Engineering Distributed Governance for Regional Prosperity: A Socio-Technical Framework for Mitigating Under-Vibrancy via Human Data Engines
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911537849958400 |
|---|---|
| author | Khanzada, Amil Takemoto, Takuji |
| author_facet | Khanzada, Amil Takemoto, Takuji |
| contents | 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 of 68% (R^2 = 0.683). We quantify an annual opportunity gap of 865,917 unrealized visits, equivalent to approximately 11.96 billion yen (USD 76.2 million) in lost revenue. We propose a dual-nudge governance architecture leveraging the DHDE to redistribute cross-prefectural flows and reduce economic leakage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_21639 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Engineering Distributed Governance for Regional Prosperity: A Socio-Technical Framework for Mitigating Under-Vibrancy via Human Data Engines Khanzada, Amil Takemoto, Takuji Computers and Society Machine Learning H.4.2; J.4; I.2.6; J.1 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 of 68% (R^2 = 0.683). We quantify an annual opportunity gap of 865,917 unrealized visits, equivalent to approximately 11.96 billion yen (USD 76.2 million) in lost revenue. We propose a dual-nudge governance architecture leveraging the DHDE to redistribute cross-prefectural flows and reduce economic leakage. |
| title | Engineering Distributed Governance for Regional Prosperity: A Socio-Technical Framework for Mitigating Under-Vibrancy via Human Data Engines |
| topic | Computers and Society Machine Learning H.4.2; J.4; I.2.6; J.1 |
| url | https://arxiv.org/abs/2603.21639 |