In this paper, we study the problem of misrepresentation under heavy-tailed regression models with the presence of both misrepresented and correctly-measured risk factors. Misrepresentation is a type of fraud when a policy applicant gives a false statement on a risk factor that determines the...

This paper presents a practical implementation of an analytical customer relationship (CRM) model, which aims to increase the customer satisfaction, thereby reducing the rate of attrition. The analytical CRM model not only manages and synchronizes customer relationship management processes, but...

Start-Ups werden oftmals dafür bewundert, wie wirkungsvoll sie neue, mitunter disruptive Angebote an den Markt bringen - und das häufig mit sehr begrenzten verfügbaren Ressourcen. In Bezug auf Vertriebseffektivität und -effizienz heben sie sich damit gegenüber etablierten Unternehmen...

Research into “algorithmic discrimination” has largely dismissed the fact that algorithms are often developed and used by organizations. In this article, we show that organizational sociology can contribute to a more nuanced perspective on “algorithmic decision-making.” Drawing on the...

The performance measurement of a great variety of enterprises is a highly complicated issue, especially taking into account that performance has a great many aspects and many variables which may, at times, be highly inconsistent with each other. The use of analytics and advanced machine learning...

Transparency in transport processes is becoming increasingly important for transport companies to improve internal processes and to be able to compete for customers. One important element to increase transparency is reliable, up-to-date and accurate arrival time prediction, commonly referred to...

Purpose: In recent years, a number of practical logistic applications of machine learning (ML) have emerged, especially in Supply Chain Management (SCM). By linking applied ML methods to the SCM task model, the paper indicates the current applications in SCM and visualises potential research...

The study's objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model as a...