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Die vorliegende Arbeit untersucht das strategische Risikomanagement bei Spielertransfers im Profifußball, einem Bereich, der aufgrund massiv steigender Transferzahlungen und einer hohen Marktvolatilität von existenzieller Bedeutung für moderne Sportorganisationen ist. Ziel der Untersuchung ist die systematische Analyse der komplexen Chancen- und Risikostrukturen innerhalb des Transferprozesses sowie die Erarbeitung eines wissenschaftlich fundierten Rahmens zu deren Steuerung. Die methodische Vorgehensweise orientiert sich am ISO 31000-Standard, wodurch ein strukturierter Prozess aus Risikoidentifikation, -bewertung, -bewältigung und kontinuierlicher Überwachung etabliert wird.
Im Fokus der inhaltlichen Auseinandersetzung steht die Kategorisierung von Transferrisiken in sechs spezifische Dimensionen: spielerbezogene, sportliche, sozial-psychologische, juristisch-reputative, finanzielle sowie organisatorische Faktoren.
Im Fokus der inhaltlichen Auseinandersetzung steht die Kategorisierung von Transferrisiken in sechs spezifische Dimensionen: spielerbezogene, sportliche, sozial-psychologische, juristisch-reputative, finanzielle sowie organisatorische Faktoren.
378 Downloads09.03.2026
Datei downloaden Aus Sicht des Controlling wirken bestimmte Ansätze im Risikomanagement nicht nur irritierend, sondern sogar provozierend. Besonders jene, die Controlling als integralen Bestandteil – organisational, nicht inhaltlich - des Risikomanagements verstehen. Es erscheint sinnvoll, Herkunft und Entwicklung derartiger Ansätze zu beleuchten und kritisch zu würdigen. Nicht zuletzt deshalb, als sie die Trennung von Controlling und Risikomanagement maßgeblich verantworten. Zudem haben diese Ansätze eine weite Verbreitung erfahren und prägen sogar das Risikomanagement ganzer Branchen.
1915 Downloads07.08.2025
Datei downloaden The invasion of Ukraine by Russian forces began on 24 February 2022. The Russian war against Ukraine has seen post Cold War hopes for a peaceful world order disappear almost overnight. But this war of aggression could be a turning point in history not just for the West but also for Russia itself. The background to the crisis is complex. For a long time now, the situation has been extremely fragile, as critical voices have repeatedly pointed out. At the 43rd Munich "Security Conference" back in 2007, the Russian President, Vladimir Putin, talked about the risks of NATO expansion to the east and a unipolar world. He called NATO's eastward expansion "a provocative factor that reduces the level of mutual trust". To get a better understanding of the key political and economic challenges brought about by the conflict and possible scenarios in a disordered world, we spoke to Emeritus Professor Dr. Günther Schmid, a renowned expert on international security policy.
7059 Downloads13.05.2022
Datei downloaden An analysis for 2021/2022 on pandemic development in Germany and a model shift to North Rhine-Westphalia (NRW) with variant B.1.1.529
Authors: Farhad Khakzad, Max Düren, Patrick Spitzer
Authors: Farhad Khakzad, Max Düren, Patrick Spitzer
2630 Downloads21.12.2021
Datei downloaden Die Fragen, wo künftig im Arbeitprozess zwischen Robotern, Algorithmen und (teil-) automatisierten Prozessabläufen der Manager oder Mitarbeiter steht, was seine Aufgaben und Ziele sind und welche Kompetenzen er dafür braucht, sind als erstes zu beantworten. Dann sollten Ausbildung, Coaching, etc. vorhandene Gaps zwischen dem "neuen Soll" und dem (alten) Ist füllen helfen. [Autoren: Josef Scherer / Ann-Kathrin Birker]
4157 Downloads21.04.2020
Datei downloaden Vortrag zur verzerrten Risikowahrnehmung: "Krisen, Kriege, Katastrophen & Disruption: Wie riskant ist die Welt wirklich?" von Prof. Dr. Werner Gleißner, Technische Universität Dresden [Oktober 2019]
8526 Downloads30.03.2020
Datei downloaden Die Corona-Krise zeigt, dass Staat und Unternehmen viel zu wenig auf Krisensituationen vorbereitet sind. Risiko- und Business Continuity Management, (persönlicher) Risikokoffer und die "Klaviatur" existenzsichernder Maßnahmen sollte sofort angegangen werden. Jeder verlorene Tag ist einer zuviel.
