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...

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...

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...

The World Bank Group supports the Ministry of Economy of Armenia in developing a green taxonomy (GT) as a key step toward a sound system of identifying, selecting, and financing green and sustainable development projects and actions, and as an essential milestone toward establishing an...

The rapid evolution of technology is reshaping labor markets by altering skill demands and job profiles. This paper introduces a novel skill-based measure of occupational technology intensity - the Occupational Technology Skill Share (OTSS) - that distinguishes between manual, digital, and...

Recidivism is a persistent challenge for criminal justice systems worldwide, yet evidence from Latin America remains scarce. This study addresses that gap through three contributions. First, it reviews the individual, institutional, and contextual determinants of recidivism, with special...

This study develops an interpretable machine learning framework for type 1 motor insurance renewal classification using 70,290 real-world Thai policies, providing essential insights for pricing, customer retention, and operational decision making. The dataset was partitioned into a 70% training...

Development finance increasingly funds entrepreneurship in developing countries, but evidence of its impact on entrepreneurship is mixed. Existing studies analyze total development finance flows as entrepreneurship-specific development finance data did not previously exist. By training and...

In insurance portfolios, classifying customers without a prior history at a given company is particularly challenging due to the absence of historical behavior, extreme class imbalance, heavy-tailed loss distributions, and strict operational constraints. Traditional machine learning approaches,...

This study aims to predict stock market risk and improve preparedness for potential economic crises by identifying sharp declines in stock returns using classification-based machine learning models. Using ten years of KOSPI 200 index data (2015 to 2024), a daily return series was constructed. 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...

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...

Accurate prediction of customer repurchase behaviour is vital for businesses aiming to boost customer retention. This study introduces an advanced approach that merges classification algorithms with RFM analysis, a widely adopted framework in customer relationship management. The proposed models...

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,...

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...

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...

In this study, work discouragement in Mexico is addressed from a mathematical modeling perspective. Two conditions of employability are considered: unemployed and discouraged, and the classification of these groups is characterized using machine learning models and sociodemographic variables,...