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  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-title-group>
        <journal-title>π-Economy</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>π-Economy</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2782-6015</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">9</article-id>
      <article-id pub-id-type="doi">10.18721/JE.19409</article-id>
      <title-group>
        <article-title>Analysis of research on self-organization of economic clusters based on a bibliometric review</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Анализ исследований самоорганизации экономических кластеров на основе библиометрического обзора</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Polyakov</surname>
            <given-names>Ruslan</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-08-31">
        <day>31</day>
        <month>08</month>
        <year>2026</year>
      </pub-date>
      <volume>19</volume>
      <issue>4</issue>
      <fpage>157</fpage>
      <lpage>179</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://economy.spbstu.ru/userfiles/files/articles/2026/4/09_polyakov.pdf"/>
      <abstract xml:lang="en">
        <p>Increased international competition under conditions of chronic turbulence in the global economic system shifts the focus of modern research towards regionalization and the determinants of spatial concentration of economic activity. However, despite the significant amount of knowledge accumulated in the world, the phenomenon of self-organization of industrial clusters has not yet received sufficient theoretical understanding. The methodological complexity of its study gives rise to a conceptual gap between empirical data and existing models. Therefore, the aim of the study is to synthesize the results of a systematic review of the academic literature for 1980–2021 on methods and approaches to the analysis of industrial clusters with a focus on identifying studies in the field of their spatial self-organization. The presented study tests the hypothesis that clusters have properties of a self-organizing dynamic system that are fundamentally different from the prerequisites and mechanisms inherent in traditional theoretical models. The implicit nature of these processes is that the endogenous forces of spatial concentration, specialization and cooperation give rise to a spontaneous order that cannot be adequately described within the framework of dominant managerial or neoclassical approaches that emphasize externalities of scale or targeted strategic regulation. To this end, the paper applies multivariate bibliometric analysis to the 2000 most cited documents in the Scopus database from 1980 to 2021, including keyword frequency analysis, citation mapping, topic evolution, Bradford’s law, and the PRISMA flowchart for systematic review of publications. The study revealed that the fundamental issues of self-organization of clusters remain poorly understood and ignored in academic circles, and Russian research mainly follows the principles of Porter management school, which limits the development of cluster structures in the Russian Federation. The work constructed thematic maps and networks of keywords that confirm the direct connection of self-organization with agglomeration, concentration, and local production systems. The theoretical significance of the presented research lies in substantiating the need for a transition from “Porterianism” to the theory of a self-organizing cluster, and the practical significance is in systematizing methods for identification that contribute to the improvement of regional policy and cluster management strategies.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>bibliometric analysis</kwd>
        <kwd>industrial cluster</kwd>
        <kwd>self-organization</kwd>
        <kwd>new economic geography</kwd>
        <kwd>spa- tial concentration</kwd>
        <kwd>Porterianism</kwd>
        <kwd>cluster identification methodology</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <back>
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