By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering change (EC) process. Here, failing to adhere to planned...

Supply Chain Analytics (SCA) has emerged as a critical factor in determining the success of electronic commerce (E-commerce) companies. This review investigates the significant impact that SCA has had on the advertising landscape in the e-commerce industry. This article examines the complex...

Maintenance strategies are vital for industrial and manufacturing systems. This study considers a proactive maintenance strategy and emphasizes using analytics and data science. We propose an Explainable Artificial Intelligence (XAI) methodology for predictive maintenance. The proposed method...

The aim of this study is to explore the influence of environmental, social, and governance (ESG) factors on business failure in Brazil by employing advanced machine learning techniques. We collected data from 235 companies and conducted principal component analysis (PCA) on 40 variables already...

This research article presents a comparative analysis between logistic regression as a traditional method, artificial neural networks (ANNs), and decision tree as machine learning techniques for predicting credit risk. It meticulously examines and evaluates these three methods, elucidating their...

Successful investment in early-stage companies has high uncertainty. More specifcally, the tools available to investors need to be more robust to reduce the risk and manage the uncertainty of startups. This research aims to use machine learning methods to design a prediction solution to identify...