Due to imbalances in the global transport of containerised goods, liner shipping companies go to great lengths to match the regional supply and demand for empty containers by transporting equipment from surplus to deficit regions. Making accurate forecasts of regional empty container...

We run an online experiment to study the origins of algorithm aversion. Participants are either in the role of workers or of managers. Workers perform three real-effort tasks: task 1, task 2, and the job task which is a combination of tasks 1 and 2. They choose whether the hiring decision...

Implementing new machine learning (ML) algorithms for credit default prediction is associated with better predictive performance; however, it also generates new model risks, particularly concerning the supervisory validation process. Recent industry surveys often mention that uncertainty about how...

Expectation maximization (EM) algorithm is a popular and powerful mathematical method for parameter estimation in case that there exist both observed data and hidden data. The EM process depends on an implicit relationship between observed data and hidden data which is specified by a mapping...

The algorithmic accountability literature to date has primarily focused on procedural tools to govern automated decision-making systems. That prescriptive literature elides a fundamentally empirical question: whether and under what circumstances, if any, is the use of algorithmic systems to make...

This article scrutinises the potential of the existing regulatory apparatus in Union law to tackle the social, technical, and legal challenges inherent in deploying automated systems in high-risk settings such as the workplace, with a view to setting out key lessons for the proposed EU...