AI-Driven Strategic Decision-Making For Business Expansion Using Naive Bayes Classifier

Abstract

The study centers on using the Naive Bayes classifier in predicting successful business expansion through strategic identification of growth opportunities. Data used in the analysis included significant variables such as market size, competitive strength, revenue growth, operating costs, and customer segmentation, resulting in significant performance indicators including 85% accuracy, 88% precision, 82% recall, and 85% F1-Score. This demonstrates the effectiveness of the model in predicting suitable areas for business expansion based on significant parameters, offering insights that could be considered by businesses to improve their expansion strategy. Additionally, this study addresses a gap in the current literature by being the first to document the application of the Naive Bayes classifier in business decisions at the highest level. The study bridges the gap between machine learning models and practical business strategies by demonstrating the applicability of the Naive Bayes classifier in making business decisions related to expansion. The simplicity and efficiency of the classifier make it a useful tool for decision-makers interested in successful business expansion. The model helps organizations focus on expanding in areas where growth is highly possible, reducing expansion risks and improving resource allocation for business expansion. Nonetheless, the study also identifies a disadvantage associated with the Naïve Future research may help refine the model in various ways by incorporating new technologies in terms of classifiers that can effectively consider the relationship among features, including using Random Forest or Deep Learning. Availability of more up-to-date data and even bigger databases may also play a role in the development of future models. Moreover, utilizing Naive Bayes classifiers together with other machine learning methods can result in decision support systems being used to make expansion strategies. To conclude, it should be noted that this research reveals the great importance of the use of artificial intelligence when making strategic decisions.