4659 Downloads13.03.2020
Datei downloaden The annual RiskNET Summit is the most important conference for risk managers in the German-speaking world. Its credo: to convey well-founded contents in theory and practice, to provide a holistic view of the risk map as well as sufficient freedom for the networking of risk, compliance and governance managers.
4758 Downloads21.01.2020
Datei downloaden Der jährlich stattfindende RiskNET Summit ist die wichtigste Konferenz der Risikomanager im deutschsprachigen Raum. Sein Credo: Fundierte Inhalte in Theorie und Praxis vermitteln, ein ganzheitlicher Blick auf die Risikolandkarte sowie genügend Freiraum für das Networking von Risiko-, Compliance- und Governance-Managern ermöglichen.
4485 Downloads21.01.2020
Datei downloaden In 1890, a company was founded in the USA that eventually developed into a leading brand. 80 years after its inception, the company had a market share of approximately 90% in its core field of business: film and photography. The company’s name is Kodak. Kodak was known for its top performance and the forward-looking view of its engineers. These engineers invented the digital camera in 1975. In spite of its long and successful company history, Kodak went bankrupt in 2012. The opportunities provided by the company’s breakthrough technology and its engineering prowess may not have been fully leveraged by the management. Kodak may provide a useful lesson and an incentive for leaders to manage and leverage disruptive technologies.
From today’s view, we believe that machine learning and deep learning are such disruptive technologies that should be leveraged. Advanced computing methods have become more and more popular alongside advances in the emergence of big data. In the finance and banking sector, increasing demand for more efficient approaches has been seen especially in the field of machine learning. The field was originally devoted to developing algorithms in artificial intelligence. In response to its significant advances, however, machine learning and its subfield of deep learning have emerged as breakthroughs with vast applications in a wide array of fields.
In our paper, we discuss the existing definitions as well as our thoughts on some of the applications of machine learning and deep learning. We will provide an insight into the significance of artificial intelligence in the banking industry, in particular and its response to big data market forces, with a focus on German Banks. To illustrate the breadth of the field’s significance, we will also address the automotive industry in Germany and its connection to machine learning technologies. To deepen our understanding of the subject, we will explain the mathematical background behind deep learning and its intersection with artificial neural networks. We will provide a brief look into the subject of Blockchain and its relevance to artificial intelligence. A second part of this paper will analyze the practical implications (use cases) of the technologies and their expected developments in the short and long term.
[Authors: Farhad Khakzad, Sangmeng Li, Pablo Arboleda]
From today’s view, we believe that machine learning and deep learning are such disruptive technologies that should be leveraged. Advanced computing methods have become more and more popular alongside advances in the emergence of big data. In the finance and banking sector, increasing demand for more efficient approaches has been seen especially in the field of machine learning. The field was originally devoted to developing algorithms in artificial intelligence. In response to its significant advances, however, machine learning and its subfield of deep learning have emerged as breakthroughs with vast applications in a wide array of fields.
In our paper, we discuss the existing definitions as well as our thoughts on some of the applications of machine learning and deep learning. We will provide an insight into the significance of artificial intelligence in the banking industry, in particular and its response to big data market forces, with a focus on German Banks. To illustrate the breadth of the field’s significance, we will also address the automotive industry in Germany and its connection to machine learning technologies. To deepen our understanding of the subject, we will explain the mathematical background behind deep learning and its intersection with artificial neural networks. We will provide a brief look into the subject of Blockchain and its relevance to artificial intelligence. A second part of this paper will analyze the practical implications (use cases) of the technologies and their expected developments in the short and long term.
[Authors: Farhad Khakzad, Sangmeng Li, Pablo Arboleda]
5492 Downloads15.02.2018
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