This study examines the use of artificial neural networks (ANNs) to classify financial risks in micro-, small-, and medium-sized enterprises (MSMEs) in Montenegro and the wider Western Balkan region. The economies in this region share structural similarities, such as a high concentration of...

Classifying games according to their strategic properties provides meaningful insights into the motivations driving the interacting parties, suggests possible future trajectories, and in some cases also points to potential interventions aiming to influence the interactions' outcomes. Here, we...

Mortgage default prediction is always on the table for financial institutions. Banks are interested in provision planning, while regulators monitor systemic risk, which this sector may possess. This research is focused on predicting defaults on a one-year horizon using data from the Ukrainian...

This article identifies the two approaches to defining a book review. The first defines a book review as a text published in the 'Book Reviews' section of a journal. The second approach involves specifying criteria that a text must satisfy to qualify as a book review and assessing whether a...

Die Nutzung von Scannerdaten in der Verbraucherpreisstatistik hat viele Vorteile, bringt allerdings auch einige Herausforderungen mit sich. Eine der Herausforderungen ist die Klassifizierung der Artikel nach dem vom Verbraucherpreisindex verwendeten Klassifikationssystem COICOP. Aufgrund der...

The exchange of information is an essential means for being able to conduct negotiations and to derive situational decisions. In electronic negotiations, information is transferred in the form of requests, offers, questions and clarifications consisting of communication and decisions. Taken...

En este estudio, se aborda el desaliento laboral en México desde una perspectiva de modelación matemática. Se consideran dos condiciones de empleabilidad: desocupado y desalentado, y se caracteriza la clasificación de estos grupos utilizando modelos de aprendizaje automático y variables...

This work introduces a novel method for sentiment analysis in the stock market by combining Deep Neural Networks (DNN) and an improved Firefly Algorithm (FA). It is essential to comprehend investor sentiment in financial markets in order to forecast stock price movements and make wise investment...

Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applications. In particular, in the last few years, Raman spectroscopy analysis of biological samples has been successfully applied for early-stage...

Social networks are becoming vital for people to interact with each other, which in turn represent the production of a huge amount of information that can be useful in many contexts (e.g., medicine, natural disasters, commercial purposes, tourism). Nevertheless, analyzing such Big Data for...

Seaweed is a globally significant aquaculture commodity with increasing economic and environmental importance. However, inconsistent quality standards and subjective procurement practices continue to hinder efficiency in its value chain, particularly for dried Eucheuma seaweed. This study...

Sustainable supply chain management plays a pivotal role in shaping corporate reputation and enhancing customer loyalty in the contemporary market. This study uniquely integrates regional, demographic, and psychographic data with advanced machine learning methodologies, including clustering,...

In July 2024, a new Theme Taxonomy was launched for all IBRD/IDA (the Bank) lending operations and Advisory Services and Analytics (ASA) products, refreshing and building on the Theme Taxonomy structure that was launched in July 2016. Theme codes are aligned with World Bank Group goals and...

Emotion recognition from electroencephalogram (EEG) signals has garnered significant attention owing to its potential applications in affective computing, human-computer interaction, and mental health monitoring. This paper presents a comparative analysis of different machine learning methods...

The prevailing consensus in statistical literature is that multiple imputation is generally the most suitable method for addressing missing data in statistical analyses, whereas a complete case analysis is deemed appropriate only when the rate of missingness is negligible or when the missingness...

The extraction of cyber threat intelligence (CTI) from open sources is a rapidly expanding defensive strategy that enhances the resilience of both Information Technology (IT) and Operational Technology (OT) environments against large-scale cyber-attacks. However, for most organizations,...

Machine learning algorithms are typically evaluated using benchmark datasets under the assumption that these datasets are clean. However, recent studies have revealed the presence of label noise in many benchmark datasets, indicating a biased evaluation to date. Confident learning (CL), an...

Financial sentiment analysis is crucial for making informed decisions in the financial markets, as it helps predict trends, guide investments, and assess economic conditions. Traditional methods for financial sentiment classification, such as Support Vector Machines (SVM), Random Forests, and...

The utilization of data presents significant opportunities for enhancing business models and generating value. Consequently, the integration of data into value creation processes has given rise to the emergence of data-driven business models. This study aims to delineate and introduce diverse...

A pesar de la importancia creciente del comercio de servicios en entornos digitales, su medición es incipiente y enfrenta limitaciones, especialmente en países en desarrollo. Este trabajo busca reducir esta brecha mediante la construcción de una nueva base de datos de más de 2.600 sitios en...