---
title: Independent Directors
url: https://www.ml-quant.com/papers/repec/spr-jahrfr-v-43-y-2023-i-3-d-10-1007-s10037-023-00198-1/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:spr:jahrfr:v:43:y:2023:i:3:d:10.1007_s10037-023-00198-1
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10037-023-00198-1%3Bh%3Drepec%3Aspr%3Ajahrfr%3Av%3A43%3Ay%3A2023%3Ai%3A3%3Ad%3A10.1007_s10037-023-00198-1
featured: 2024-03-06
citations: unknown
topic: ML & AI Methods
---


# Independent Directors

The research uses micro-scale job-household data and machine learning to analyze spatiotemporal patterns in Tokyo, highlighting urbanization and suburbanization trends.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10037-023-00198-1%3Bh%3Drepec%3Aspr%3Ajahrfr%3Av%3A43%3Ay%3A2023%3Ai%3A3%3Ad%3A10.1007_s10037-023-00198-1
- Identifier: RePEc:spr:jahrfr:v:43:y:2023:i:3:d:10.1007_s10037-023-00198-1
- Released: 2023-05-12
- First featured: Quant Letter No. 39 (2024-03-06): https://www.ml-quant.com/issues/2024-03-06/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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