Trades and Services

Trades and Services: Many studies outline structural inequalities between workers, clients and platforms, which leave the workers vulnerable to exploitative practices. Key challenges are dissatisfaction on earnings, ill treatment or unfair ratings by clients, algorithm led allocation with no way to choose locations or clients. This section is marred by inequalities favoring the clients, leaving little room for negotiation by the workers. Workers in these studies expressed vulnerability as they work, for instance, the estimation, assessment and the ratings of the work is left to the clients, with no redress mechanisms even when they raise their grievances on the platform. Workers have found solace in each other, through community groups to learn from each other, exchange ideas and occasionally share transportation to the work areas.

Find references for this section at the bottom of this page or see the PDF for in-text citations.

Local labor platforms give validity to workers. This is an advantage to workers because “Clients will treat you right because they know that you have someone behind you. It’s different than when you go to a client’s house alone looking for work, they don’t trust you” (Hunt et al. 2019, 66). Such platforms also have an entry point for new workers, unlike other traditional jobs where they “…don’t like new people, they have lots of politics…They don’t want to share their work with new people. They even said that they liked my work but nothing happened…So, I decided to join ServiceHelp” (Gupta 2020, 5). Workers expressed dissatisfaction with earnings in some jobs, claiming there is fair remuneration in short-term gigs. “I used to bring a business of about 1-1.5 lakhs a month, but I only used to get paid 25,000 no matter what. But now […] [i]f I do more work, I can earn more” (Raval and Pal 2019, 7). Furthermore, job allocation and earnings are usually determined by forces outside the workers’ domain.

With the platform it’s very uncertain, everything is uncertain. From the money you are going to earn to getting the booking itself and once you get the booking you don’t even know what to expect because you might find a house that has not been cleaned for two months (Hunt et al. 2019, 35).

Others reported lack of control over their earnings, stating, “Some clients really trouble…For example, one client said my work was good but gave me a bad rating…The client said that if you refund my money, I will improve your rating” (Gupta 2020, 6).

Workers are frustrated by unfair payment or allocation practices (underestimation).

Let’s say I have been booked for five hours [. . .]. It will be a big house that does not even tally with those five hours [. . .] but the client expects me to finish that job, so I am forced to add hours [. . .]. The client will be putting pressure on me to work fast, but if I work fast, I will get a bad rating attributed to not cleaning properly as the job was rushed. There is a serious problem there work. (Hunt et al. 2019, 41) 

Hard-to-track-or-rate work leads to an over-reliance on the client’s review, which often results in unfair ratings, “Clients know they can reduce ratings so they misbehave” (Gupta 2020, 6). Some clients also lack respect for workers. 

Those of us who work as housekeepers, we are disrespected a lot. They disrespect us a lot. They see us as if we are not learned. Someone talks to you rudely. The woman can give you clothes to wash and she has even left a pad on the panty for you to remove. Because she is seeing you are useless! (Hunt et al. 2019, 47) 

In some instances, workers lack ways to negotiate and even redress mechanisms.

I have been deactivated. It was only six months after joining ServiceHelp, my son fell very sick…I had to leave him and go to work because for three days, the hospital bill was amounting to INR 18,000. I did not have so much money… I went to the client in tension so I forgot the disposable sheet. The client got very angry. She told me not to do the job and just leave. The commission of INR 1,200-1,300 got deducted from my account so I ended up losing money. I didn’t earn anything and lost more (Gupta 2020, 6). 

Further to this are reports on unstable work, which make it difficult to plan time difficult. “A lot of people complain but they say the client wants to go work so they cannot change the time” (Hunt et al. 2019, 40). Also, unpaid travel costs are not always factored in the earnings, which may “eat” into workers’ earnings. Other workers experience insecurity as they travel.

Like now it’s winter and I stay in [area] . . . people are getting robbed every day. So 6 am it will be very dark, and for instance you will be having a booking for 7 a.m. which means I will have to wake up by 5 a.m. then I will take my child to crèche by 6 a.m. because at the crèche they open at 6 a.m. I will then go to take whatever that I will take but it’s not safe to move from my house to the school because it will be very dark so I do not want a 7 am booking because it’s a risk. I can’t risk my life for ZAR 150; it won’t work (Hunt et al. 2019, 40).

These structural inequalities between workers, clients, and organization policies exacerbate workers’ low confidence and prohibit them from demanding explanations for penalties or low ratings (Raval and Pal 2019).

Another issue that is confusing is this word of “independent contractor”—we do not know what it means or which company we are working under because when we go to clients we are under the platform but when we go to the platform with our issues they say they are not responsible for us. This is bothering us, we don’t know where we stand (Hunt et al. 2019, 46).

Some workers have sought solace in online communities, to learn from each other, find support, feel a sense of belonging, and occasionally arrange to share transport (Hunt et al. 2019; Raval and Pal 2019).


Gupta, Shruti. 2020. “Gendered Gigs: Understanding the Gig Economy in New Delhi from a Gendered Perspective.” In Proceedings of the 2020 International Conference on Information and Communication Technologies and Development, 1–10. ICTD2020. New York, NY: ACM.

Hunt, Abigail, Emma Samman, Sherry Tapfuma, Grace Mwaura, Rhoda Omenya, Kay Kim, Sara Stevano, and Aida Roumer. 2019. “Women in the Gig Economy: Paid Work, Care and Flexibility in Kenya and South Africa.” London, UK: Overseas Development Institute.

Raval, Noopur, and Joyojeet Pal. 2019. “Making a ‘Pro’: ‘Professionalism’ after Platforms in Beauty-Work.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 1–17.