Die diskrete Simulation stellt eine wichtige und etablierte Methode zur Untersuchung des dynamischen Verhaltens von komplexen Produktions- und Logistiksystemen dar. Sie ist daher zur Planung, Steuerung und Kontrolle solcher Systeme unerlässlich, beispielsweise in der Automobilindustrie oder in...

This research aims to understand how the interactions across several social networks influence the visibility of a luxury brand's most relevant social network which acts as a showcase (Instagram). A data mining approach is proposed for modeling the number of likes on Instagram using 365 posts...

The paper reviews the evidence on the challenges of digitalization for direct (corporate profit) and indirect (consumption) taxation. Based on both anecdotal and empirical evidence, we evaluate ongoing developments at the OECD and European Union level and argue that there is no justification for...

Research analysis of small enterprises are still rare, due to lack of individual level data. Small enterprise failures are connected not only with their financial situation abut also with non-financial factors. In recent research we tend to apply more and more complex models. However, it is not...

There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of "Empirical Finance" and includes novel empirical research associated with financial data. One example...

The use of advanced predictive techniques and reasoning models has greatly assisted clinicians in improving the diagnosis, prognosis, and treatment of diabetes. Although numerous studies have focused on the relationship between abnormal blood glucose levels and diabetes, few have focused on the...

For automobile insurance, it has long been implied that when a policyholder made at least one claim in the prior year, the subsequent premium is likely to increase. When this happens, the policyholder may seek to switch to another insurance company to possibly avoid paying for a higher premium....

The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology...

In this paper, we present a new approach to design a multi-criteria supply chain network (SCN) under uncertainty. Demands, supplies, production costs, transportation costs, opening costs are all considered as uncertain parameters. We propose an approach based on evidence theory (ET), analytic...

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is...

We propose a Hawkish-Dovish (HD) indicator that measures the degree of 'hawkishness' or 'dovishness' of the media's perception of the ECB's tone at each press conference. We compare two methods to calculate the indicator: semantic orientation and Support Vector Machines text classification. We...

Durch den Einfluss der digitalen Transformation können Firmen umfangreiche Daten sammeln. Die Analyse dieser Daten kann Unternehmen helfen, wichtige Kundeninformationen zu gewinnen. Jedoch analysieren nur wenige Firmen ihre vorhandenen Daten, da ihnen die Kompetenzen hierzu fehlen. Darüber...

Diabetes has become an important public health issue in the twenty-first century, and dialysis treatment has become a large burden on the National Health Insurance of Taiwan. Diabetic nephropathy(DN) is the leading factor that determines whether patients with diabetes will require dialysis....

The goal of the paper is to present the overview of methodology of using credit scoring analysis with software Weka. German credit dataset was used in order to develop a decision tree with J.48 algorithm. We present characteristics of the dataset and the main results with the focus to the...

"This book explores the complex value and governance issues that arise as a consequence of the big data phenomenon and provides examples of best practices found in organizations concerning teaching and learning in academia and the business-industrial environment. It also investigates improving...

"This book provides the information on the machine learning techniques that can be in business problems in efficient way. It encourages the data Scientists to take a proactive attitude toward applying machine learning techniques in business. It increases evolutionary computation awareness in...

"This book fills a void in the systems and big data space with regard to human capital systems, data architecture, analytics, and systems. It is designed both as a text for graduate level courses in human resource systems, human capital analytics, and data mining as well as a resource for human...

"This book explores what drives profitability and more successful customer relationship management. It looks the behavior of any classifier used to classify sentiments in product reviews. It also develops common expert system to classify and visualize the predicted result"--