, 2018). Because work and conditions are hugely individualised across platforms,

employment relations and human resource management (HRM) implications along with policy and union

DUGGAN ET AL.115