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@article{199177,
        author = {Aditi Kadu},
        title = {Ride booking trends on can aggregators (Uber/Ola)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12451-12454},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199177},
        abstract = {One of the major factors in the Indian urban transportation digital transformation is the spread of the ride-hailing services. This study examines the key elements that define consumer preferences and booking behaviours on two most popular applications, Uber and Ola. Beyond the straightforward price comparison, the research uses the multi-dimensional methodology to assess the effects of algorithmic pricing models, digital interface design, perceived safety, service reliability, and engagement strategies. The study applies a mixed method; the combination of quantitative survey results related to urban commuters and qualitative findings based on interviews with users. The results will be used to develop an elaborate behavioural model that will categorise the users into decision-driving segments. The model is designed to offer actionable intelligence to platform operators to improve service delivery, better customer retention and negotiating the competitive nature of the dynamic mobility industry in India. The strategic recommendations are also given at the end of the paper in relation to the consumer segments identified.},
        keywords = {Digital Mobility, Platform Economy, Consumer Behaviour, Service Quality, Pricing Strategy, Urban Transportation, India},
        month = {April},
        }