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Predicting the operational efficiency of banks using their Information Technology: Decision tree algorithm approach


Peter Appiahene
Yaw Marfo Missah
Rose-Mary Owusuaa Mensah Gyening
Daniel Adu-Gyamfi
Micheal Opok

Abstract

Literature from industrialized countries suggests that investments in innovative technologies such as Information Technology (IT) can boost performance and productivity growth.This has pushed severalinstitutions like banksworldwide to invest their resources and even their future in IT in order to gain advantage over their competitors within the same business environment.In solving this problem, the current study proposesthe usage of a model that combines a two-stage Data Envelopment Analysis (DEA) model, Multinomial Regression Analysis (MRA) and Decision Tree (DT) using C5.0 Algorithm, achieving favorable prediction rate of 88% and a good computational time compared to similar studies.


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eISSN: 2805-3478
print ISSN: 1597-4316