Karnataka’s uniform fare policy is a boon for customers, but does little for taxi workers

The government recently introduced a fare policy aiming for parity between aggregator (app-based) and other taxis. But workers' experiences reveal how inequalities and systemic barriers remain.
Image for representation
Image for representation

The Karnataka transport department’s February 2024 policy on uniform fares for aggregator (app-based) taxis and all other taxis is an encouraging step towards addressing disparities created by market-dominant platforms such as Ola Cabs and Uber. 

The policy is the latest among a number of notifications by the Karnataka transport department on regulations for the app-based taxi sector. In a first, the policy attempts to bring parity between the app-based and offline taxi sectors by setting the same base and per kilometre fares for both categories. It also looks at a novel aspect of regulating app-based platforms through the prohibition of surge pricing.

This article views the policy against workers’ experiences with platforms’ management and income distribution practices. While it is found that the policy may achieve its intended objectives of standardising fares for customers, it is also believed that in the process, the policy may unfairly harm taxi workers on platforms.

Datafied work management practices

First, while the policy prohibits surge pricing, it is silent on larger concerns: the platforms’ datafied work management practices around providing rides, setting worker earnings, and real time tracking. It is through these systems that platforms are able to control a vast workforce.

The Centre for Internet and Society (CIS) conducted surveys among 300 taxi workers, and found that workers were routinely marked on metrics such as ride acceptance and ratings. Over 74% of them reported that these had a significant impact on their work allocation and earnings.

Along with these metrics, earnings and work allocation are contingent on a large number of variables including the number of rides a worker completes, the hours they long, and the number of weeks they have been employed on the platform. Critically, they’ve all been optimised towards minimising the platform’s cost per worker by estimating the lowest payout at which workers remain logged on. 

Determinations of earnings and work allocation therefore go much beyond surge pricing practices. The transport department’s policy does not adequately account for these datafied work management processes. Even with uniform fares under the policy, workers would have to contend with unpredictable ride prices and locations, worsened by volatile commission rates. Unless these systems are brought under the regulatory ambit, platforms are likely to continue unfair work allocation and pricing practices and bring in further disparities compared to taxis that do not operate on datafied systems.

High fees and offloaded operational costs

Second, the policy fails to account for commissions and fees that platforms levy on workers. It also does not acknowledge operational costs that are offloaded onto workers.

Workers’ demands for a fair wage have considered commissions and charges, as well as offloaded expenses like fuel and vehicle maintenance. The policy disregards these demands. It does not place a cap on commissions. Instead, it only prescribes rates to be paid by the customer, without accompanying safeguards on minimum rates or fare percentages that must be paid to the worker.

This is a critical oversight. Workers in CIS’ surveys faced high commission charges, with a median of 25% of the fare, going up to 35% for some. Commissions are also not the only costs borne by workers. Workers also incurred a median monthly cost of Rs 16,500 on routine expenses, which further diminished their take-home earnings.

As we can see, standardisation of fares by no means guarantees standardisation of earnings for workers. The policy’s failure to recognise this leaves room for platforms to further increase costs for workers and generate revenue. It is important to mandate transparency on the worker-end of platform operations to curb such practices.

Diverse actors sustaining an asset-light business model

Third, the policy does not recognise the various actors and work arrangements on platforms. Platforms sustain their asset-light business models by tapping into pre-existing formal and informal networks. Workers access investments for vehicles through a number of work arrangements, including formal and informal contractors, fleet operators, and platform subsidiaries that enable leasing and financing, to name a few.  

Our survey highlighted the diversity of arrangements that actually existed outside the platform — while a majority were individual owners, over 30% of workers were engaged in rental, leasing, commission, or salaried arrangements.

These arrangements also translated to disparate earnings for workers. For instance, the median weekly take-home earnings for an individual owner were Rs 5,500, while the same were Rs 3,600 for a salaried worker.

Considering these disparities, how then would the policy decide on whom and how to regulate when multiple actors are involved? Here, it is important to introduce mechanisms on operational accountability for various actors, while also recognising that they are ultimately controlled by platforms themselves.

Calling for a worker justice lens to policy imaginations of parity

Policies such as the call for fare uniformity may well be one of many attempts to draw parity between aggregator platforms and other offline taxi firms. Yet, workers have barely featured in these conversations of transport policy, whether on parity or otherwise.

The fare policy has been welcomed by some workers’ organisations as fulfilling a key demand for uniformity. However, it still remains silent on actual systemic issues and impacts for workers on platforms. This is a pressing issue in light of how workers face the worst impacts of platform practices that extract value and create disparities. CIS’ surveys showed that workers worked over 84 hours a week whilst only earning a median of Rs 5,000. For over half of them, these earnings were not sufficient to cover even basic household expenses. Further reflecting their vulnerability, 28% of workers had access to workplace accident insurance, and an even lower 6% had access to health insurance, while 57% depended on the government for benefits like food rations.

Operational and algorithmic accountability within a policy agenda on labour and data rights are inextricably linked to curbing disparities driven by dominant aggregator platforms. There is a need therefore to ensure that uniform fare policies are not limited only to customers, but also consider potential impacts on workers.

Chiara Furtado and Nishkala Sekhar are researchers working on labour and technology at the Centre for Internet and Society (CIS). Aayush Rathi and Chetna VM provided critical inputs to this analysis.

Research data cited above is based on findings from surveys conducted at CIS.

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