Abstract
<title>Abstract</title> <p> Modern consumer devices are converging into connected product-service systems that encompass tangible products, embedded software, mobile applications, cloud platforms, user profiles, telemetry data, and a network of after-sales support systems. This synergy also presents opportunities for operational value but entails greater risks to privacy, cybersecurity, reparability, and end-of-life (EOL) sustainability. Focus on investigating the relationship of the privacy-oriented lifecycle governance, AI–enabled lifecycle intelligence and MIS-driven lifecycle operation integration, and the secure and sustainable performance of the lifecycle of consumer devices in the U.S. The sample consists of 300 employees from the consumer products business dimension who were examined in a quantitative, cross-sectional manner. The examination of the complete dataset involves an analysis of reliability, a factor analysis, and the computation of correlations and regressions. Regression indicates 42.9% of the variance in secure & sustainable lifecycle performance is explained. MIS-based operational integration has the highest standardized regression coefficient (β = .377) with lifecycle performance, followed by privacy-oriented lifecycle governance (β = .326) and AI-powered lifecycle intelligence (β = .152). These outcomes reveal that the device firms can’t operate the privacy, AI, MIS, cybersecurity, and circularity projects independently. Rather, the key to secure and maintainable lifecycle performance lies in the integration of lifecycle privacy accountability, responsible AI–driven decision support, and converged MIS systems integrating records of product, firmware, warranty, repair, security, reverse logistics, and recycling. The business and information systems literature will benefit from this work through an empirical test of a lifecycle-based framework for the digital governance of consumer device ecosystems. <bold>JEL Classification:</bold> M15, M10, O33, Q56, K24 </p>