650 Management
Refine
Year of publication
- 2020 (25) (remove)
Document Type
- Journal article (15)
- Book (3)
- Book chapter (3)
- Conference proceeding (3)
- Report (1)
Is part of the Bibliography
- yes (25)
Institute
- ESB Business School (18)
- Informatik (6)
- Technik (1)
Publisher
- Springer (8)
- Springer Gabler (3)
- Verl.-Gruppe Handelsblatt (2)
- AfM, Arbeitsgemeinschaft für Marketing (1)
- Elsevier (1)
- Emerald (1)
- Hochschule Reutlingen (1)
- IGI Global (1)
- IdW-Verlag (1)
- MIT Center for Information Systems Research (1)
Energieversorgungsunternehmen sehen sich gegenwärtig und mit dem Voranschreiten der Energiewende mit einer Vielzahl von Herausforderungen konfrontiert. Die zunehmende Dezentralisierung und Digitalisierung der Energiewirtschaft zwingen die EVU zusammen mit dem steigenden Wettbewerbs- und Kostendruck dazu, von den gewohnten Pfaden des Commodity-Geschäfts abzuweichen und neue Produkte und Dienstleistungen zu entwickeln sowie neue Geschäftsfelder zu erschließen. Die Kunden rücken mit ihren zunehmend individualisierten und komplexen Bedürfnissen in den Mittelpunkt des Interesses. Wollen EVU langfristig am Markt erfolgreich sein, müssen sie sich vom klassischen Energieversorger als Anbieter von einfachen Produkten hin zu innovativen, kundenzentrierten Energiedienstleistern weiterentwickeln. Ein Schlüssel hierfür stellt die Entwicklung von Energiedienstleistungen dar. Gleichzeitig tun sich viele EVU mit dieser Entwicklung jedoch aufgrund interner Hemmnisse wie fehlender personeller Kapazitäten, einer angesichts des dynamischen Marktumfeldes unflexiblen Organisation mit langen Entwicklungsdauern, geringen Budgets sowie mangelndem fachlichen und/ oder methodischen Know-How schwer. Dies zeigen die Ergebnisse der vorliegenden Studie unter Geschäftsführern und Vorständen in der Energiewirtschaft.
Background. We describe and provide an initial evaluation of the Climate Action Simulation, a simulation-based role playing game that enables participants to learn for themselves about the response of the climate-energy system to potential policies and actions. Participants gain an understanding of the scale and urgency of climate action, the impact of different policies and actions, and the dynamics and interactions of different policy choices.
Intervention. The Climate Action Simulation combines an interactive computer model, En-ROADS, with a role play in which participants make decisions about energy and climate policy. They learn about the dynamics of the climate and energy systems as they discover how En-ROADS responds to their own climate-energy decisions.
Methods. We evaluated learning outcomes from the Climate Action Simulation using pre- and post-simulation surveys as well as a focus group.
Results. Analysis of survey results showed that the Climate Action Simulation increases participants’ knowledge about the scale of emissions reductions and policies and actions needed to address climate change. Their personal and emotional engagement with climate change also grew. Focus group participants were overwhelmingly positive about the Climate Action Simulation, saying it left them feeling empowered to make a positive difference in addressing the climate challenge.
This study investigates empirically the development of working capital management and its impact on profitability and shareholder value in Germany. We analyse panel data of 115 firms listed on the German Prime Standard, covering the period from 2011 to 2017. The results provide evidence that efficient working capital management, indicated by a shorter cash conversion cycle, deteriorated over time, but that a shorter cash conversion has a positive impact on profitability and shareholder value. The findings highlight the need that managers should give greater priority to working capital optimization, even in a low-interest environment. The paper contributes to the literature by advancing this research area in Germany, and it is the first study investigating shareholder relationship with working capital management and all its determinants.
On the design of an urban data and modeling platform and its application to urban district analyses
(2020)
An integrated urban platform is the essential software infrastructure for smart, sustainable and resilitent city planning, operation and maintenance. Today such platforms are mostly designed to handle and analyze large and heterogeneous urban data sets from very different domains. Modeling and optimization functionalities are usually not part of the software concepts. However, such functionalities are considered crucial by the authors to develop transformation scenarios and to optimized smart city operation. An urban platform needs to handle multiple scales in the time and spatial domain, ranging from long term population and land use change to hourly or sub-hourly matching of renewable energy supply and urban energy demand.
