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<p>With the global trend of rising demand for Chinese language education, this study investigated socio-ecological drivers of sustainable growth in the international Chinese training industry across 20 countries (10 developed, 10 developing). Using the gravity model and big data analytics, we quantified the impacts of microsystem (education cost), mesosystem (learner population), exosystem (bilateral trade), and macrosystem (diplomatic relationships) factors, with particular emphasis on privately operated for-profit institutions. Results demonstrated statistically significant positive effects across all dimensions, with bilateral trade emerging as the strongest predictor of the Chinese language training industry expansion. While diplomatic relationships exhibited weaker and context-dependent effects, education cost showed greater explanatory power in developed economies, whereas learner population growth potential was more pronounced in developing nations. Structural equation modeling revealed interdependent relationships between sectoral development and ecological variables. These findings provide actionable insights for stakeholders, suggesting that policy frameworks and corporate strategies should align with country-specific socio-ecological conditions to foster global sustainability of the Chinese language education.</p>

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Modeling the social-ecological factors influencing the sustainable development of the international Chinese language training industry: evidence from 20 countries

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月4日

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  • Chengang Zeng,
  • Zhi Geng,
  • Jiaye Tang

摘要

With the global trend of rising demand for Chinese language education, this study investigated socio-ecological drivers of sustainable growth in the international Chinese training industry across 20 countries (10 developed, 10 developing). Using the gravity model and big data analytics, we quantified the impacts of microsystem (education cost), mesosystem (learner population), exosystem (bilateral trade), and macrosystem (diplomatic relationships) factors, with particular emphasis on privately operated for-profit institutions. Results demonstrated statistically significant positive effects across all dimensions, with bilateral trade emerging as the strongest predictor of the Chinese language training industry expansion. While diplomatic relationships exhibited weaker and context-dependent effects, education cost showed greater explanatory power in developed economies, whereas learner population growth potential was more pronounced in developing nations. Structural equation modeling revealed interdependent relationships between sectoral development and ecological variables. These findings provide actionable insights for stakeholders, suggesting that policy frameworks and corporate strategies should align with country-specific socio-ecological conditions to foster global sustainability of the Chinese language education.