The process of transition and growth in Central and Eastern Europe (CEE) provides interesting insights, considering the countries' historical relationship with the Soviet Union. The 20 years after the Eastern enlargement of the European Union show an integrative power within the Single Market....

Leib et al. (2024) examine how artificial intelligence (AI) generated advice affects dishonesty compared to equivalent human advice in a laboratory experiment. In their preferred empirical specification, the authors report that dishonesty-promoting advice increases dishonest behavior by...

When inter-arrival times between events follow an exponential distribution, this implies a Poisson frequency of events, as both models assume events occur independently and at a constant average rate. However, these assumptions are often violated in real-insurance applications. When the rate at...

Investigating how systemic risk originates and spreads across the financial system poses an inherently compositional question, i.e., a question concerning the joint distribution of relative risk share across several interdependent contributors. To address this question, we propose a weighted...

Logistic regression is widely used in complex data analysis. When predictors are at individual level and the response at aggregate level, logistic regression can be estimated using the Maximum Likelihood Estimation (MLE) method with the joint likelihood function formed by Poisson binomial...

Based on the job demands-resources (JD-R) model, this study aims to investigate how algorithmic behavioral constraint and algorithmic tracking evaluation affect gig workers' turnover intention by increasing relative deprivation and the extent to which this mediating role is moderated by...

Managing sustainable supply chain operations in dynamic three-dimensional (3D) environments is a significant challenge. Unmanned Aerial Vehicles (UAVs) offer transformative solutions to supply chains. This study aims to enhance sustainable supply chain management by considering new opportunities...

We study the propensity of independent algorithms to collude in repeated Cournot duopoly games. Specifically, we investigate the predictive power of different oligopoly and bargaining solutions regarding the effect of asymmetry between firms. We find that both consumers and firms can benefit...

The standard approach to solving linear DSGE models is to apply the QZ method. It is a one-shot algorithm that leaves the researcher with little alternative than to seek a different algorithm should the result be numerically unsatisfactory. We develop an iterative implementation of QZ that...

This study examines the application of machine learning models to predict financial performance in various sectors, using data from 21 companies listed in the BIST100 index (2013-2023). The primary objective is to assess the potential of these models in improving financial forecast accuracy and...

As the consumer market changes rapidly, retail networks require a system to optimize the quantity and assortment of goods. The authors develop and test theoretical and practical assortment optimization and distribution principles. The study aims to improve retail assortment management by...

Employee turnover poses a significant challenge to organizations, leading to increased costs and disruptions in workforce stability. In this study, we propose a novel hybrid model for employee turnover prediction that integrates Genetic Algorithms (GA) for feature selection with LightGBM for...

Purpose In an era marked by fierce business competition, customer retention is crucial for sustaining profitability. Churn prediction, the ability to forecast customer defections, is essential to enhance retention and can profoundly impact a company's bottom line. Among prediction techniques,...

This paper examines the racial implications of police interaction with algorithms, particularly in the context of racial disparities in rearrest predictions. Our experimental study involved showing police officers the profiles of young offenders and asking them to predict rearrest probabilities...