A Multi‐Criteria Decision Framework for Performance Evaluation of Large‐Scale Research Infrastructure: A Fuzzy Borda Approach With IoT‐Enabled Case Study
Case study demonstrates a 15.00% efficiency gain across 350 large-scale research instruments following IoT integration, indicating the value of digital multi-criteria performance frameworks.
Key Points
To develop an integrated multi-criteria decision framework using the fuzzy Borda method to quantitatively evaluate and enhance the operational efficiency of shared large-scale research instruments.
Developed a fuzzy Borda decision framework prioritizing four performance indicators: total operating hours, basic management capacity, testing revenue, and research output.
Deployed the framework to assess an IoT intervention featuring QR-code access, automated logging, and dual-sensor validation across 350 large-scale instruments at Shanghai University under full-time and part-time management models.
Conducted Monte Carlo simulations to assess the robustness and stability of the measured efficiency gains.
IoT implementation yielded a 15.00% average improvement in overall system utilization efficiency across 350 instruments.
Monte Carlo simulations demonstrated robust efficiency gains, maintaining performance improvements between 14.87% and 14.98%.
Testing revenue and research output showed the highest sensitivity to digital integration, with efficiency gains varying across full-time versus part-time staffing regimes.