Engineering Distributed Governance for Regional Prosperity: A Socio-Technical Framework for Mitigating Under-Vibrancy via Human Data Engines
Amil Khanzada, Takuji Takemoto

TL;DR
This paper presents a socio-technical framework called DHDE, adapted from biological crisis management, to combat under-vibrancy in declining regions by analyzing high-granularity data and optimizing regional economic flows using AI-driven decision support systems.
Contribution
It introduces the DHDE framework for regional economic optimization, validated with high-granularity data from Japan, and proposes a dual-nudge governance architecture to enhance regional prosperity.
Findings
Achieved 81% in-sample explanatory power and 68% out-of-sample predictive performance.
Quantified an annual opportunity gap of 11.96 billion yen in lost revenue.
Proposed a governance architecture to redistribute flows and reduce economic leakage.
Abstract
Most research in urban informatics and tourism focuses on mitigating overtourism in dense global cities. However, for regions experiencing demographic decline and structural stagnation, the primary risk is "under-vibrancy", a condition where low visitor density suppresses economic activity and diminishes satisfaction. This paper introduces the Distributed Human Data Engine (DHDE), a socio-technical framework previously validated in biological crisis management, and adapts it for regional economic flow optimization. Using high-granularity data from Japan's least-visited prefecture (Fukui), we utilize an AI-driven decision support system (DSS) to analyze two datasets: a raw Fukui spending database (90,350 records) and a regional standardized sentiment database (97,719 responses). The system achieves in-sample explanatory power of 81% (R^2 = 0.810) and out-of-sample predictive performance…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Smart Cities and Technologies · Global Urban Networks and Dynamics
