イスガンダロフ適応移行理論とイスガンダロフ移行脆弱性指数（ITFI）：AI-グリーン双方向移行時代におけるシステム的経済脆弱性の測定

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a theoretical foundation and composite index for measuring twin transition fragility, offering testable propositions for future empirical work.

🏢実務担当者:Offers a practical tool for assessing transition risks in portfolios and operations, aiding in disclosure and risk management.

🏛政策担当者:Suggests a framework for macroprudential supervision and adaptive policy design in the face of AI and climate transitions.

The simultaneous acceleration of artificial intelligence adoption and decarbonization is reshaping national economies through interconnected structural transformations. Existing research on the twin transition largely examines these processes separately and provides limited theoretical or empirical treatment of the systemic risks arising from their interaction. This paper addresses this gap by proposing the Isgandarov Adaptive Transition Theory (IATT), which argues that systemic fragility emerges when the combined pace of AI- and climate-driven transformation exceeds the adaptive capacity of labor markets, institutions, and households. The theory is formalized through four core principles and translated into five testable propositions. Building on this framework, the study develops the Isgandarov Transition Fragility Index (ITFI), a composite indicator integrating eight dimensions of transition vulnerability, including AI disruption, decarbonization pressure, workforce adaptability, institutional flexibility, climate-economic exposure, digital dependency, human resilience, and systemic connectivity. The index employs winsorized min–max normalization, entropy weighting with robustness checks against alternative weighting schemes, and an AI–green interaction term to capture compound transition effects. The framework is demonstrated using a fully documented synthetic panel covering 28 countries over 12 years as a methodological proof of concept. Results show that the index is computationally feasible, highly robust to weighting variation, and capable of distinguishing transition fragility across alternative scenarios. The proposed framework provides a foundation for future empirical research and offers practical applications for macroprudential supervision, sustainable finance, transition risk assessment, and adaptive economic policymaking.

• openaire https://doi.org/10.33774/coe-2026-th7f1first seen 2026-09-01 04:56:37 · last seen 2026-09-21 04:30:02