Many cities with school choice programs employ algorithms to determine which applicants get seats in oversubscribed schools. This study explores whether the New Orleans placement algorithm favored students of certain races or socioeconomic classes via its use of priorities such as geographic and...

We audit the job recommender algorithms used by four Chinese job boards by creating fictitious applicant profiles that differ only in their gender. Jobs recommended uniquely to the male and female profiles in a pair differ modestly in their observed characteristics, with female jobs advertising...

Effective management of fuel logistic distribution is essential for ensuring timely supply chain operations and achieving product sustainability. This study employs systematic literature mapping (SLM) to identify gaps in research and potential advancements in Supply Chain Management (SCM) for...

Businesses increasingly rely on algorithmic systems and machine learning models to make operational decisions about customers, employees, and counterparties. These "algorithmic operations" can improve efficiency but also concentrate liability in a small number of technically complex, drifting...

This paper considers how a system designer can program a team of autonomous agents to coordinate with one another such that each agent selects (or covers) an individual resource with the goal that all agents collectively cover the maximum number of resources. Specifically, we study how agents...

A large body of research across management, psychology, accounting, and economics shows that subjective performance evaluations are systematically biased: ratings cluster near the midpoint of scales and are often excessively lenient. As organizations increasingly adopt large language models...

In this digital era, many companies are integrating new solutions involving Artificial Intelligence (AI)-based automation systems to optimize processes, reach higher efficiency, and help them with decision-making. While implementing these changes, various challenges may arise, including...

Social media are at the center of countless debates on polarization, misinformation, and even the state of democracy in various parts of the world. An essential feature of social media is their recommendation algorithm that determines the ranking of content presented to the users. This paper...

The accelerating penetration of electric vehicles (EVs) is reshaping modern distribution networks by introducing substantial, time-varying charging demand and new operational uncertainties. At the same time, Vehicle-to-Grid (V2G) capable EVs offer unprecedented flexibility to support grid...

A large body of research across management, psychology, accounting, and economics shows that subjective performance evaluations are systematically biased: ratings cluster near the midpoint of scales and are often excessively lenient. As organizations increasingly adopt large language models...

While algorithmic decision-making technology can greatly improve efficiency at work, it has the potential to promote unethical decision making in humans who work with the technology. In this paper, we test how the moral disengagement mechanism, displacement of responsibility arises, as an...

Probability distributions, which are typically used to describe income distributions, are not suitable to describe a population's distribution of wealth because of the existence of negative observations and a large concentration of values close to zero. To overcome these problems, we describe...

Subspace algorithms like canonical variate analysis (CVA) are regression-based methods for the estimation of linear dynamic state space models. They have been shown to deliver accurate (consistent and asymptotically equivalent to quasi-maximum likelihood estimation using the Gaussian likelihood)...

This paper develops a novel hybrid framework that integrates clustering-enhanced Particle Swarm Optimization (PSO) with stretching techniques to solve Markowitz's quadratic portfolio optimization problem. The proposed approach avoids local optima traps that plague traditional optimization...

Algorithms pose interesting challenges to competition law, particularly discussing which practices involving this fast-paced technologies may or should be caught under Article 101 of the Treaty on the Functioning of the European Union ("TFEU"). As AI-driven pricing algorithms become increasingly...

Background: This paper investigates hybrid quantum-classical optimization approaches for addressing core supply chain management (SCM) problems. A unified hybrid framework is implemented and evaluated across five representative domains: vehicle routing, scheduling, facility location, inventory...

The increasing urgency of carbon footprint reduction in supply chain operations demands innovative optimization approaches that balance economic efficiency with environmental sustainability. This paper presents a novel carbon-aware route optimization framework that integrates machine...

This study proposes an optimized estimation approach for Self-Exciting Threshold Autoregressive (SETAR) models by integrating the Majorization-Minimization Group Least Absolute Shrinkage and Selection Operator (MM-gLASSO) algorithm, with a primary focus on improving forecasting performance in...

This paper develops a sequential deep learning algorithm for solving dynamic stochastic general equilibrium (DSGE) models. The algorithm trains a deep neural network to approximate the model's policy functions across four progressive phases: steady-state anchoring, exploration around the steady...

Organizations increasingly employ algorithms to support or automate decision-making processes across various functions, such as personnel performance evaluation, resource allocation and strategic planning. Despite growing research interest, the literature on algorithmic decision-making (ADM)...

Predictive AI is increasingly used to guide decisions on agents. I show that even a bias-neutral predictive AI can potentially amplify exogenous (human) bias in settings where the predictive AI represents a cost-adjusted precision gain to unbiased predictions, and the final judgments are made by...

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....