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Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
Leveraging textual information for improving decision making in the business process lifecycle
(2015)
Business process implementations fail, because requirements are elicited incompletely. At the same time, a huge amount of unstructured data is not used for decision-making during the business process lifecycle. Data from questionnaires and interviews is collected but not exploited because the effort doing so is too high. Therefore, this paper shows how to leverage textual information for improving decision making in the business process lifecycle. To do so, text mining is used for analyzing questionnaires and interviews.
Digital enterprise architecture management in tourism : state of the art and future directions
(2018)
The advance of information technology impacts tourism more than many other industries, due to the service character of its products. Most offerings in tourism are immaterial in nature and challenging in coordination. Therefore, the alignment of IT and strategy and digitization is of crucial importance to enterprises in tourism. To cope with the resulting challenges, methods for the management of enterprise architectures are necessary. Therefore, we scrutinize approaches for managing enterprise architectures based on a literature research. We found many areas for future research on the use of enterprise architecture in tourism.
Business process models provide a considerable number of benefits for enterprises and organizations, but the creation of such models is costly and time-consuming, which slows down the organizational adoption of business process modeling. Social paradigms pave new ways for business process modeling by integrating stakeholders and leveraging knowledge sources. However, empirical research about the impact of social paradigms on costs of business process modeling is sparse. A better understanding of their impact could help to reduce the cost of business process modeling and improve decision-making on BPM activities. The paper constributes to this field by reporting about an empirical investigation via survey research on the perceived influence of different cost factors among experts. Our results indicate that different cost components, as well as the use of social paradigms, influence cost.
Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.
A new class of information system architecture, decision-oriented service systems, is spreading more and more. Decision-oriented service systems provide services that support decisions in business processes and products based on the capabilities of cloud-computing environments. To pave the way for the creation of design methods of business processes and products based on decision-oriented service systems, this article introduces a capability-oriented approach. Starting from technological capabilities, more abstract operational and dynamic capabilities are created. The framework created is based on an integrated conceptualization of decision-oriented service systems that allows capturing synergetic effects. By creating the framework, the gap between the technological capabilities of technologies and the strategic goals of enterprises shall be narrowed.
An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.
AI technologies such as deep learning provide promising advances in many areas. Using these technologies, enterprises and organizations implement new business models and capabilities. In the beginning, AI-technologies have been deployed in an experimental environment. AI-based applications have been created in an ad-hoc manner and without methodological guidance or engineering approach. Due to the increasing importance of AI-technologies, however, a more structured approach is necessary that enable the methodological engineering of AI-based applications. Therefore, we develop in this paper first steps towards methodological engineering of AI-based applications. First, we identify some important differences between the technological foundations of AI- technologies, in particular deep learning, and traditional information technologies. Then we create a framework that enables to engineer AI-applications using four steps: identification of an AI-application type, sub-type identification, lifecycle phase, and definition of details. The introduced framework considers that AI-applications use an inductive approach to infer knowledge from huge collections and streams of data. It not only enables the rapid development of AI-application but also the efficient sharing of knowledge on AI-applications.
Modern enterprises reshape and transform continuously by a multitude of management processes with different perspectives. They range from business process management to IT service management and the management of the information systems. Enterprise Architecture (EA) management seeks to provide such a perspective and to align the diverse management perspectives. Therefore, EA management cannot rely on hierarchic - in a tayloristic manner designed - management processes to achieve and promote this alignment. It, conversely, has to apply bottom-up, information-centered coordination mechanisms to ensure that different management processes are aligned with each other and enterprise strategy. Social software provides such a bottom-up mechanism for providing support within EAM-processes. Consequently, challenges of EA management processes are investigated, and contributions of social software presented. A cockpit provides interactive functions and visualization methods to cope with this complexity and enable the practical use of social software in enterprise architecture management processes.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
Digitization is more than using digital technologies to transfer data and perform computations and tasks. Digitization embraces disruptive effects of digital technologies on economy and society. To capture these effects, two perspectives are introduced, the product and the value-creation perspective. In the product perspective, digitization enables the transition from material, static products to interactive and configurable services. In the value-creation perspective, digitization facilitates the transition from centralized, isolated models of value creation, to bidirectional, co-creation oriented approaches of value creation.
