The field of MLOps (Machine Learning Operations), which focuses on effectively managing and operationalizing ML workflows, has grown because of the advancements in machine learning (ML). The goal of this study is to examine and contrast the difficulties encountered in the implementation of MLOps...

This paper explores the relationship between green bond markets and both green and conventional financial markets, while also evaluating their effectiveness as a climate finance instrument. Using the Thick Pen Measure of Association — a visually interpretable tool for analysing co-movement...

The digital transformation of industries has given rise to new categories of tech workers, such as software engineers and UX/UI designers, who now work alongside traditional engineers. This study explores the evolving relationship between these groups, focusing on work processes, status...

This paper explores the relationship between green bond markets and both green and conventional financial markets, while also evaluating their effectiveness as a climate finance instrument. Using the Thick Pen Measure of Association - a visually interpretable tool for analysing co-movement...

"This book presents statistics and data science methods for risk analytics in quantitative finance and insurance. Part I covers the background, financial models, and data analytical methods for market risk, credit risk, and operational risk in financial instruments, as well as models of risk...

Die Statistik als fachliche Disziplin muss sich in einem rasch wandelnden Umfeld behaupten, das durch den Aufstieg der Data Science, den Bedeutungszuwachs der künstlichen Intelligenz sowie neue Datenstrukturen charakterisiert wird. Wie kann sich die Statistik hier behaupten oder verlorenes...

The study explores key academic competencies and professional skills in data science in the context of the development of artificial intelligence, highlighting their importance in the business environment. Using the "2022 Stack Overflow Annual Developer Survey" dataset and machine learning...

This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck's law) and machine learning to detect the heat...

Access to high quality microdata is a precondition for the empirical investigation of many interrelationships in the economic and social sciences. Therefore, well-functioning research data infrastructure is a cornerstone of a successful science location. While other countries in Europe, such as...

Purpose - Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood. Design/methodology/approach - Conceptual variables that are representative of liquidity will be used to formulate the...

Der Einsatz von Daten mit unterschiedlicher Struktur zur Fehleranalyse in der Produktion ist eine große Herausforderung für Industrieunternehmen. Dieser Artikel zeigt einen prototypischen Lösungsweg auf, wie die Integration von unterschiedlich strukturierten Daten zur Fehleranalyse gelingen...

Abstract This article describes a data-driven case study for teaching and assessing students’ skills in marketing analytics, specifically in pricing. This case study combines teaching econometrics to analyze data and substantive marketing to derive managerial insights. The econometric...

The current Special Issue brought out the newest trends in Econophysics that have made use of the most recent available tools, such as Big Data. The emphasis of the reprint is on deciphering the effects of current world events, such as the repercussions of the recent war conflicts, the oil and...

This paper examines the phenomenon of residential segregation in Berlin over time using a dynamic clustering analysis approach. Previous research has examined the phenomenon of residential segregation in Berlin at a high spatial and temporal aggregation and statically, i.e. not over time. We...

The study explores key academic competencies and professional skills in data science in the context of the development of artificial intelligence, highlighting their importance in the business environment. Using the "2022 Stack Overflow Annual Developer Survey" dataset and machine learning...

This study presents an overview of data science, exploring the role of data scientists and the methods they employ to investigate analytical problems within business administration. It discusses the responsibilities of data scientists, emphasizing their multidisciplinary nature and the...

This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck's law) and machine learning to detect the heat...

Qualität digitalisieren - Das Workbook zur Umsetzung Durch die vielfältigen Möglichkeiten von Big Data, Artifical Intelligence (KI), Predictive Analytics, Data Science, Process Mining etc. einschließlich der damit verbundenen Kommunikation und Vernetzung verändert sich auch das...

"The book features a highly selective collection of relevant and advanced scientific research by world-renowned researchers and experts in the field. It aims to provide concise and relevant answers to a wide range of questions at the crossroads of reflexivity on the adoption of innovative...

This paper surveys the relevant existing literature that can help researchers and policy makers understand the drivers of competition in markets that constitute the provision of artificial intelligence products. The focus is on three broad markets: training data, input data, and AI predictions....

Kann man mit Machine-Learning-Algorithmen prognostizieren, ob es nach einem erfolgten Wohnungseinbruchdiebstahl in kurzer Zeit und in unmittelbarer Nähe zu Nachfolgedelikten kommen wird? Dieser Frage geht der vorliegende Artikel anhand von Daten aus Baden-Württemberg nach. Dabei zieht er einen...

Kann man mit Machine-Learning-Algorithmen prognostizieren, ob es nach einem erfolgten Wohnungseinbruchdiebstahl in kurzer Zeit und in unmittelbarer Nähe zu Nachfolgedelikten kommen wird? Dieser Frage geht der vorliegende Artikel anhand von Daten aus Baden-Württemberg nach. Dabei zieht er einen...

Fourth Industrial Revolution is describes as exponential growth of several key technological fields’ concepts, such as intelligent materials, cloud computing, cyber-physical systems, data exchange, the Internet of things and blockchain technology. At its core, data represents a post-industrial...

Data science and big data analytics (DS &BDA) methodologies and tools are used extensively in supply chains and logistics (SC &L). However, the existing insights are scattered over different literature sources and there is a lack of a structured and unbiased review methodology to systematise DS...