The Automotive Data-Equity Loop: Converting Telemetry into Consumer-Owned Resale Value Through Verifiable Digital Passports - Karishma Verma (International Journal of Computational and Experimental Science and Engineering, 2026)
The transformation of vehicles into software-defined platforms creates a fundamental trust gap between consumers and entities seeking detailed telemetry data. Traditional incentive models, including direct payments and feature personalization, fail to motivate sustained telemetric sharing because they cannot overcome consumer concerns about surveillance, fairness, and asymmetric value extraction. This article introduces the Automotive Data-Equity Loop, a socio-technical framework that reframes telemetry sharing from data extraction to asset protection by converting operational data into durable, consumer-owned verified credentials that enhance resale value. The framework operates through three interconnected phases: value creation during ordinary vehicle use, value crystallization through privacy-preserving conversion of raw telemetry into tamper-resistant cryptographic credentials, and value realization when verified history reduces buyer uncertainty in resale transactions. The hybrid asset conceptual model positions vehicles as composite assets integrating physical components with verifiable digital history layers, leveraging behavioral-economic principles, including loss aversion and endowment effects, to align long-term consumer interests with platform data requirements. The transparency slider interface operationalizes graduated consent through multi-level controls mapping sharing choices to certification outcomes, while purpose-bound certificates restrict secondary use by design. Comparative analysis establishes testable hypotheses predicting that asset value enhancement outperforms alternative incentive structures through increased perceived fairness and reduced exploitation concerns. The governance blueprint addresses multi-stakeholder trust through explicit role definitions for credential issuers, verifiers, and marketplace participants, alongside threat models addressing consumer gaming, forgery attacks, and marketplace pressure dynamics. Implementation requires empirical validation through controlled experiments measuring adoption rates, persistence duration, and depth of consent, complemented by observational market studies assessing effects on resale prices, transaction velocity, and buyer confidence indicators. The framework demonstrates how consumer-generated data ecosystems can align with autonomy and long-term value creation when systems treat individuals as asset owners rather than extractable data sources, with implications extending beyond automotive contexts to broader Internet of Things and smart asset domains.