Have Uber and Ola Met Promises Made to Drivers and Commuters?

In November 2019, the central government contemplated introducing a cap of 10% on the commission levied by app-based transport aggregators such as Uber and Ola and as well as a cap on their surge pricing. Ola and Uber started in 2013 and 2014 respectively, promising commuters taxi services that would be easy to use, affordable and comfortable, and taxi drivers fair wages and streamlined payments. Their model relied on deep discounting and large incentives to capture market share at a rapid rate while sacrificing on short- or medium-term profit. In India and other parts of the world, they made use of a legal vacuum in regulating the number and type of taxis allowed to operate, minimum wage payments and standard fare rates. 

Firms like Uber and Ola boast neo-liberal characteristics—they have limited fixed costs, given that they have few full-time workers and they do not own any taxis (reducing maintenance, repair and insurance costs), but can mobilise drivers, termed “independent contractors” and “partners,” based on demand from commuters. The two firms frame their relationship with drivers carefully to avoid abiding by laws about minimum wage, healthcare, vehicle insurance and job-loss security. Chaavi Sharma adds that even “in cases of harassment and rapes, companies have been found wanting, distancing themselves, and following a strategy of “risk transference” (Malin and Chandler 2016; Schor 2014), transferring risks and cost of risk on to their passengers.”

Many other large firms, such as Urban Clap, Zomato and Swiggy, have followed such a model, leading to calls for social security for workers, minimum wages according to car type and transparent information about earnings. Indeed, two of the 13 demands made by trade unions participating in the nationwide Bharat Bandh that took place on 9 January 2020 was the formalisation of workers who conduct “permanent perennial” work and provision of social security for all workers. 

This reading list offers an introductory understanding of the gig economy for transportation focusing on the impact it has had on workers and commuters. 

Behaviour Change Using Incentives 
Aditi Surie observes that technology companies intend to change people’s behaviour by offering incentives to drivers and low prices to commuters. Incentives, particularly in 2014–15, propelled drivers earning in many instances to about Rs 90,000 per month. 

This incentivisation shaped drivers’ investments in cars and multiple smartphones that enabled participation in the platform. The degree and measure of this investment and its concomitant debt has kept drivers on platforms for the most part, allowing the competing companies to create a stable base of service providers. But this has also allowed platforms to lower incentives for drivers: A change in policy that has drivers protesting, striking and demanding better terms of earning … In a curious if not unexpected move, both companies have decided that to protect the habits of Indian consumers and price behaviour is far more important than protecting drivers’ ability to earn and work. Low fares keep an ever-widening market of riders attached to the platforms, despite the degree of elasticity afforded the platform companies in the Indian market.

Surie points out that these protests highlight the gap between what Uber and Ola promise as earnings for drivers and their real earnings. The language that drivers use to frame their protests provides insight into their sense of labour and their relationship with their “employers.”

Drivers’ claims articulate their positions as defrauded consumers: They were sold on a particular guarantee that was undelivered. Transport platforms give drivers a curious mix of a consumer identity that depends on their work and labour. Such a mix amounts to hidden employment with no benefits, and a very constrained micro-entrepreneurship. 

Regulation Fails to Catch Up 
Workers across industries had high expectations for the Code on Wages, 2019 that sought to streamline four existing laws. Alok Prassana Kumar identifies that since India’s economic structures are rapidly changing, where even the definitions of employee and employer have shifted, it was important to take stock of these definitions in the legislation itself.  This is important because, as Kumar mentions, gig-platform “workers … enjoy little control over their work and receive a lot of direction through apps.”

[An] issue specific to minimum wages emerges in the context of the Code on Wages and gig workers in the platform economy. While the Code on Wages refers to those who are doing time work or piece work, what about those who are paid on the basis of tasks fulfilled? Even if interpretation gives a wide definition, how will their minimum wages be fixed in the absence of any guidance from the law?

Kumar argues that the labour code fails to provide clarity on these definitions and is likely to be redundant by the time it is put into practice. 

