Ruiyu ZHANG

Ruiyu ZHANG

About Me

I am a research assistant in the Department of Applied Social Sciences, The Hong Kong Polytechnic University, researching the fields of Organization Studies, Bureaucracy, and Computational Methods in Social Science.

Publications

  • “Sustainability of Small and Medium-Sized Enterprises in Hong Kong: Drivers and the Moderating Role of Social Network” (with Lin Nie and Wai-Fung Lam). Corporate Social Responsibility and Environmental Management. 2025. https://doi.org/10.1002/csr.3207

Our study examines what drives small and medium-sized enterprises (SMEs) to adopt sustainability practices, and how social networks shape these dynamics. Using survey data from 1,400 SMEs in Hong Kong, we find that internal drivers—such as responsibility, commitment, and a clear sustainability mission—and external pressures like regulation and customer demand significantly influence sustainability efforts. Crucially, our study shows that SMEs with stronger social network engagement benefit more from external drivers, especially in areas like environmental management, innovation, and social contribution. These findings highlight the need for policy approaches that not only provide support but also strengthen SME networks to enhance sustainability outcomes.

  • “Eco-efficiency as a Catalyst for Citizen Co-production: Evidence from Chinese Cities” (with Lin Nie, Ce Zhao, Xin Zhao). Preprint. 2025. Available at Research Square

In our study, we explored the relationship between eco-efficiency and the local governments’ engagement in collaborative environmental governance with citizens. By analyzing provincial-level data from China and employing advanced textual analysis methods, our findings reveal that localities with higher eco-efficiency are significantly more likely to adopt co-productive responses to environmental complaints.

  • “Enhancing Citizen-Government Communication with AI: Evaluating the Impact of AI-Assisted Interactions on Communication Quality and Satisfaction” (with Lin Nie). Preprint. 2025. Available at arXiv/SSRN

In our investigation of AI-assisted interactions, we sought to understand how artificial intelligence might elevate the quality of communication between citizens and civil servants. We compared traditional and AI-enhanced communication across diverse scenarios—from routine service requests to emergency concerns. Our analyses demonstrated that AI modifications can significantly improve key dimensions such as satisfaction, responsiveness, clarity, and trust.

Our study delved into the transformative ambitions of the double-hundred action programme, a reform designed to modernize China’s state-owned enterprises by expanding the pool of top executive talent beyond traditional cadres. Through extensive fieldwork and detailed ethnography at a selected enterprise, we explored how this policy is reshaping recruitment, performance evaluation, and remuneration practices. While our findings highlight strong support for the initiative and notable shifts in organizational dynamics, they also reveal that traditional influences endure, particularly in key board appointments. This work deepens our understanding of the delicate balance between progressive reform and longstanding institutional practices.

  • “Achieving Semantic Consistency: Contextualized Word Representations for Political Text Analysis” (with Lin Nie, Ce Zhao, Qingyang Chen). Preprint. 2024. Available at arXiv/SSRN

In our exploration of political text analysis, we set out to address the challenge of maintaining semantic stability over time. By comparing traditional static embeddings with contextual models using two decades of People’s Daily articles, our research evaluated how well each approach captures both enduring meanings and subtle semantic shifts. The results indicate that contextual models not only provide greater semantic consistency but also detect nuanced variations that static methods often miss.

Contact

Feel free to reach out via email: ruiyu.zhang@polyu.edu.hk