International Journal For Multidisciplinary Research

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To What Extent Has Game Theory Explained the Pricing Strategies of Ride-Hailing Firms Like Uber and Ola in India (2015–2023)?

Author(s) Mr. Aarnav Agrawal, Ms. Merilyn Sunny
Country India
Abstract This paper investigates the extent to which game theory explains the pricing strategies of Uber and Ola in the Indian ride-hailing market between 2015 and 2023. The study employs a secondary-data-based approach, drawing on company financial reports, market analyses, and industry publications to identify strategic pricing patterns across three distinct phases: (1) Entry and Subsidy Wars (2015–2016), (2) Price War and Customer Retention (2017–2019), and (3) Post-COVID Surge Pricing and Algorithmic Adjustments (2020 onwards).

The findings indicate that game theory provides significant explanatory power in the early stages of market competition. The aggressive subsidy-driven strategies during Phase 1 align closely with the Prisoner’s Dilemma and Bertrand competition frameworks, while Phase 2 reflects dynamics consistent with repeated games, as firms engaged in prolonged tit-for-tat price reductions to secure market share. However, the relevance of classical game-theoretic models diminishes in Phase 3, as pricing decisions became increasingly algorithm-driven and influenced by external factors such as regulatory controls, fuel costs, and pandemic-related disruptions.

The paper concludes that game theory explains Uber and Ola’s pricing strategies effectively during the initial and intermediate phases but offers limited predictive value in a mature, technology-driven environment. Recommendations for future research include incorporating consumer behavior analysis and assessing the impact of emerging competitors like Rapido and BluSmart.
Field Business Administration
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-07-24
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.51662
Short DOI https://doi.org/g9vpkr
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