Keynote Speakers

  • Dr. Xiaowen Fu is a Professor in Engineering Management in the Department of Industrial and Systems Engineering, the Hong Kong Polytechnic University. His main research area is transport economics and management. He has provided advisory and modelling services to organizations such as the Boeing Commercial Aircraft, New Zealand Commerce Commission, Australian Competition and Consumer Commission, Government of British Columbia in Canada, Australian Competition Tribunal, Hong Kong Transport and Housing Bureau, Japan Rail (East), and OECD. He is an editor of the journal of Transport Policy, Vice President (Research) of the Air Transport Research Society, Vice President (Research) of the Institute for Aviation (UK), founding chair of the Maritime Economy and Policy stream of the World Transport Convention, and an honorary professor of the University of Sydney Business School.

    Abstract: This paper models two commonly adopted regulatory polices (the minimum requirement regulation vs. subsidy) on port adaptation investment engineering to mitigate the damage caused by climate change-related disasters. The ambiguity of the disaster occurrence probability and the decision makers’ attitudes towards risk are explicitly modelled. It is found, under the minimum requirement regulation, ports balance the option of increasing their adaptation vs. reducing their economic activities. In comparison, subsidies promote adaptation without introducing any incentive for ports to reduce outputs, but they can be less efficient than minimum requirement regulations in addressing market failures, such as that caused by a spill-over externality. The ambiguity of disasters changes the optimal designs of minimum requirement regulation and subsidy policy but does not change their relative ranking qualitatively. Decision makers’ risk attitudes also play important roles. Higher degrees of pessimism (more risk aversion) lead to lower port outputs but can also increase the level of port adaptation to achieve full insurance against disaster loss. Higher degrees of pessimism also make the government more conservative to intervene in the ports’ adaptation and thus less likely to impose the two regulatory policies. Our analysis also explains why it is justified for the government to withhold intervention under ambiguity, and also shows that the ambiguity does not necessarily bring worse expected social welfare.

    Keywords: Port adaptation investment; Climate change-related disaster; Disaster ambiguity; Regulation; Subsidy; Minimum requirement

  • Xu Chen is Professor of operations and supply chain management at School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, China. His current research interests include coopetition management, supply chain management, and operations management. His publications have appeared in Production and Operations Management, IISE Transactions, IIE Transactions, European Journal of Operational Research, OMEGA-International Journal of Management Science, Journal of Business Research, IEEE Transactions on Engineering Management, IEEE Transactions on Systems Man and Cybernetics: Systems, International Journal of Production Economics, International Journal of Production Research, Journal of the Operational Research Society, Annals of Operations Research, and other journals. His research has been supported by grants from the National Sciences Foundation of China (NSFC), Major Program of National Social Science Foundation of China (NSSFC), and National Key R&D Program of China.

    Abstract: We investigate the effects of low-carbon technology transfer between two rival manufacturers on their economic, environmental, and social welfare performance under a cap-and-trade policy. We model alternative licensing arrangements of technology transfer and evaluate the model performance from the perspectives of different stakeholders, including manufacturers, customers, and policy makers. Our findings show that the contractual choice on low-carbon technology licensing is dependent on the trade-off between the benefits gained from the licensing of technology and the consequential losses incurred from competition with a strengthened competitor, which is influenced by a combination of factors, including internal technological abilities, the interfirm power relationship, external market competition, and the carbon emission control policy. Among them, the interfirm power relationship is most influential in determining the optimal contractual decision. In addition, we extend the analysis of technology licensing strategies to different carbon emissions caps with additional cost incurred from purchasing emission allowances through auction, and a two-period model considering emissions cap reduction, respectively. Finally, our analyses show it is critical for policy makers to develop appropriate emissions control policies to promote the agenda of a sustainable, low-carbon economy.

  • Dr. Jingzhi Guo is an associate professor of Department of Computer and Information Science, Faculty of Science and Technology at University of Macau, teaching the subjects of e-commerce technology. He graduated on the major of International Business Management at the University of International Business and Economics (UIBE), China with a bachelor degree in economics (1983-1988). He obtained M.Sc degree in Computation at University of Manchester Institute of Science and Technology, UK (1999-2000), and awarded PhD degree in Electronic Commerce and Internet Computing at Griffith University, Australia (2001-2004).
    Dr. Guo's current research focuses on the e-commerce areas of electronic marketplace, concept representation, semantic integration, collaborative commerce, virtual world and virtual marketplace, and electronic payment systems. Major applications of his research includes: vocabulary editor, business document editor, business activity inference engine, virtual world architecture and networking, electronic marketplace modeler, interoperable electronic product catalogues, electronic cash, and virtual money. Current prototypical implementations of his research includes ConexNet (collaborative concept exchange network) and EMpNet (electronic marketplace network). Based on the idea of ConexNet and EMpNet, some particular achievements are made, for example, Concept Dictionary (CoDic), Sign Description Framework (SDF).

    Abstract: One of the main challenges in modern industrial and business engineering is the semantic heterogeneity in the interactions among humans and computer applications. For example, there are heterogeneous concept representations in natural languages for chatbots, voice assistants, user content generation, intent analysis, business document exchange, smart contract creation, and machine translation. It is highly desirable that there is a common semantic mediation method to mediate all those semantic heterogeneities between human and computers and between computer applications. In this talk, a Machine Natural Language (MNL) will be introduced, which is a universal artificial natural language understood by both humans and computers. It enables computers to simulate humans to read and write, and to talk with humans as human do. MNL was developed based on the existing collaborative conceptualization theory and a newly devised case grammar. The goals of MNL are: (1) to mediate various heterogeneous applications through a universal natural language mappable onto all existing natural languages, and (2) to enable humans to interact with computers or future AI agents without semantic ambiguity.