Automatic classification of rotating machinery defects using Machine Learning (ML) algorithms
(2020)
Electric machines and motors have been the subject of enormous development. New concepts in design and control allow expanding their applications in different fields. The vast amount of data have been collected almost in any domain of interest. They can be static; that is to say, they represent real-world processes at a fixed point of time. Vibration analysis and vibration monitoring, including how to detect and monitor anomalies in vibration data are widely used techniques for predictive maintenance in high-speed rotating machines. However, accurately identifying the presence of a bearing fault can be challenging in practice, especially when the failure is still at its incipient stage, and the signal-to-noise ratio of the monitored signal is small. The main objective of this work is to design a system that will analyze the vibration signals of a rotating machine, based on recorded data from sensors, in the time/frequency domain. As a consequence of such substantial interest, there has been a dramatic increase of interest in applying Machine Learning (ML) algorithms to this task. An ML system will be used to classify and detect abnormal behavior and recognize the different levels of machine operation modes. The proposed solution can be deployed as predictive maintenance for Industry 4.0.
Power line communications (PLC) reuse the existing power-grid infrastructure for the transmission of data signals. As power line the communication technology does not require a dedicated network setup, it can be used to connect a multitude of sensors and Internet of Things (IoT) devices. Those IoT devices could be deployed in homes, streets, or industrial environments for sensing and to control related applications. The key challenge faced by future IoT-oriented narrowband PLC networks is to provide a high quality of service (QoS). In fact, the power line channel has been traditionally considered too hostile. Combined with the fact that spectrum is a scarce resource and interference from other users, this requirement calls for means to increase spectral efficiency radically and to improve link reliability. However, the research activities carried out in the last decade have shown that it is a suitable technology for a large number of applications. Motivated by the relevant impact of PLC on IoT, this paper proposed a cooperative spectrum allocation in IoT-oriented narrowband PLC networks using an iterative water-filling algorithm.
Our paper gives first answers on a fundamental question: how can the design of architectures of intelligent digital systems and services be accomplished methodologically? Intelligent systems and services are the goals of many current digitalization efforts today and part of massive digital transformation efforts based on digital technologies. Digital systems and services are the foundation of digital platforms and ecosystems. Digtalization disrupts existing businesses, technologies, and economies and promotes the architecture of open environments. This has a strong impact on new value-added opportunities and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, and social enterprise networks systems are important enablers of digitalization. The current publication presents our research on the architecture of intelligent digital ecosystems and products and services influenced by the service-dominant logic. We present original methodological extensions and a new reference model for digital architectures with an integral service and value perspective to model intelligent systems and services that effectively align digital strategies and architectures with artificial intelligence as main elements to support intelligent digitalization.
his book highlights new trends and challenges in intelligent systems, which play an important part in the digital transformation of many areas of science and practice. It includes papers offering a deeper understanding of the human-centred perspective on artificial intelligence, of intelligent value co-creation, ethics, value-oriented digital models, transparency, and intelligent digital architectures and engineering to support digital services and intelligent systems, the transformation of structures in digital businesses and intelligent systems based on human practices, as well as the study of interaction and the co-adaptation of humans and systems. All papers were originally presented at the International KES Conference on Human Centred Intelligent Systems 2020 (KES HCIS 2020), held on June 17–19, 2020, in Split, Croatia.
Service Blueprinting
(2020)
Ein Ansatz des Dienstleistungsmanagements, mit dessen Hilfe Gesundheitsleistungen ganz aus Perspektive der behandelten Person und ihrer Customer Journey durch den Leistungsprozess analysiert werden kann, ist das sogenannte Service Blueprinting. Die vorliegende Fallstudie beginnt mit einer kurzen Einführung zur Begründung und zum Vorgehen dieses Ansatzes. Im Anschluss wird der Ansatz anhand der holprigen Customer Journey des imaginären Patienten Torben Schulz im Rahmen einer Bandscheiben-Operation kritisch diskutiert und auf einen Teilaspekt dieser Dienstleistung angewendet.