Entropy Weight TOPSIS Evaluation of Corporate Internal Control Quality Based on Fuzzy Matter-Element Model

Abstract

One of the core objectives of domestic and foreign regulation policies is to strengthen internal control and improve corporate risk management ability. To evaluate corporate internal control quality (CICQ), this paper constructs a composite fuzzy matter-element model based on the fuzzy matter-element theory and the data on 781 listed enterprises in China. By the entropy weight method, five evaluation indices of internal control were weighed and compared with the positive and negative ideal indices. Next, the internal control of the listed enterprises was measured by TOPSIS. The results show that the indices of laws and regulations (LR), financial statements (FS), assets safety (AS), operation (OP), and strategy (ST) are of different weights in terms of CICQ evaluation. The LR, OP, and ST indices are more important than the FS indices. Among the secondary indices, the most important indices, namely, major litigation and arbitration cases, turnover of total assets, and Tobin’s Q account for 66% of total weights. In addition, the CICQ varies with industries: the top-10 enterprises in terms of CICQ mostly belong to industries with strict requirements on work safety. The research findings lay a methodological and practical basis for the CICQ evaluation of Chinese enterprises.