CKGSB Professor Sun Tianshu Wins Best Paper Award at CIST 2023 for Ground-breaking Research

Cheung Kong Graduate School of Business (CKGSB) proudly announces that Professor Sun Tianshu, CKGSB Visiting Professor of Information Systems, Director of the Center for Digital Transformation and Academic Director of the Business Scholars Program, has been awarded the prestigious Best Paper Award at the Conference on Information Systems and Technology (CIST 2023), one of the world’s top academic conferences in the field of information systems. This recognition marks Professor Sun’s second win of the award in the past decade, making him the only Chinese scholar to achieve this honor twice in recent years.

Professor Sun’s winning paper, titled, “Consumer Search and Dynamic Preference: An Econometric Model Based on Deep Learning,” is a collaborative effort with Professor Song Yicheng from the Carlson School of Management at the University of Minnesota. The paper introduces the “Consumer Preference Transformer (CPT) Dynamic Search Model,” a revolutionary approach that seamlessly integrates deep learning methods from artificial intelligence and structural econometric models in economics and marketing.

The CPT model is the first dynamic search model to innovatively integrate deep learning methods in artificial intelligence across borders and addresses key challenges faced by existing models in describing and predicting consumers’ search and purchase process. By merging artificial intelligence and econometric models, the CPT model offers unparalleled advantages:

• Gradual Formation of Consumer Preferences: The CPT model captures the development of consumer preferences during the search and comparison process, mirroring the real decision-making process consumers make when shopping.
• Dynamic Changes in Consumer Preferences: Unlike traditional models, the outcomes of consumer preferences can dynamically evolve over time, providing a more accurate representation of consumer behavior in the digital era.

Professor Sun emphasizes the importance of understanding consumers. He says, “Through the combination of artificial intelligence, big data, and structural econometric models, we can better match products with consumers, providing more accurate information and, thereby, providing businesses with better services. For platforms and merchants, the CPT dynamic search model offers a meaningful innovation. It enables companies to understand and predict the dynamically changing needs of consumers during the search process, facilitating the simulation of different product and information recommendation strategies.”

This award-winning research not only contributes to academic excellence, but also holds significant implications for businesses striving to enhance user consumption experiences and improve service efficiency in the digital economy.