TY - CHAP A1 - Schmitz, Manfred A1 - Dietze, Christian A1 - Czarnecki, Christian ED - Urbach, Nils ED - Röglinger, Maximilian T1 - Enabling digital transformation through robotic process automation at Deutsche Telekom T2 - Enabling digital transformation through robotic process automation at Deutsche Telekom N2 - Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data. Y1 - 2019 SN - 978-3-319-95272-7 U6 - http://dx.doi.org/10.1007/978-3-319-95273-4_2 SP - 15 EP - 33 PB - Springer CY - Cham ER - TY - CHAP A1 - Bensberg, Frank A1 - Buscher, Gandalf A1 - Czarnecki, Christian ED - Nissen, Volker T1 - Digital transformation and IT topics in the consulting industry: a labor market perspective T2 - Advances in consulting research : recent findings and practical cases N2 - Information technologies, such as big data analytics, cloud computing, cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns. Y1 - 2019 SN - 978-3-319-95998-6 SN - 978-3-030-07125-7 SN - 978-3-319-95999-3 U6 - http://dx.doi.org/10.1007/978-3-319-95999-3_16 SP - 341 EP - 357 PB - Springer CY - Cham ER - TY - CHAP A1 - Auth, Gunnar A1 - Czarnecki, Christian A1 - Bensberg, Frank A1 - Thor, Andreas ED - Barton, Thomas ED - Müller, Christian ED - Seel, Christian T1 - Digitalisierung des Forschungsprozesses aus Sicht von Forschenden – durch Serviceintegration zum persönlichen Forschungsinformationssystem T2 - Hochschulen in Zeiten der Digitalisierung : Lehre, Forschung und Organisation N2 - In der Diskussion über die Digitalisierung der Forschung spielt die Frage nach der optimalen IT-Unterstützung für Forschende eine wichtige Rolle. Forschende können heute an ihren Hochschulen bzw. Wissenschaftseinrichtungen auf ein breites Angebot interner IT-Dienstleistungen zurückgreifen, das auch kooperative IT-Dienste umfasst, die von mehreren Institutionen in Zusammenarbeit bereitgestellt werden. Außerhalb der eigenen Organisation und des weiteren Verbunds hat sich im Internet zudem ein breites externes Angebot an innovativen, häufig kostenlos nutzbaren Onlinediensten entwickelt. Neben horizontalen Onlinediensten, die sich prinzipiell an jeden Internetnutzer richten (bspw. Dropbox, Twitter, WhatsApp), nimmt auch die Zahl von vertikalen Diensten für wissenschaftliche bzw. Forschungszwecke immer weiter zu (bspw. GoogleScholar, ResearchGate, figshare). Für Forschende eröffnen sich damit vielfältige neue Möglichkeiten, ihren individuellen Forschungsprozess durch digitale Werkzeuge zu verbessern. Aufgrund rechtlicher, technischer und personeller Restriktionen können jedoch interne Dienstleister bei der Identifizierung, Auswahl und Nutzung externer Onlinedienste nur wenig Unterstützung leisten. Aus einer serviceorientierten Perspektive stehen Forschende zunehmend vor dem Problem, wie sich heterogene IT-Dienste interner und externer Anbieter in den eigenen Forschungsprozess integrieren lassen. Als Lösungsansatz skizziert das Kapitel das Konzept eines persönlichen Forschungsinformationssystems nach Gesichtspunkten eines digitalen Servicesystems. KW - Digitalisierung KW - Forschung KW - Forschungsprozess KW - Forschungsinformationssystem KW - Serviceintegration Y1 - 2019 SN - 978-3-658-26617-2 (Print) SN - 978-3-658-26618-9 (Online) U6 - http://dx.doi.org/10.1007/978-3-658-26618-9_17 SP - 287 EP - 307 PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Czarnecki, Christian A1 - Bensberg, Frank T1 - Enhanced Telecom Operations Map (eTOM) T2 - Enzyklopädie der Wirtschaftsinformatik Y1 - 2019 N1 - Online-Lexikon SP - 1 EP - 4 PB - Gito CY - Berlin ER - TY - CHAP A1 - Czarnecki, Christian T1 - Robotergesteuerte Prozessautomatisierung T2 - Enzyklopädie der Wirtschaftsinformatik T2 - Robotic Process Automation (RPA) Y1 - 2019 N1 - Online-Lexikon SP - 1 EP - 3 PB - Gito CY - Berlin ER - TY - CHAP A1 - Czarnecki, Christian A1 - Bensberg, Frank T1 - Telekommunikationsunternehmen, Anwendungssysteme für T2 - Enzyklopädie der Wirtschaftsinformatik Y1 - 2019 N1 - Online-Lexikon SP - 1 EP - 3 PB - Gito CY - Berlin ER - TY - CHAP A1 - Kurz, Melanie T1 - Betrifft Design : von historischen Zukunftsperspektiven zu gegenwärtigen Vergangenheitssehnsüchten T2 - Positionen des Neuen : Zukunft im Design Y1 - 2019 SN - 978-3-89986-301-7 SP - 136 EP - 144 PB - avedition CY - Stuttgart ER - TY - CHAP A1 - Golland, Alexander ED - Taeger, Jürgen ED - Gabel, Detlev T1 - Kommentierung von Artikel 94 bis 99 Datenschutz-Grundverordnung T2 - DSGVO-BDSG N2 - Das Werk kommentiert leicht verständlich, aktuell und praxisnah die DSGVO wie auch das neue BDSG. Datenverarbeiter erhalten damit eine umfassende Darstellung mit Handlungsempfehlungen zum gesamten neuen Datenschutzrecht. KW - Bundesdatenschutzgesetz (2017) KW - EU-DSGVO KW - EU-Datenschutzgrundverordnung KW - Internationales Recht / Europarecht KW - Datenschutzrecht Y1 - 2019 SN - 978-3-8005-1659-9 N1 - Inhaltsverzeichnis https://d-nb.info/1149714018/04 PB - Fachmedien Recht und Wirtschaft CY - Frankfurt am Main ET - 3., völlig neue bearbeitete und wesentlich erweiterte Auflage ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Simon, Nicolai A1 - Pelz, Peter F. T1 - Finding global-optimal gearbox designs for battery electric vehicles T2 - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019 N2 - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements. KW - Powertrain KW - Gearbox KW - Optimization KW - BEV KW - WLTP Y1 - 2019 SN - 978-3-030-21802-7 U6 - http://dx.doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER -