Assoc. Prof. Anna Yumiao Tian, Xi’an Jiaotong-Liverpool University, China

Anna Yumiao Tian is Associate Professor in IBSS at XJTLU. Prior to this, she was holding a permanent lectureship at Sheffield Business School, Sheffield Hallam University after obtaining her Ph. D in Teesside University with a full scholarship. Her Ph. D work was awarded Doctoral Fellowship by Northern Leadership Academy with less than 30 successful candidates across UK. Her research interests mainly sit in mergers and acquisitions, green economy, sustainability and AI implementations with humans. She has published academic papers in leading journals such as Human Resource Management, International Journal of Operations and Production Management, Journal of Business Research, Industrial Marketing Management, Journal of Managerial Psychology, Journal of Business Ethics, International Marketing Review, Multinational Business Review. She is also an honorary Ph. D supervisor in University of Liverpool; and Fellow of Higher Education Academy in UK.

Title: Taichi versus Boxing: A Multi-Phase Model of Reverse Knowledge Transfer in Chinese-UK AI Technology Acquisitions
Abstract: Emerging market multinationals increasingly acquire Western tech firms to overcome latecomer disadvantages in the AI hardware race, specifically within the semiconductor manufacturing sector. Yet, reverse knowledge transfer (RKT) research remains predominantly static and Western-centric. Through a qualitative, longitudinal study involving 40 in-depth interviews across a Chinese parent firm and its UK semiconductor subsidiary, we investigate how tacit engineering logic successfully transfers across borders. Findings reveal a four-phase interactive process, distilled into a "Boxing vs Taichi" metaphor. The UK subsidiary deploys a defensive "Boxing" strategy, using access controls and contractual clauses to shield codified knowledge. Conversely, the Chinese parent adopts an adaptive "Taichi" strategy, leveraging strategic patience, low-key integration, and philosophical "non-action" to foster trust. Crucially, success hinged not on top-down mandates, but on empowering floor-level engineers to build interpersonal trust. We contribute a novel temporal-process model, highlighting that effective RKT in high-tech acquisitions demands indirect, relationship-driven approaches over direct confrontation.

Assoc. Prof. Abdullah Sarwar, Multimedia University, Malaysia

Dr. Abdullah Sarwar is an Associate Professor of Marketing at the Faculty of Management, Multimedia University (MMU), Cyberjaya, Malaysia. He holds a Master's degree in Business Administration from University Tun Abdul Razzak, Malaysia, following a distinguished five-year tenure as a commissioned officer in the Bangladesh Army. He subsequently gained experience as a corporate manager for three years before pursuing a Ph.D. in Business Administration at the International Islamic University Malaysia. With a robust academic career, he has taught both undergraduate and postgraduate students, contributing significantly to the fields of marketing and management. He has authored over 80 academic articles in renowned international journals and conferences. In recognition of his scholarly contributions, he was honoured with the “Emerald Literati Network Awards for Excellence” in 2016. He is a member of the American Psychological Association (APA) and also an active trainer and consultant. He is currently engaged in digital marketing training and provides mentorship to Ph.D. and master's students. His research interests encompass consumer behavior, digital marketing, Islamic marketing, service marketing, marketing strategy, and tourism marketing.

Title: From Data to Value: How Artificial Intelligence and Analytics are Transforming Business Models, Customer Experiences, and Economic Growth
Abstract: The rapid growth of digital technologies has generated unprecedented volumes of data, creating new opportunities for organizations to transform information into strategic value. Artificial Intelligence (AI), advanced analytics, and machine learning are increasingly enabling businesses to extract actionable insights, optimize decision-making, enhance customer experiences, and develop innovative business models. In the digital economy, data has emerged as a critical asset, driving competitive advantage and economic growth across industries.
This presentation explores how organizations convert data into value through AI-driven innovation, data monetization strategies, and intelligent analytics. It examines the evolution of business models in e-commerce and digital platforms, highlighting how firms leverage consumer analytics, personalization, and predictive intelligence to create superior customer experiences and sustainable competitive advantages. The presentation also discusses the broader economic implications of AI adoption, including productivity enhancement, market transformation, and the emergence of new digital ecosystems.
While AI and analytics offer significant opportunities, they also raise important ethical, governance, and regulatory challenges related to privacy, transparency, bias, and responsible data usage. The presentation concludes by examining future trends in the digital economy, including generative AI, autonomous decision systems, and data-driven innovation, and offers strategic insights for business leaders, policymakers, and academics seeking to thrive in an increasingly intelligent and data-centric world.