Far better, perhaps, would have been for the Code on Wages to acknowledge the workers of the gig economy and create separate provisions for them, keeping in mind the peculiar nature of work and the trend of economic and technological change in the country.

Why do People Drive for Ola and Uber? 
Surie, in another article, argues that the work conditions for drivers in the platform economy mirrors work conditions in the informal sector. These conditions include the absence of a guarantee of long-term wages, retirement and health benefits, and protection against layoffs. Surie investigates why, despite such conditions, people have joined platform companies as drivers.   

Primary research conducted in Bengaluru suggests that drivers—60% of those sampled—migrated to the city from districts which had declared drought conditions for 10 years out of the 16-year reference period. Informal, semi-skilled work with low barriers of entry—like driving— allows workers the option of manipulating flexible work options and the ability to switch between the most remunerative opportunities for work.

She also questions the importance given to the categorisation of “formal” label, given that “cannot accrue adequate social benefits that address and outweigh the costs of living in urban India (Motiram and Singh 2012).” She highlights multiple benefits of the platform economy system. 

Algorithm-based work brings with it the systematisation of work experiences, automation of processes and an aspect of trust for drivers with regard to the payment for services, and their income. Drivers, who were previously paid in disparate and irregular intervals of time, now have an assurance that a faceless company for whom they drive will pay them with regularity. Text messages and app-based (mobile applications) push notifications convey the drivers’ income earned and deductibles. Drivers have a constant flow of information that is regular and consistent, waylaying the several anxieties of contract-less work. 

Chaavi Sharma disagrees with Surie, arguing instead that Uber and Ola’s model have increased precariousness of drivers under the garb of autonomy. Financial liabilities, Sharma says, are a component of the Uber–Ola mode and have strained drivers ability to be autonomous. 

To become owner–drivers, the aspiring drivers pool in their life savings to get loans from banks. In 2016, Uber and Ola had tied up with different banks and finance companies to facilitate drivers to get loans that were collateral-free and had easy documentation processes. However, this changed in 2017, when banks pulled back these offers on the observation that incomes had declined and non-payment of instalments was on the rise. The State Bank of India had discontinued this practice entirely in Bengaluru (Gopakumar and Chakraborty 2017). There is, therefore, the pressure to drive more hours and sacrifice rest breaks to increase earnings and keep up with loan payments lest one loses the vehicle/asset that one has bought on high, but delusional hopes. It is forcing drivers to adopt all those practices that the companies promised they would alleviate for its associated drivers. Thus, Uber and Ola need to be held accountable, and their operations regulated.

Scientific, Rational and Transparent? 
In a separate article, Sharma points out that Uber and Ola’s pricing estimates and breakdowns need to be scrutinised despite claims of algorithmic and data-driven precision. 

Ola and Uber claim, based on their information technology enabled and GPS navigation powered apps that the rider is the master of his ride. However, resolution in cases of incorrect fare is ambiguous as the apps are expected to be unerring. Algorithms are abstract, thought to be scientific, rational and unbiased and therefore the state has seen no need for their regulation, thus making them ungovernable. Algorithms, unlike their transparency claim, are highly opaque.

She points out that while the firms bring periodic changes to their payment structures and incentives, far from consulting drivers about the changes, they often do not make this information transparent with drivers (and riders). 

The incentive structure ended and the one that restarted in 2018 is meagre, difficult to achieve and varies from driver to driver as told by two drivers of platform companies in 2018. There are different cars, different categories corresponding with different fare brackets and surge pricing for them. Nothing of this is available in the public domain. Despite the opacity, the city public believes in their claims of transparency, innovation, scientifically precision, rationality and unbiasedness due to their grounding in information technology.

Read more:
How Globalisation Has Diluted Workers’ Rights | EPW Engage, May 2019 
Economic Liberalisation, Work and Democracy | Nandini Gooptu, May 2007
Protection of Workers’ Wages in India: An Analysis of the Labour Code on Wages, 2019 | Nivedita Jayaram, December 2019
Politics of the Informal: Women’s Associational Life and Public Space in the Hills of Manipur | G Amarjit Sharma, February 2018