This paper describes an intelligent decision support system for evaluating state-owned enterprises (SOEs) using DEA models. This decision support system converts numerical data into information that can be used to evaluate state-owned enterprises (SOEs). In this paper, we use DEA models, including CCR, BCC and FDH, to shed new light on the operational efficiency and determinants of state-owned enterprises in Beijing. We propose an evaluation framework for evaluating state-owned enterprises (SOEs), including a database management subsystem, a model base subsystem, a knowledge acquisition subsystem, and a dialogue subsystem. Finally, we adopt the logistic regression model to analyze the effect factors of inefficient state-owned enterprises and provide optimum decision-making for state-owned enterprises (SOEs).
['Wei-Kang Wang', 'Hao-Chen Huang', 'Lai My']
Design of a knowledge-based performance evaluation system: A case of high-tech state-owned enterprises in an emerging economy