BI in simulation analysis with gaming for decision making and development of knowledge management

Abstract

Increasing technology advancements have led to a number of problems with modern corporate decision-making, which is a challenging occurrence in the absence of business intelligence and machine learning (ML). Because effective decision-making is impossible without ML, integration of ML with business intelligence (BI) is essential to both corporate decision-making and business intelligence as a whole. Only once they have learned anything again may machines assist in your educational process. This study suggests a fresh approach to knowledge building in company management decision-making through the use of gaming and machine learning models. Using a game model that involves decision-making, knowledge analysis based on business management is conducted. Subsequently, quantum reinforcement reward neural networks build knowledge. The accuracy, precision, recall, F_1 score, MSE, NSE of business management modelling with knowledge growth are all assessed by simulation. The student’s gender had no bearing on the income they were offered throughout the job placement process or their MBA specialisations in Marketing and Finance (Mkt & Fin) or Marketing and Human Resource (Mkt & HR), according to a statistical t-test with a significance threshold of 0.05 (p > 0.05).