RCE- Emerging Technologies and Innovation (RCE-ETI)
Research areas and priorities
We conduct interdisciplinary research spanning business, finance, accounting, marketing, operations and information systems, empowered by artificial intelligence, machine learning, large language models and big‑data analytics.
- Artificial intelligence, data analytics and intelligent decision-making
We study how artificial intelligence, machine learning, large language models, data analytics, and related technologies can be developed and applied to business and economic problems.
- FinTech, digital finance and financial innovation
AI and machine learning are applied to asset pricing and volatility forecasting. We explore FinTech innovation covering blockchain and tokenised assets, investigate digitalisation and digital transformation within finance and accounting domains, conduct textual analysis and large‑language‑model‑driven research, and advance big‑data analytics and information‑system‑related studies.
- Technology innovation, strategy and entrepreneurship
We examine the links between technology development and business strategy. We investigate technology adoption, innovation management, venture capital and entrepreneurial decision‑making.
- Digital transformation and business applications
We examine how digital technologies transform business processes, organisational practices, and interactions with customers and other stakeholders.
- Emerging applications and smart systems
The Cluster also supports interdisciplinary research into emerging technology applications in areas such as smart mobility, healthcare, industrial systems, and other technology-enabled services.
Key methodologies
- Large language models: sentiment analysis, tone detection, text similarity, readability measurement
- Data mining: structured data (financial, business, government public datasets); unstructured data (news, corporate announcements, policies, social‑media content)
- Machine learning/deep learning/transfer learning: addressing small‑sample and data‑imbalance challenges
- Modelling work: forecasting, valuation, optimisation, firm‑performance evaluation, technology‑adoption assessment
Cross-school research priority
A central priority of the Cluster is to develop cross-school research projects that combine technological capabilities with expertise in business and social sciences.
In particular, the Cluster seeks to build sustained collaboration with the Academy of AI and Advanced Technology, creating opportunities for researchers to jointly develop new methods, applications, datasets, and research projects at the intersection of AI and business.
This cross-school approach allows the Cluster to connect:
AI and computing → data and technology → business and economic Applications → real-world Impact
Research activities and opportunities
Research activities
The Cluster provides a platform for researchers, students, and industry partners to engage in interdisciplinary research and knowledge exchange.
Research opportunities
Cross-School Research
The Cluster is developing new opportunities for researchers across XJTLU to work together on emerging technology and business research.
Particular emphasis is placed on collaboration between IBSS and the Academy of AI and Advanced Technology, including:
- Joint research projects
- Interdisciplinary research teams
- Joint grant applications
- AI and data-driven business research
- Joint seminars and workshops
- Shared research datasets and analytical resources
- Interdisciplinary student research projects
The Cluster also welcomes collaboration with researchers from other schools and disciplines where emerging technologies intersect with business, economics, management, engineering, and social science research.
Student research and industry projects
The Cluster creates opportunities for undergraduate, postgraduate, and research students to gain experience through:
- Research projects
- Interdisciplinary projects with other schools
- Company-sponsored projects
- Quantitative finance and trading projects
- AI and data analytics projects
- Consulting and applied research
- Industry internships
- Research assistant opportunities
Students may work with academic staff and industry partners on real-world problems involving AI, FinTech, data analytics, digital transformation, and emerging technologies.
Research seminars and workshops
The Cluster organises and supports:
- Research seminars
- Academic workshops
- Interdisciplinary research meetings
- Industry seminars
- Technology and innovation forums
- Conferences and special research events
These activities bring together researchers from different disciplines and provide opportunities to discuss new technologies, research methods, emerging research questions, and industry developments.
Industry engagement and professional development
The Cluster works with companies and professional organisations through:
- Joint research projects
- Industry consulting
- Company visits
- Executive education
- Professional training
- Industry workshops
- Technology and digital transformation programmes
Existing activities have included training and knowledge exchange in areas such as Python and data analytics, large language models, accounting analytics, digitalisation in financial services, digital marketing, and quantitative trading in the AI era.
