Keynote Speaker
Dr. Minhao Zhang
University of Bristol，UK
Minhao is an assistant professor in operations management at University of Bristol, where he is also the programme director of MSc Global Operations and Supply Chain Management. The theme throughout Minhao’s current work is data analytics in advancing the theoretical development of strategic operations management.
Thanks to various cross-disciplinary research collaborations, Minhao has published papers in the fields of operations management, information systems, and social media. His work has been published in Journal of Service Research; British Journal of Management; International Journal of Operations & Production Management; Tourism Management; IEEE Transactions on Engineering Management; Industrial Marketing Management; International Journal of Production Economics; Supply Chain Management: An International Journal; Journal of Business Research, and R&D Management, among others.
Topic: Environmental Performance Feedback and Timing of Reshoring: Perspectives from Behavioural Theory of the Firm
Abstract：
The behavioural theory of the firm (BTOF) claims that firms’ performance feedback is of significance to strategic decision making. Building upon this, we shift our focus from widely researched financial performance to sustainability performance and theorize that firm’s environmental sustainability performance feedback (i.e., performance relative to social peers) exerts influence on firms’ reshoring decisions. Using archival data of 194 manufacturing firms from the Reshoring Initiative, we find that when firms experience underperformance in environmental sustainability, they are more likely to initiative reshoring earlier as problemistic search. In contrast, they tend to initiative reshoring later when they experience over-performance. Moreover, we examine the interaction of multiple performance feedback, in specific, social sustainability performance feedback in this study. We find that aspiration-relative social performance strengthens the relationship between environmental overperformance intensity and lateness of reshoring.
Dr. WANG Yue
The Hang Seng University of Hong Kong,China
Dr. Wang is an Associate Professor in the Department of Supply Chain and Information Management and the Associate Director of Policy Research Institute of Supply Chain of the Hang Seng University of Hong Kong. He received the Bachelor of Science and Master of Engineering degrees from Peking University, Beijing, China, and the PhD degree from the Hong Kong University of Science and Technology (HKUST). He previously worked in MIT Media Lab as a Research Assistant, and HKUST as Research Associate/Research Assistant Professor. His research interest includes machine learning, natural language processing and their applications in industrial engineering, healthcare management and operations management. He has published a number of articles in international refereed journals, such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Engineering Management, International Journal of Production Economics, International Journal of Production Research etc. His Erdos number is 3.Website: https://scm.hsu.edu.hk/us/aboutus/faculty/56.
Topic: Bridging the semantic gap between customer needs and design specifications using user-generated content
Abstract：
The key to successful product design is better understanding customer needs and creating better links between customer needs and product design parameters. With the recent trends toward diverse customer needs, the rapid introduction of new products, and shortened lead times, the elicitation and fulfilment of customer needs has become increasingly important for product development. However, there is a semantic gap between different parties involved in the design process. Specifically, customers may not possess the necessary domain knowledge to specify the product they want. As a result, they may only be able to express their needs in layman’s terms. The mapping from customer needs to design specifications must be closely studied to achieve efficient communication in the design process. In this talk, I will introduce our work on leveraging deep learning and natural language processing techniques to mine product review text, a kind of user-generated content, to devise a semantic mapping from review to product specifications. The result could bridge the semantic gap between the customer needs and design specification domains and facilitate the product design process.