Updating the study by Seiler and Wohlrabe (2013) we use archetypoid analysis to classify top economists. The approach allows us to identify typical characteristics of extreme (archetypal) values in a multivariate data set. In contrast to its predecessor, the archetypal analysis, archetypoids...

The way one leads their life is considered an important factor in health. In this paper we propose a system to provide risk assessment based on behavior for the health insurance sector. To do so we built a platform to collect real-world data that enumerate different aspects of behavior, and a...

The rising popularity of smart factories and Industry 4.0 has made it possible to collect large amounts of data from production stages. Thus, supervised machine learning methods such as classification can viably predict product compliance quality using manufacturing data collected during...

In the past 30 years, as sponsors of defined benefit (DB) pension plans were facing more severe underfunding challenges, pension de-risking strategies have become prevalent for firms with DB plans to reduce pension-related risks. However, it remains unclear how pension de-risking activities...

The aim of this paper is to assess the level of success achieved by entrepreneurs. The concept of success has many subjective facets, and it needs to be evaluated to reach other higher objectives, such as improving support systems for entrepreneurs. The usual pre-existing focuses for the...

Leveraging the availability of a large panel of signed trade data in the corporate bond market,we explore how machine learning methods can be used to improve upon standard tradedirection classification methods in markets in general, both with and without pre-trade transparency.Using the signed...

In the past 30 years, as sponsors of defined benefit (DB) pension plans were facing more severe underfunding challenges, pension de-risking strategies have become prevalent for firms with DB plans to reduce pension-related risks. However, it remains unclear how pension de-risking activities...

Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that...

Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy. A central issue in the PCA is how to select the number of principal components....

Corporate misconduct is a huge and widespread problem in the economy. Many companies make mistakes that result in them having to pay penalties or compensation to other businesses. Some of these cases are so serious that they take a toll on a company’s financial condition. The purpose of this...

We evaluate the performance of common stock trade classification algorithms including the quote, tick, Lee and Ready (1991), and Ellis, Michaely, and O’Hara (2000) rule to infer the trade direction of option trades. Using a large sample of matched intraday transactions and Open/Close data, we...

Knowledge management is essential to modern organizations. Due to the information overload problem, mangers are facing critical challenges in utilizing the data in the organizations. Although several automated tools have been applied, previous applications often deem knowledge items independent...

The company's sustainability is influenced by several internal and external factors, one of them is the turnover intention which has an impact on the weak loyalty of human resources. Based on the results of a survey, it shows the level of turnover intention is influenced by many factors. A high...

The aim of this paper is to assess the level of success achieved by entrepreneurs. The concept of success has many subjective facets, and it needs to be evaluated to reach other higher objectives, such as improving support systems for entrepreneurs. The usual pre-existing focuses for the...

Background and objectives: Atrial fibrillation (AF) is a common and extremely harmful arrhythmia disease that leads to stroke and death. Several kinds of AF exist as paroxysmal AF, persistent AF, and permanent or chronic AF. Based on electrocardiograms (ECG), wavelet transform (WT), and...

Research Aims: The Freemium business model is becoming increasingly prominent in the current digital economy. In the mobile game market, total revenue from free-to-download apps is overtaking those from paid apps. The purpose of this article is to propose a taxonomy that examines and categorizes...

This paper uses the Austrian theory of money, as developed mainly by Ludwig von Mises and Murray N. Rothbard to identify the separate economic processes commonly designated as “deflationary” and to determine whether they can be classified as “benign” or “malignant.”

Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data...