Assoc. Prof. Dr. Qin Liu | Big Data | Dean at Wuhan University of Technology | China
Big Data has become the defining pillar of the academic identity, research vision, and professional impact of Assoc. Prof. Dr. Qin Liu, a distinguished scholar in management science whose work integrates data-driven intelligence with innovation management, green entrepreneurship, and strategic decision-making. Assoc. Prof. Dr. Qin Liu received a Ph.D. degree in Management from Wuhan University, following a Master’s degree in Management and a Bachelor of Management from Wuhan University of Technology, forming a rigorous academic foundation that combines management theory, quantitative analysis, and applied policy research. Throughout his professional career, Assoc. Prof. Dr. Qin Liu has accumulated extensive experience in government industrial planning projects and enterprise management consulting initiatives, where Big Data methodologies have been applied to real-world policy evaluation, strategic planning, and organizational optimization. He has presided over major nationally funded projects, including a general project of the National Social Sciences Foundation and soft science projects supported by provincial science and technology departments, while also actively participating in multiple national, provincial, and municipal scientific research programs. The professional experience of Assoc. Prof. Dr. Qin Liu reflects a rare balance between academic leadership and applied consulting, enabling him to translate Big Data insights into actionable management and policy outcomes. The research interests of Assoc. Prof. Dr. Qin Liu center on Big Data–driven business analysis, intelligent management decision-making, green entrepreneurship, innovation management, digital empowerment, and sustainable industrial transformation, with particular emphasis on new energy vehicles, green innovation networks, and digital economy governance. His research skills include Big Data analytics, text mining, knowledge framework construction, multi-agent modeling, complex network analysis, policy evaluation, econometric modeling, and intelligent decision-support systems, all of which support interdisciplinary inquiry at the intersection of data science and management. In terms of academic achievements, Assoc. Prof. Dr. Qin Liu has published more than forty high-quality academic papers in leading international journals, authored one scholarly monograph, and edited three teaching textbooks, contributing substantially to both research advancement and talent cultivation. His publications demonstrate consistent influence in applying Big Data to energy policy, sustainability, innovation ecosystems, and intelligent manufacturing. Although formal awards and honors are embedded primarily within competitive national research grants and academic leadership roles, his recognition is evident through repeated selection as principal investigator for major projects and publication in top-tier journals. In conclusion, Assoc. Prof. Dr. Qin Liu stands as a forward-looking scholar whose sustained commitment to Big Data–enabled management science continues to shape intelligent decision-making, green innovation, and sustainable economic development in the digital era.
Featured Publications
Liu, Q., Wen, X., & Cao, Q. (2023). Multi-objective development path evolution of new energy vehicle policy driven by big data: From the perspective of economic–ecological–social. Applied Energy.
Liu, Q., Jia, M., & Xia, D. (2023). Dynamic evaluation of new energy vehicle policy based on text mining of PMC knowledge framework. Journal of Cleaner Production.
Chen, J., & Liu, Q. (2023). The green consumption behavior process mechanism of new energy vehicles driven by big data: From a metacognitive perspective. Sustainability.
Wang, S., & Liu, Q. (2023). Decentralized multi-agent collaborative innovation platform for new energy vehicle core technology breakthrough with digital empowerment: From the perspective of prospect theory. Heliyon.
Li, H. Y., Liu, Q., & Ye, H. Z. (2023). Digital development influencing mechanism on green innovation performance: A perspective of green innovation network. IEEE Access.
He, Z., & Liu, Q. (2023). The crossover cooperation mode and mechanism of green innovation between manufacturing and internet enterprises in digital economy. Sustainability.
Liu, Q., & Chen, G. (2022). Research on government countermeasure optimization of multi-agent complex network game in intelligent vehicle cooperative manufacturing driven by big data. Proceedings of the International Conference on Electronics, Communications and Information Technology.
Muazu, A., Yu, Q., & Liu, Q. (2023). Does renewable energy consumption promote economic growth? An empirical analysis of panel threshold based on 54 African countries. International Journal of Energy Sector Management.