@article{YANG2026, 
author = {Fuqiang YANG and Haoteng LI and Fanliang GE and Youkun ZHANG},
title = {Optimization of the collaborative network system for emergency management in university laboratories},
year = {2026},
journal = {Experimental Technology and Management},
volume = {43},
number = {1},
pages = {273-278},
keywords = {university laboratory, social collaborative network, emergency collaborative network, network structure characteristics, structural hole theory},
url = {https://www.sciopen.com/article/10.16791/j.cnki.sjg.2026.01.034},
doi = {10.16791/j.cnki.sjg.2026.01.034},
abstract = {ObjectiveLaboratories are vital hubs for fostering scientific innovation and experimental research among university students. However, they face growing safety management challenges and declining emergency response efficiency due to hazardous experiments and aging systems, which hinder both emergency prevention and accident response in university laboratories. This study aims to enhance academic laboratories’ emergency management capabilities and their operational effectiveness. It also analyzes an accident case study at a university laboratory using the social network analysis method and builds an emergency management cooperation network model between departments.MethodsFirst, this study analyzes the effectiveness of emergency collaboration networks through a literature review to demonstrate their general applicability. Then, based on accident reports on the authoritative information platform for almost a month, an “organization-to-organization” relationship matrix was established and used as a basis for creating an emergency coordination network. Subsequently, relevant parameters of the emergency collaboration network in higher education laboratories were determined by a systematic analysis of a university laboratory accident case, including network density, central tendency, cohesion, and average distance. Using this network, this study refers to centrality and structural hole theories as the basis for the influence of each node in the university laboratories’ emergency coordination network and reveals the structural characteristics and interactions between the network nodes. Three optimization strategies were developed based on the results: creating cross-departmental resource coordination mechanisms, strengthening the coordinating functions of central nodes, and building a multi-department emergency collaboration network model for university laboratories. These strategies aim to enhance emergency management efficiency and safety in university laboratories.ResultsNetwork data analysis revealed an overall network density of 0.54 and a central potential of 41.32%, indicating good synergy but room for optimization. Data analysis, using centrality and structural hole theories, indicates that local governments and emergency management departments should be identified as core entities in university laboratory emergency management systems. Using their high network centrality and resource allocation capabilities, these departments must actively develop laboratory safety policies. University functional departments should serve as information exchange platforms because of their cross-departmental coordination capabilities. Specialized functional departments (such as fire brigades) are at non-core nodes of the emergency system with limited information control but can compensate for information gaps in the emergency coordination network through functional division and collaboration.ConclusionsThis study introduces an emergency collaborative network system and applies it to analyze a university laboratory accident. By establishing the laboratory’s emergency network and conducting data calculations and analyses, we identify critical nodes in the emergency management coordination network, addressing the aging issues of the current system. This method extends social network analysis to university laboratory safety management and offers insights into efficient university emergency response.}
}