{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T20:52:03Z","timestamp":1768510323011,"version":"3.49.0"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T00:00:00Z","timestamp":1768176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Digital technologies have transformed the spatial organization of finance. As a result, geographic and virtual agglomerations co-exist. In this paper, we model the synergistic integration of geographic and virtual agglomerations within China\u2019s financial industry from a systems perspective. Using provincial panel data from 2011 to 2023, we develop an entropy-weighted coupling coordination model to measure the interaction between the two agglomerations. Furthermore, we employ spatial and convergence analyses to reveal their evolutionary characteristics. Our findings reveal three key results. First, financial geographic agglomeration shows an overall increasing trend, with regional levels ranked as follows: eastern region, northeastern region, western region, and central region. It exhibits significant positive spatial correlation and convergence characteristics. Second, financial virtual agglomeration also continues to strengthen, with regional levels ranked as eastern, central, western, and northeastern regions. Its convergence patterns display regional heterogeneity, and no significant spatial correlation is observed. Third, the coupling coordination degree between the two agglomerations has steadily improved nationwide and across all four major regions with convergent trends. By 2023, the eastern region has entered a stage of primary coordination, while the central, western, and northeastern regions remain in a near-dysfunctional state. In terms of driving patterns, most provinces are primarily driven by geographic agglomeration. Hunan, Hainan, and Guizhou are driven by virtual agglomeration, whereas Beijing, Anhui, Shandong, Guangdong, and Yunnan demonstrate a synchronized pattern driven by both agglomeration types. Overall, our findings highlight the systemic nature of financial agglomeration in the digital economy and enrich the theoretical understanding of financial dual-agglomeration synergy. They provide an analytical framework and empirical evidence for designing differentiated regional financial development policies.<\/jats:p>","DOI":"10.3390\/systems14010084","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T14:57:25Z","timestamp":1768229845000},"page":"84","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling the Synergistic Integration of Financial Geographic and Virtual Agglomerations: A Systems Perspective"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4987-7600","authenticated-orcid":false,"given":"Chunyan","family":"Guan","sequence":"first","affiliation":[{"name":"School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China"},{"name":"Department of Economics and Management, Yuncheng University, Yuncheng 044000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4759-0999","authenticated-orcid":false,"given":"Zhen","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3817-4239","authenticated-orcid":false,"given":"Anitha","family":"Chinnaswamy","sequence":"additional","affiliation":[{"name":"Aston Business School, Aston University, Birmingham B4 7ET, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5284-6051","authenticated-orcid":false,"given":"Jieyu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Economics and Management, Yuncheng University, Yuncheng 044000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,12]]},"reference":[{"key":"ref_1","first-page":"110","article-title":"Digital platforms and ecosystems: Remarks on the dominant organizational forms of the digital age","volume":"24","author":"Gawer","year":"2022","journal-title":"Innov. 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