Data collection and processing.

This study focuses on how technical and vocational education and training (TVET) institutions can effectively enhance educational quality to cultivate a globally competitive industrial workforce, addressing the World Banks projection that over 1.1 billion jobs worldwide will undergo skill transformations in the next decade due to automation, digitalization, and the green economy transition. Employing the fuzzy-set qualitative comparative analysis (fsQCA) method, the research conducts an in-depth analysis of developmental data from 16 Chinese TVET institutions to identify key factors influencing their competitiveness. The findings reveal that social service constitutes the foundation of high-quality vocational education. The social service capacity of TVET institutions is primarily reflected in vocational skill training, aligning with the core philosophy of Singapore Polytechnic’s “SkillsFuture” initiative. Through data analysis, a “social service-driven” development mechanism is identified: under similar conditions, TVET institutions achieve high-quality development by participating in government-funded vocational training programs. Simultaneously, two types of developmental bottlenecks are uncovered: (1) the “student skill level-international exchange constraints” type, where limited student proficiency and international collaboration hinder institutional progress; and (2) the “social service-technological R&D constraints” type, where weak social service delivery and technology transfer capabilities act as critical barriers. The outcomes provide a robust reference for global TVET stakeholders and policymakers to optimize industrial talent cultivation strategies and deepen integration into global value chains. The methodological framework also holds transferability to other domains, enabling regions to pinpoint success pathways and avoid ineffective measures.本研究聚焦于技术与职业教育与培训（Technical and Vocational Education and Training，TVET）机构如何有效提升教育质量，以培养具备全球竞争力的产业劳动力，同时回应世界银行的预测：未来十年内，全球将有超11亿个工作岗位因自动化、数字化与绿色经济转型而经历技能变革。本研究采用模糊集定性比较分析（fuzzy-set qualitative comparative analysis，fsQCA）方法，对16家中国TVET机构的发展数据开展深入分析，以识别影响其竞争力的关键因素。研究结果表明，社会服务是高质量职业教育的根基。TVET机构的社会服务能力主要体现在职业技能培训领域，这与新加坡理工学院“技能未来（SkillsFuture）”计划的核心理念高度契合。通过数据分析，本研究识别出一种“社会服务驱动型”发展机制：在条件相似的前提下，TVET机构可通过参与政府资助的职业培训项目实现高质量发展。同时，本研究还发现两类发展瓶颈：其一为“学生技能水平-国际交流约束”型，即有限的学生技能水平与国际合作阻碍了机构发展；其二为“社会服务-技术研发约束”型，即薄弱的社会服务交付能力与技术转化能力构成了关键障碍。本研究结果可为全球TVET利益相关方与政策制定者优化产业人才培养策略、深化融入全球价值链提供坚实的参考依据。该方法论框架同样具备跨领域迁移性，能够帮助各地区精准定位成功路径，规避低效举措。