Parallel Exhibition: An ACP-Based Framework for Organization and Management of MICE Systems

Authors

  • Sangtian Guan Macau University of Science and Technology image/svg+xml Author
  • Siji Ma Macau University of Science and Technology image/svg+xml Author
  • Jun Huang Author
  • Wen Ding QAII Author

DOI:

https://doi.org/10.61702/nkbcm104

Keywords:

Parallel Exhibition, ACP, Parallel Intelligence, MICE Management, Complex Systems, Digital Human

Abstract

The MICE (Meetings, Incentives, Conferences, and Exhibitions) industry serves as a critical infrastructure of the global service economy, combining huge economic scale with an irreplaceable knowledge spillover function. However, the essential characteristics of temporary organizations give rise to multidimensional management challenges, including multi-participant conflicts, spatiotemporal uniqueness, rigid regional constraints, and emergent crowd behavior. Existing project management tools, isolated technologies, and digital twin methods are all insufficient to address these complex challenges. In this paper, we propose a parallel exhibition intelligent management framework based on the ACP (Artificial systems, Computational experiments, Parallel execution) approach. We design a collaborative mechanism among three types of humans---biological humans, digital humans, and robotic humans---to enable virtual-real closed-loop management. The framework aims to achieve coordination among participants, transferable experience accumulation, and real-time dynamic regulation through the ACP approach, addressing systemic management challenges in the MICE industry through a system-level approach and offering a reference for the intelligent management of complex social systems.

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Published

2025-12-30

Issue

Section

Journal of Cyber-Physical-Social Intelligence 2025

Categories

How to Cite

Guan, S., Ma, S., Huang, J., & Ding, W. (2025). Parallel Exhibition: An ACP-Based Framework for Organization and Management of MICE Systems. Journal of Cyber-Physical-Social Intelligence, 4(1), 9. https://doi.org/10.61702/nkbcm104

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