The credit rating of taxpayers through integrating a 𝐤-means clustering algorithmwith DEA

Due to the importance of improvement in any organisation,measuring the efficiency of employees, clients, andorganizations are so important.Knowing the primaryfunction of tax revenues in the development of state plans,the tax system has always attempted to resolve the problemsahead by practicing suitable measures. This study wascarried out to improve the efficiency of homogeneousclusters of taxpayers considering that no research hasventured so far to evaluate their performance. Here, westudied ۱۹۰۲ companies of legal taxpayers by reviewing thedata available, extracted effective clustering indices, andperformed clustering by the 𝒌 -means method . The bestnumber of clusters was determined as 𝒌=۱۵ using Davies–Bouldin index. then The efficiency of each cluster oftaxpayers was determined DEA, where eight of the clusterswere efficient and the remaining were inefficient. Simply put,the taxpayers of these efficient clusters have been able to givethe maximum output with the same inputs. Cluster number۱۱ was the most inefficient cluster with an efficiency ofapproximately ۰.۴۸۷.

کلیدواژه ها:

K-means ، Efficiency ، Tax Compliance ، DataEnvelopment Analysis