Trust, Privacy, and Transparency in Multi-Service Platforms: A Study of India’s Super Apps
Keywords:
Super Apps, Trust,, Privacy, Transparency, Trust Spillover, AI, DPDP, REFLECT Framework,, Dark Patterns, User Experience, IndiaAbstract
India’s super apps are growing fast. Platforms like PhonePe, Paytm, Tata Neu, and Jio
have layered payments, shopping, travel, and entertainment into a single application,
building directly on the scale of UPI adoption. As AI features chatbots, personalised
recommendations, fraud detection get embedded into these platforms, questions
of trust, privacy, and transparency become harder to sidestep.
This study looks at how Indian users aged 18–45 perceive trust, privacy, and
transparency within AI-enabled super apps and specifically, whether trust in one
service bleeds over to others on the same platform. Using a structured questionnaire
(N = 50) and the REFLECT Ethical UX Framework, four hypotheses were tested. Three
findings stand out: a moderate-to-strong trust spillover effect across all AI feature pairs
(Pearson r = 0.533–0.742, all p < 0.001); a privacy paradox where AI convenience (M =
3.82) and data concern (M = 3.90) co-exist; and a clear user demand for transparency,
with 80.0% of respondents saying they would share more data if given honest
explanations and genuine control. The study also finds serious failures in the Legibility
and Consent dimensions of current super app interfaces, and proposes three design
interventions aligned with India’s Digital Personal Data Protection (DPDP) Act 2023
and the 13 dark patterns prohibited by the Central Consumer Protection Authority
(CCPA).
