Measuring the Sustainability of Open Sharing for Scientific Instruments in China: An Ascendency Analysis Using Benchmark Use-Time Data
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Background: The open sharing of large-scale scientific instruments is critical for national innovation and reflects a core principle of the circular economy. While China has invested heavily in creating a national instrument sharing network, methods for evaluating the overall health and sustainability of this complex ecosystem are underdeveloped, often focusing on simple efficiency metrics while ignoring system-wide resilience.
Methods: This study introduces Ecological Network Analysis (ENA) as a novel framework to assess the sustainability of China's scientific instrument sharing system. We constructed a network model representing the flow of instrument use-time among three key sectors (universities, public research institutes, and enterprises) using benchmark data from the National Network for Scientific Instrument Sharing from 2020 to 2024. We then calculated the system's ascendency—a comprehensive, information-theory-based measure that quantifies the balance between organized efficiency (growth and development) and redundant flexibility (resilience).
Results: The analysis revealed a steady increase in the system's total sharing activity (Total System Throughput) over the five-year period. However, the ratio of ascendency to total development capacity (A/C) showed a significant upward trend, while the overhead-to-capacity ratio (Φ/C) declined. This indicates that the network is evolving towards higher efficiency but at the cost of decreasing resilience. Public research institutes were identified as the keystone sector, contributing most significantly to the network's organized structure.
Conclusion: Applying ascendency analysis provides a holistic, quantitative measure of the sustainability of resource-sharing networks. Our findings suggest that current policies governing China's instrument sharing system may be prioritizing short-term efficiency gains over long-term systemic resilience. We recommend that policymakers adopt a more balanced approach, using ascendency-based metrics to foster a sharing ecosystem that is not only efficient but also robust and adaptive.