Governance-Driven Sustainovation in Heavy Manufacturing: Balancing AI, Circularity, Quality, and Managerial Judgement
Year: 2026
Type: article
Abstract: This presentation introduces a governance-driven sustainovation framework for heavy manufacturing, examining how AI and data-enabled support, circularity, quality governance and managerial judgement can be integrated within an accountable decision system. Using an anonymised, practice-informed manufacturing case, the framework distinguishes between different forms of evidence and their corresponding decision authority. It proposes an evidence-confidence lens for evaluating what verified, compliance-based, diagnostic and AI-supported evidence can legitimately support in industrial decision-making. The presentation was delivered at the EXEED Multidisciplinary International Research Conference 2026 (EMIRC'26) on 8 August 2026. It received the Outstanding Research Award, securing Second Runner-up in Theme A: Ethical Leadership, Sustainable Innovation, and Future-Ready Organizations. The framework is conceptual and case-informed and does not claim statistical validation across firms.
Author: Bithra, Navneet Kumar
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7203722904
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