Historical events
- Future mobility experiences: Insights from preferences over different future mobility situations in China
Speaker: Dr. Juhyun Lee, Assistant Professor, Urban Planning and Design, XJTLU
Date: 26 September, 2024
- Heterogeneous Networks and Startups’ Subsequent Financing: Theorization Based on Machine Learning Algorithm
Speaker: Dr. Jin Chen, Associate Professor, University of Nottingham Ningbo China
Date: 22 October, 2024
- Mitigating Supply Disruptions with Endogenous Capacity Priority
Speaker: Dr. Jiahua Zhang, Associate Professor, Dongbei University of Finance and Economics
Date: 24 October, 2024
- Enhanced coupling approach to demand prediction and repositioning in shared autonomous vehicle systems
Speaker: Dr. Dongyao Jia, Associate Professor, Xi’an Jiaotong Liverpool University
Date: 31 October, 2024
- Labor Income Share and Enterprise Innovation: Evidence from the Social Insurance Law
Speaker: Prof. Haoran Peng, Professor, Sun Yat-sen University
Date: 11 November, 2024
- Automated Decision-Making Systems: How the Accounting Profession Can Contribute Toward Ethical and Responsible Practices
Speaker: Dr. Arif Perdana, Associate Professor, Monash University
Date: 28 November, 2024
- AI Empowerment and Flexible Labor Supply: Evidence from an Online Delivery Platform
Speaker: Prof. Xianghua Lu, Professor, Fudan University
Date: 5 December, 2024
- Blockchains for Environmental Monitoring
Speaker: Dr. Guojun Wang, Associate Professor, Shanghai Normal University
Date: 20 December, 2024
- From Econometrics to Machine Learning: Transforming Empirical Asset Pricing
Speaker: Dr. Chuan Shi, Assistant Professor, Chinese University of Hong Kong, Shenzhen
Date: 21 April, 2025
- Crowdsourced Earnings Forecasts: Implications for Sell-side Analysts’ Earnings Forecasts Strategies
Speaker: Dr. Wanyun Li, Assistant Professor, Xiamen University, Institute for Financial & Accounting Studies
Date: 24 April, 2025
- Embracing the Opportunities of Humanoid Robots
Speaker: Mr. Roy Lin, Vice President, UBTECH Robotics Co., Ltd
Date: 25 April, 2025
- CBDC and Banks’ Disintermediation in a Portfolio Choice Model
Speaker: Dr. Huifeng Chang, Assistant Professor, Fudan University
Date: 29 April, 2025
- The Boundary of Open Data: Implications for Financial Market and Real Efficiency
Speaker: Zhigang Qiu, Professor, Renmin University of China
Date: 9 May, 2025
- Integrating Generative Artificial Intelligence and Humans under Uncertainty
Speaker: Dr. Du Liu, Assistant Professor, East China Normal University
Date: 29 May, 2025
- The Value of Payment Convenience: Evidence from Households Investment in Money Market Funds
Speaker: Dr. Junli Zhao, Lecturer, Bayes Business School
Date: 3 June, 2025
- Data Breach Disclosure Laws and Corporate Tax Planning Activities
Speaker: Dr. Yanlei Zhang, Associate Professor, Copenhagen Business School
Date: 5 June, 2025
- Leveraging Text-based Nudging to Enhance Patient Acceptance and Compliance of Artificial Intelligence Care Management: Evidence from a Randomized Field Experiment
Speaker: Dr. Siliang Tong, Assistant Professor, Nanyang Technological University
Date: 16 July, 2025
- Finding the Impacts of Different Orders: Evidence Based on a Big Brokerage in China
Speaker: Dr. Ya Gao, Associate Professor, Dalian University of Technology
Date: 26 September, 2025
- Racial Disparities in the U.S. Mortgage Market: Evidence from Data Privacy Legislation.
