Associate Professor Goh Khim Yong, Ph.D. student Guo Yutong and collaborators win big at ICIS 2022

10 January 2023
From left to right: Ph.D. student Guo Yutong and Associate Professor Goh Khim Yong with their Best Conference Paper Award plaque.

10 January 2023 ­– Associate Professor Goh Khim Yong and Ph.D. student Guo Yutong who are both from the Department of Information Systems and Analytics (DISA), won the Best Paper Award in the Digital and Mobile Commerce track and the Best Conference Paper Award at the 2022 International Conference Information Systems (ICIS)

ICIS is an annual conference that brings together academic researchers in the field of information systems from all over the world. About 1,600 researchers from 53 countries attended the conference in 2022. The conference was held in Copenhagen, Denmark from December 9 to 14.

Besides A/P Goh Khim Yong and Ph.D. student Guo Yutong, the winning team also consists of collaborators from Alibaba Group and Zhejiang University.

Their paper, “Short Video Marketing in E-commerce: Analysing and Predicting Consumer Response,” analyses and predicts consumer viewing response to e-commerce short videos (ESVs). Using a dataset and a model, they found that product description, product demonstration, pleasure, and aesthetics were four key determinants of ESV viewing duration. They also constructed a framework to predict and evaluate consumer viewing response to ESVs which is a first in an e-commerce setting. Overall, the paper provides pioneering theoretical, practical, and methodological contributions for short-video marketing in e-commerce to the information systems and relevant literatures.

In the fourth year of her Ph.D. study, Yutong was an on-site research intern at Alibaba for nearly seven months. During her internship, she observed many challenges the industry typically face when implementing or employing artificial intelligence technologies to tackle business problems. “These observations were actually what greatly motivated my research,” reflected Yutong.

She also looked through the economics and marketing literatures to conceptualise real-world challenges and find appropriate business theories to guide technical solutions.

“I feel very honoured. This co-working experience provided me with a great opportunity to understand real-world business problems (e.g., how to increase short-video marketing effectiveness), to learn and apply advanced machine learning algorithms, and to get my hands dirty with large-scale unstructured data. I deeply appreciate my Alibaba colleagues for their consistent help and hard work. In the future, I hope to closely connect with industry practitioners and to investigate other research problems that can yield impact for both research and practice,” further added Yutong.

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