This study aims to explore how users in Bangladesh perceive and use popular ride-sharing platforms such as Uber, Pathao, and inDrive, compared to informal ride systems where riders and passengers connect without app mediation. Through surveys and interviews with both riders and passengers, the research will examine factors influencing platform choice, satisfaction levels, and desired improvements.
A key focus of the study will be to analyze gender-based differences in adoption and perception, particularly investigating the lower participation of female users in ride-sharing services. It will identify whether issues of safety, convenience, cost, or trust are major barriers and suggest design-level interventions to improve inclusivity.
By combining quantitative and qualitative methods, the study will offer a holistic understanding of the ride-sharing ecosystem in Bangladesh and propose actionable design recommendations to make such platforms safer, more inclusive, and user-friendly.
Ride-sharing platforms have transformed urban mobility in Bangladesh, yet issues of safety, gender inclusivity, and trust continue to affect user adoption. Understanding these behavioral and perceptual factors is crucial for both policymakers and platform developers. The findings will contribute to Human-Computer Interaction (HCI), gender-inclusive design, and transportation system research, offering evidence-based insights that can guide future feature design and policy reform.
Future extensions of this study may include cross-country comparisons, integration of behavioral analytics from app usage data, or the development of a prototype “inclusive ride-sharing” model focusing on safety feedback loops and gender-sensitive features. The work could also expand to explore AI-driven trust mechanisms and recommendation systems for safer ride-matching.