Speaker: Dr. Xiangyu Lin, Assistant Professor, Nankai University
Date: 30 October, 2025
- Social Learning and Sentiment Contagion in the Bitcoin Market
Speaker: Prof. Bing Han, Professor, University of Toronto
Date: 6 November, 2025
- Do Unlucky Days Affect Investors’ Risk Perceptions? Cross-Country Evidence from IPO Returns
Speaker: Dr. Jing Zhao, Associate Professor, Hong Kong Polytechnic University
Date: 19 November, 2025
- Invisible Threats, Visible Losses: LLMs-Analysed Supply Chain Cybersecurity Risk and Corporate Product Market Performance
Speaker: Prof. Jia Liu, Professor, University of Portsmouth
Date: 25 November, 2025
- Housing and Household Portfolio Choices: Evidence Based on Dutch Population Data
Speaker: Dr. Shuai Fang, Assistant Professor, Soochow University
Date: 12 December, 2025
- Risk Factor Similarity and Economic Links
Speaker: Dr. Bei Chen, Assistant Professor, Shanghai International Studies University
Date: 8 January, 2026
- Workshop on Collaborative Research Initiatives
Date: 25 September, 2024
- 2025 XJTLU Derivatives and FinTech Workshop
Date: 17 May, 2025
- The 4th International Workshop: Chinese Development Model
Date: 4 July, 2025
- 2025 Conference on Accounting and Finance Research and Education in the Era of Rapid Technological Advances
Date: 3 September, 2025 – 4 September, 2025
- Inter-Collegiate Workshop on Academic Collaborations
Date: 27 May, 2026
- 2026 XJTLU Derivatives and FinTech Workshop
Date: 13 June, 2026
Research partners and collaborations
Cross-school collaboration at XJTLU
Strengthening collaboration across XJTLU is a key strategic priority of the Cluster.
The Cluster aims to serve as a bridge between IBSS and technology-focused schools, particularly the Academy of AI and Advanced Technology, bringing together complementary expertise in AI, computing, data science, finance, economics, management, accounting, marketing, and operations.
Potential areas of collaboration include:
- AI and financial markets
- Large language models and business applications
- Intelligent decision-making
- AI-enabled healthcare
- Digital transformation
- Data-driven management
- FinTech and digital finance
- Smart systems and mobility
- Technology innovation and entrepreneurship
Academic Collaborations
The Cluster has developed research connections with universities and research institutions in the UK, Europe, Asia, Australia, and North America.
Examples of collaborative research include projects with:
- University of Bath
- Lancaster University
- University of Macau
- Fudan University
- University of Science and Technology of China
- Shenzhen University
- City University of London / Bayes Business School
- Monash University
- University of North Texas
- Illinois State University
- Newcastle University
- University of Edinburgh
- Aix-Marseille University
The Cluster seeks to expand these networks through joint research, international projects, seminars, workshops, and grant applications.
Industry collaborations
The Cluster works with companies and professional organisations across finance, FinTech, technology, consulting, retail, healthcare, and other sectors.
Industry engagement includes:
- Joint research and applied projects
- Industry consulting
- Data analytics and AI projects
- Digital transformation projects
- Financial technology and quantitative finance
- Corporate training and executive education
- Student internships and company projects
The Cluster has engaged with financial institutions, securities firms, FinTech companies, technology companies, professional organisations, and other industry partners.
About
Who we are
The Research Cluster of Excellence in Emerging Technologies and Innovation (ETI) is a cross-disciplinary research platform that connects business, technology, and emerging fields across Xi’an Jiaotong-Liverpool University (XJTLU).
The Cluster brings together researchers from accounting, economics, finance, management, marketing, operations, information systems, and related disciplines to investigate how emerging technologies are transforming businesses, markets, organisations, and society. A key strategic priority is to strengthen collaboration across schools and disciplines within XJTLU, particularly with the Academy of AI and Advanced Technology and other technology-focused schools.
By connecting expertise in artificial intelligence, data science, computing, engineering, and emerging technologies with business and social science research, the Cluster aims to develop interdisciplinary research that addresses both technological opportunities and real-world business and economic challenges.
Vision
To establish a leading platform for emerging technologies and innovation in business research. By bringing together strengths in research, education and industry engagement, we aim to promote innovation and the application of cutting‑edge technologies in interdisciplinary fields.
Mission
The Cluster aims to: