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<p>This article presents a methodological approach employing Emerging Hot Spot Analysis (EHSA) to track the life cycles of clusters of inventive activity. Evolutionary Economic Geography seeks to elucidate the spatial development of economic activity by analyzing past formations and their impact on current and future trends. We enhance this literature by offering an explanation of cluster life cycles through EHSA. EHSA is a spatial statistical methodology that integrates Getis-Ord Gi* and Mann–Kendall trend assessments to examine spatiotemporal variability. We analyze inventive activity utilizing Japanese patent data from 1980 to 2020 across the chemical, mechanical, computers and communications, and electrical and electronics broad technological categories. EHSA provides a statistical test to analyze the stages of a cluster's life (emergence, growth, maturity, and decline) by finding patterns like <i>new</i>, <i>intensifying</i>, <i>persistent</i>, or <i>diminishing</i> hot/cold spots. Results indicate varying trajectories among technology categories: chemicals demonstrate post-growth decline; mechanicals are stable and expand; computers and communications remain confined to metropolitan areas; and electrical and electronics sectors bifurcate. The research underscores EHSA's efficacy in delivering a reproducible and flexible approach to visualize and comprehend clustering dynamics from spatiotemporal data, hence facilitating informed policymaking. Nonetheless, it recognizes constraints, as cluster evolution encompasses more than mere agglomeration, indicating the need for future integration with network analysis and qualitative data for a thorough comprehension.</p>

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A methodological framework for tracing cluster life cycles: emerging hot spot analysis in evolutionary economic geography

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月1日

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  • Sebastián Baeza-González,
  • Natsuki Kamakura

摘要

This article presents a methodological approach employing Emerging Hot Spot Analysis (EHSA) to track the life cycles of clusters of inventive activity. Evolutionary Economic Geography seeks to elucidate the spatial development of economic activity by analyzing past formations and their impact on current and future trends. We enhance this literature by offering an explanation of cluster life cycles through EHSA. EHSA is a spatial statistical methodology that integrates Getis-Ord Gi* and Mann–Kendall trend assessments to examine spatiotemporal variability. We analyze inventive activity utilizing Japanese patent data from 1980 to 2020 across the chemical, mechanical, computers and communications, and electrical and electronics broad technological categories. EHSA provides a statistical test to analyze the stages of a cluster's life (emergence, growth, maturity, and decline) by finding patterns like new, intensifying, persistent, or diminishing hot/cold spots. Results indicate varying trajectories among technology categories: chemicals demonstrate post-growth decline; mechanicals are stable and expand; computers and communications remain confined to metropolitan areas; and electrical and electronics sectors bifurcate. The research underscores EHSA's efficacy in delivering a reproducible and flexible approach to visualize and comprehend clustering dynamics from spatiotemporal data, hence facilitating informed policymaking. Nonetheless, it recognizes constraints, as cluster evolution encompasses more than mere agglomeration, indicating the need for future integration with network analysis and qualitative data for a thorough comprehension.