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...