Combining Quality of Life Indicators and AI Simulations for Human-Centric Governance

StatusVoR
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Authors
Wojtkiewicz, Katarzyna
Lyubashenko, Igor
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Date
2026-09
Publisher
Journal title
International Journal of Contemporary Management
Issue
1
Volume
62
Pages
Pages
160-171
ISSN
2449-8920
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Access date
2026-09-14
Abstract PL
Abstract EN
Purpose Although human-centric governance emphasizes subjective well-being, a structural gap persists between retrospective Quality of Life (QoL) measurement and anticipatory decision-making. This article addresses this gap by asking: how can validated QoL indicators and Large Language Model (LLM)-based simulations be systematically integrated within a coherent governance framework? Design/methodology/approach The study adopts a structured dual-track research design. Study 1 employs a quasi-experimental mixed-methods evaluation of a Norwegian-funded social innovation project using the “Impactometer,” grounded in OECD-aligned subjective well-being scales. Study 2 develops a proof-of-concept LLM-based simulation (Bielik model) applying the Ryff Psychological Well-Being Scale to synthetic professional personas in an organizational policy scenario. The two studies are analytically distinct but conceptually integrated within a governance cycle linking empirical grounding and anticipatory modeling. Findings Study 1 demonstrates an observed increase in life satisfaction (+0.8 points), accompanied by qualitative evidence of enhanced meaning, autonomy, and social connectedness. Study 2 shows that LLM-based simulation can generate differentiated and internally consistent well-being distributions across professional roles. However, simulation results establish plausibility rather than predictive validity and require empirical validation. Originality/value The article advances governance theory by proposing and empirically illustrating a hybrid model that bridges validated well-being measurement with structured AI-based simulation. This integration addresses the temporal mismatch in evidence-based policy and clarifies the methodological and ethical conditions under which AI can complement, rather than replace, human-centered governance.
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Keywords PL
Keywords EN
human-centric governance
subjective well-being measurement
anticipatory governance
large language model simulation
hybrid empirical–simulation framework
Keywords other
Sustainable Development Goals
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Except as otherwise noted, this item is licensed under the Attribution licence | Permitted use of copyrighted works
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