Conference Background
This is a two-day online and physical conference hosted by TCI Network Asian Chapter, Microeconomics of Competitiveness (MOC) Asian Chapter, National Chengchi University (NCCU) and Industrial Technology Research Institute (ITRI). The physical conference will be held in NCCU, Taipei City. Further detail will be announced soon.
Purpose Aim of the Conference
This two-day hybrid conference is hosted jointly among the TCI Asian Chapters, the MOC Asian Chapter and NCCU to learn from new experiences in collaboration as enterprises, clusters and countries begin to build new types of in-time collaboration caused by generative and the other kind of AI (e.g. ChatGPT and Notion AI), geo-political conflicts, climate change and other impacts. It has become so critical for governments, clusters, enterprises, schools and other institutes to build the capability of in-time collaboration by deploying digital tools and planning new strategies. Key drivers of this in-time collaboration include business transformation, shifting supply chain, shared value, etc.
This will be a practical, policy-driven, visual, presentation-based, case study based conference.
This conference brings together speakers, ideas and papers to examine the eco-system of this in-time collaboration and how policy, strategy and practice can make in-time collaboration effective in Asia. The MOC Asian Chapter draws from the Harvard Business School Microeconomics of Competitiveness Network comprising over 100 universities worldwide. TCI draws from a worldwide network of people and organisations working in clusters and innovation ecosystems around the world that together create global connections, inspire new thinking about clusters and improve policy learning. This conference draws from the depth of knowledge and experience of the TCI / MOC networks from around the world including the Americas (LATAM), Europe, and other regions. Particular emphasis is on the development of case studies and examples from around the Asian Region.
Date:
July 7, 2023
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