Barriers to entry of gig workers in the gig platforms: exploring the dark side of the gig economy
| DOI | https://doi.org/10.1108/AJIM-08-2021-0235 |
| Published date | 20 January 2022 |
| Date | 20 January 2022 |
| Pages | 818-839 |
| Subject Matter | Library & information science,Information behaviour & retrieval,Information & knowledge management,Information management & governance,Information management |
| Author | Aastha Behl,K. Rajagopal,Pratima Sheorey,Ashish Mahendra |
Barriers to entry of gig workers in
the gig platforms: exploring the
dark side of the gig economy
Aastha Behl
Symbiosis International (Deemed University), Pune, India and
Jagannath International Management School, New Delhi, India
K. Rajagopal and Pratima Sheorey
Symbiosis Centre for Management and Human Resource Development (SCMHRD),
Symbiosis International (Deemed University), Pune, India, and
Ashish Mahendra
School of Management, IMS Unison University, Dehradun, India and
Department of Banking Technology, Pondicherry University, Puducherry, India
Abstract
Purpose –The alternative arrangements to traditional employment have become a promising area in the gig
economy with the technological advancements dominating every work. The purpose of this paper is to explore
the barriers to the entry of gig workers in gig platforms pertaining to the food delivery sector. It proposes a
framework using interpretive structural modelling (ISM) for which systematic literature review is done to
extract the variables. This analysis helps to examine the relationship between the entry barriers to gig
platforms. The study further proposes strategies to reduce the entry barriers in gig sector which would help to
enhance productivity and generate employment opportunities.
Design/methodology/approach –The study uses interpretive structural model (ISM) to ascertain the
relationship between various entry barriers of the gig workers to the gig platforms. It also validates the
relationship and understand the reasons of their association along with MICMAC analysis. The model was
designed by consulting the gig workers and the experts allied to food delivery gig platforms namely Zomato
and Swiggy.
Findings –It was observed that high competition, longer login hours and late-night deliveries are the
significant barriers with high driving power and low dependence power. Poor payment structures and strict
terms and conditions for receiving the incentives are interdependent on each other and have moderate driving
and dependence power. The expenses borne by the gig workers, such as Internet, fuel and vehicle maintenance
expenses have high dependence power and low driving power. Hence, they are relatively less significant than
other barriers.
Research limitations/implications –The study is confined to food delivery sector of India, without
considering other important sectors of gig economy for generalizing the framework. As the study is based on
forming an ISM framework through literature review only, it does not consider other research methods for
analysing the entry barriers to the gig platforms.
Practical implications –The study attempts to dig out the low entry barriers for gig workers in food
delivery platforms as there is a dearth of analysis of these factors. This study would weave them using ISM
framework to help the gig platforms overcome these barriers at various levels, thus adding to the body of
literature.
Originality/value –The study discusses the need for understanding relationship between the entry barriers
in the form of ISM model to identify the dependent and driving factors of the same.
Keywords Gig economy, Interpretive structural modelling, Food delivery sector, Entry barriers,
MICMAC, India
Paper type Research paper
1. Introduction
Digitalization and globalization have led to the growth of the gig economy across the globe to
support alternative work arrangements that have the advantage of flexible working hours.
With the advancement in technology, people’s preferences for jobs have changed from
AJIM
74,5
818
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2050-3806.htm
Received 16 August 2021
Revised 19 November 2021
31 December 2021
Accepted 1 January 2022
Aslib Journal of Information
Management
Vol. 74 No. 5, 2022
pp. 818-839
© Emerald Publishing Limited
2050-3806
DOI 10.1108/AJIM-08-2021-0235
traditional ones to freelance services (Todol
ı-Signes, 2017). The surge of Internet users and
the demand for food delivery services have created a broad opportunity for India’s sprawling
gig workers to work as per their own convenience. While the demand to access the desired
goods and services is transforming the urban economies, the gig workforce is devalued at its
core due to high competition and unemployment prevailing in the country (Davidson and
Infranca, 2015).
The era of growth-at-all-costs hasmade many gig workers unhappy becauseof increasing
discounts and coupons given to the customers (Ray et al., 2019) and market correction rates
prevailingin the gig sector. The monthly incomeof food delivery gig workershas plummeted,
which is unfair when the demand for such deliveries is at an inflection point (Kaine and
Josserand, 2019). Gig platforms have added delivery persons by thousands due to such high
demand,as this sector has very low entrybarriers. Since they are contractworkers who are not
even directly hired through the gig platforms, they are not covered in the ambit of labour
regulation and social security. They have no say in the wages and terms of work, and the
incentivesare strictly based on theirworking hours. The gig platformsoffer employee benefits
such as accident, m edical and life insurance but t he claim to such benefits hardl yr eaches them.
Additionally, the modest income received by the gig workers leads to frequent dropouts or
irregularityin the work scheduleof the gig workers(Be hl etal.,2021;Anwarand Graham, 2021).
It is important to understand that existing literature in this sector has failed to list the
entry barriers that gig workers face while choosing to work under this platform. Existing
studies focus on barriers and problems faced by the gig workers during their work or the
challenges faced by the gig economy in general (Tan et al., 2021;Koutsimpogiorgos et al.,
2020;Bregiannis et al., 2017). Although the studies mention that there are low entry barriers in
the gig economy, it is essential to portray these entry barriers concerning food delivery
platforms and their impact on the gig sector.
The COVID-19 crisis reveals the unprecedented growth of the gig sector due to the drastic
demand for jobs in the economy. Considering the dearth of literature and paucity of studies in
this field, the following are the objectives of the study:
(1) To explore the entry barriers for the gig workers in the gig platforms in India,
(2) To develop a theoretical framework for understanding the barriers that gig workers
face when entering the gig platforms and
(3) To recommend strategic measures to combat the restrictions and barriers for gig
workers in the gig platforms in India.
The present work aims to address the research gaps in the literature and highlights the
importance of gig workers in the food delivery sector, such as Zomato and Swiggy, with the
help of a hierarchical model. The study utilizes the ISM model that reveals the hierarchy of
theidentified barriersto entry in the gig sector basedon their interrelationship.The reachability
matrix and level partitioning is done by identifying the barriers and representing them in a
diagraph. There exist umpteen studies that discuss concepts related to the factors that make
gig workers choose gig jobs. However, the entry barriers are not addressed clearly in the
past literature. The relationship link to these barriers is also missing. Hence, the present
study addresses three important research questions, namely:
RQ1. What are the entry barriers for the gig workers in the gig platforms?
RQ2. What are the reasons for developing a theoretical framework to understand the
relationship between these entry barriers for the gig workers in India?
RQ3. What are the driving and dependent factors for these entry barriers in the gig
platforms?
Barriers to
entry of gig
workers
819
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