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AI-Empowered Volunteer Services: Practical Innovation of College Students' Intelligent Support for Shaoxing Textile City
DOI: https://doi.org/10.62381/H261320
Author(s)
Ziyu Meng, Yuhong Zhang, Long Wang
Affiliation(s)
Zhejiang Yuexiu University, Shaoxing, Zhejiang, China
Abstract
With the all-round development of digital China and culture tourism and commerce, traditional volunteer services in professional markets face challenges such as low management efficiency, inaccurate resource matching, insufficient international services, and weak incentive mechanisms. Shaoxing China Textile City serves as the research area, and this study develops an integrated model of "AI+volunteer service+international business service" based on the strengths of Business English majors and the nature of college students' volunteer services. Develop the four functional modules of intelligent matching, multilingual translation, service hour certification and resource scheduling to build an intelligent volunteer service platform for college students. the problems of language barriers in foreign exchange, unbalanced distribution of volunteer manpower and fragmented service experience in Textile City have been addressed by the platform. This study establishes an achievable and promote-worthy AI-empowered volunteer service model. Improve the international service level and urban governance of Shaoxing Textile City, and offer a practical case study for applied talent training and industry-university-research collaborative innovation in universities.
Keywords
AI Empowerment; College Students’ Volunteer Service; Shaoxing Textile City; International Service
References
[1] Calvino, F., & Fontanelli, L. (2026). AI users are not all alike: the characteristics of French firms buying and developing AI. Research Policy, 55, 105473. [2] Fan, H., et al. (2026). How moral judgment incongruence affects employee job crafting: the moderating roles of AI-generated ads' verisimilitude and creativity. Tourism Management, 113, 105333. [3] Huang, G. Q. I., et al. (2026). Responsible AI and human collaboration in tourism management: Ethical considerations and identity disclosure. Tourism Management, 113, 105315. [4] Jain, R., & Kumar, A. (2025). From what (motives) to what (outcomes) of relationships with artificially intelligent voice assistants. International Journal of Information Management, 85, 102953. [5] Lasarov, W., et al. (2026). How practitioners can leverage GenAI to bridge the research-practice gap. Tourism Management, 113, 105309. [6] Xu, X., et al. (2026). Empathy order effects on shaping GenAI online complaint management in tourism. Tourism Management, 113, 105304. [7] Yhee, Y., & Koo, C. (2026). Seeing AI as human or machine? Effects of transparency, valence, and readability on review summary helpfulness. Tourism Management, 113, 105305. [8] Zhai, X., et al. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 2021(1), 8812542.
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