When Mobile App Data Fails: Data-Quality Problems, Trust-Related Responses, Post-Adoption Intentions, and Governance Expectations

Abstract

Mobile applications increasingly mediate access to consequential information, yet user-centred evidence on which data-quality dimensions matter most, which failures users encounter, and how such experiences relate to trust-related and post-adoption responses remains fragmented. This cross-sectional online survey study analysed 477 respondents. Descriptive statistics addressed perceived importance, failure types, and reported responses, while two chi-square tests examined whether prior negative data-quality experience was associated with responsibility attribution and support for stricter platform controls. Accuracy was rated important or very important by 95.0% of respondents, followed by timeliness (92.2%), completeness (89.7%), and understandability (84.1%). Negative experiences were reported by 260 respondents (54.5%); among them, inaccurate data were the most frequent problem (49.6%). In this routed subsample, 96.2% agreed that reliable data increased trust, 93.8% reported a reduced-use intention when data were poor, 90.0% reported non-recommendation, and 88.5% reported deletion willingness when inaccuracies were frequent. Prior negative experience was associated with responsibility attribution, χ²(2, N = 477) = 8.024, p = .018, Cramer's V = .130, and support for stricter platform controls, χ²(2, N = 477) = 7.199, p = .027, Cramer's V = .123. These modest associations indicate experience-contingent differences in governance expectations without supporting causal inference. The findings connect multidimensional data-quality perceptions with a trust-related response and stated post-adoption intentions and distinguish expectations directed toward developers from those directed toward platform operators.