DrMengyao Fu

Mengyao’s research agenda centers on developing a nuanced and analytically rigorous understanding of how emerging digital technologies shape  digital marketing, financial innovation and sustainable innovation, with particular attention to their behavioral, strategic, and societal implications. Her work is organized around three interrelated research streams that collectively constitute the core of her scholarly contributions:

• Digital Marketing via emerging technologies (AI, VR, blockchain, and Web3) - focuses on the effectiveness of digital marketing strategies, with an emphasis on product placement and live-streaming commerce. It explores how content design, platform affordances, and social cues shape consumer attention, engagement, and persuasion in increasingly interactive and data-rich marketing contexts.

• Financial Innovation and FinTech Ecosystems - investigates how FinTech innovations, particularly cryptocurrencies, blockchain-based assets, and decentralized platforms, reshape investment behaviors and market dynamics. Specific attention is given to cryptocurrency investment decisions and hoarding behavior driven by speculative motives in the NFT market, offering insights into price volatility, risk perception, and participation incentives in digital asset ecosystems.

• Sustainability Ecosystems and Emission Trading Systems - explores the intersection of digital technology and sustainability, focusing on how digital innovations support the design, governance, and effectiveness of emission trading systems.

Together, these streams reflect a coherent program of research that elucidates the multifaceted roles of digital technologies in transforming innovation processes, market structures, and societal outcomes.

Prospective Master's and PhD students are welcome to enquire about research opportunities in digital marketing, financial technology, blockchain and Web3 ecosystems, AI-enabled digital innovation, sustainability and emissions trading systems, as well as computational social science approaches involving machine learning, large language models, network analysis, and online experiments.