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An Approach to the Evaluation of the Quality of Accounting Information Based on Relative Entropy in Fuzzy Linguistic Environments

机译:模糊语言环境下基于相对熵的会计信息质量评价方法

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There is a risk when company stakeholders make decisions using accounting information with varied qualities in the same way. In order to evaluate the accounting information quality, this paper proposed an approach to the evaluation of the quality of accounting information based on relative entropy in fuzzy linguistic environments. Firstly, the accounting information quality evaluation criteria are constructed not only from the quality of the accounting information content but also from the accounting information generation environment. Considering that the rating values with respect to the criteria are in linguistic forms with different granularities, the method to deal with the linguistic rating values is given. In the method, the linguistic terms are modeled with the 2-tuple linguistic model. Relative entropy is used to calculate the information consistency, which is used to derive the weight of experts and criteria. Finally, the example is given to illustrate the feasibility and practicability of the proposed method.
机译:当公司利益相关者以相同的方式使用质量不同的会计信息进行决策时,存在风险。为了评估会计信息质量,提出了一种在模糊语言环境下基于相对熵的会计信息质量评估方法。首先,不仅从会计信息内容的质量来构建会计信息质量评价标准,而且从会计信息生成环境来构建会计信息质量评价标准。考虑到与标准相关的评级值是具有不同粒度的语言形式,给出了处理语言评级值的方法。在该方法中,用两元组语言模型对语言术语建模。相对熵用于计算信息的一致性,用于导出专家和标准的权重。最后,通过算例说明了该方法的可行性和实用性。

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