The cross-disciplinary virtually simulated platform for enterprise management in universities' new business courses is an initiative practical framework based on scenario-driven tasks. However, there is a prominent conflict between the rapid operating cycle of simulation enterprises plus their fierce competitions and the strategic demand for real-time analysis for operational data. Based on such demand, this study takes the development method of the simulated enterprise management cockpit from Guangzhou Huashang College as an example. It adopts the combined weighting method based on cloud models to determine indicator weights, then qualitative and quantitative data analyses are conducted from five aspects: "business, finance and operation", "customer management and marketing", "internal operational objectives", "product development strategy", along with "team building and management". This approach achieves a comprehensive evaluation and early warning of the enterprise management process. Specifically, the subjective weights are determined by the Analytic Hierarchy Process, while the objective weights by the entropy weight method, finally verified by cloud model evaluation of its overall indicator performance. The design can evaluate the comprehensive performance of enterprise management indicators and students' activity participation through the cloud-based application and the digital cockpit, so as to fully presents the enterprise's overall management level, along with judgement of whether it is reasonable through pointers in different colors. In addition, apparent indicatorrelated characteristics are also utilized to assess future decision-making directions. Finally, this comprehensive approach can timely optimize operation strategies and facilitate budget allocation for future development.
CITATION STYLE
Fan, W., & Li, Z. (2024). Evaluation of comprehensive early warning for higher education institutions’ cloud model of simulated enterprise management cockpit. PLoS ONE, 19(6 June). https://doi.org/10.1371/journal.pone.0305652
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