Der folgende Artikel befasst sich mit Wearables für Pferde. Ziel ist es, die Sicherheit der Tiere bei einem Ausbruch von einer Weide zu erhöhen und damit Personen- und Sachschäden zu minimieren. Hierzu wird der Stand der Technik zur Standortbestimmung im Freien zusammengetragen und durch eine Klassifizierung der unterschiedlichen Ansätze ermittelt, welche Standortbestimmung pferdegerecht erscheint. Zudem soll ein Fragebogen konzipiert werden, um Charakteristiken und Funktionalitäten für einen Prototypen festzustellen.
Introduction: Telemedicine reduces greenhouse gas emissions (CO2eq); however, results of studies vary extremely in dependence of the setting. This is the first study to focus on effects of telemedicine on CO2 imprint of primary care.
Methods: We conducted a comprehensive retrospective study to analyze total CO2eq emissions of kilometers (km) saved by telemedical consultations. We categorized prevented and provoked patient journeys, including pharmacy visits. We calculated CO2eq emission savings through primary care telemedical consultations in comparison to those that would have occurred without telemedicine. We used the comprehensive footprint approach, including all telemedical cases and the CO2eq emissions by the telemedicine center infrastructure. In order to determine the net ratio of CO2eq emissions avoided by the telemedical center, we calculated the emissions associated with the provision of telemedical consultations (including also the total consumption of physicians’ workstations) and subtracted them from the total of avoided CO2eq emissions. Furthermore, we also considered patient cases in our calculation that needed to have an in-person visit after the telemedical consultation. We calculated the savings taking into account the source of the consumed energy (renewable or not).
Results: 433 890 telemedical consultations overall helped save 1 800 391 km in travel. On average, 1 telemedical consultation saved 4.15 km of individual transport and consumed 0.15 kWh. We detected savings in almost every cluster of patients. After subtracting the CO2eq emissions caused by the telemedical center, the data reveal savings of 247.1 net tons of CO2eq emissions in total and of 0.57 kg CO2eq per telemedical consultation. The comprehensive footprint approach thus indicated a reduced footprint due to telemedicine in primary care.
Discussion: Integrating a telemedical center into the health care system reduces the CO2 footprint of primary care medicine; this is true even in a densely populated country with little use of cars like Switzerland. The insight of this study complements previous studies that focused on narrower aspects of telemedical consultations.
Digital companies need information systems to implement their business processes end-to-end. BPM systems are promising candidates for that, because they are highly adaptable due to their business process model-driven operation mode. End-to-end processes contain different types of sub-processes that are either procedural, data-driven or business rule-based. Modern BPM systems support modeling notations for all these types of sub-processes. Moreover, end-to-end processes contain parts of shadow processing, so consequently, they must be supported in a performant way, too. BPMN seems to be the adequate notation for modeling these parts due to its procedural nature. Further, BPMN provides several elements that enable the modeling of parallel executions which are very interesting for accelerating shadow processing parts of the process. The present paper will observe the limitations and potentials of BPM systems for a high-performance execution of BPMN models representing shadow processing parts of a business process.
Diese Arbeit beschäftigt sich mit dem neuen elektronischen Personalausweis. Zum einen werden in diesem Paper die Sicherheitsziele des Personalausweises und die technische Umsetzung der Architektur und Protokolle erklärt. Es wird der Ablauf einer Online-Identifizierung für einen Nutzer mithilfe des Ausweises aufgezeigt. Risiken und Schwachstellen der Technologie im Software- und Hardwarebereich werden diskutiert und die bereits erfolgten Hack-Angriffe aufgezeigt. Die Arbeit legt Möglichkeiten dar, wie sich der Nutzer vor Angriffen schützen kann. Es werden die Gründe genannt, warum der neue Personalausweis online nur schwar Anklang findet und warum die Aufklärung über die zur Verfügung stehenden Anwendungen, eine Preisreduzierung der Lesegeräte sowie die vom Europa-Parlament und Europarat erlassene eIDAS-Verordnung nicht helfen werden, um die Nutzung voranzutreiben. Ergebnisse hierfür liefert eine Nutzerstudie. Zum anderen werden Ideen genannt, wie die Nutzung der elektronischen Funktionen des Ausweises stattdessen zu fördern ist.
In recent years, artificial intelligence (AI) has increasingly become a relevant technology for many companies. While there are a number of studies that highlight challenges and success factors in the adoption of AI, there is a lack of guidance for firms on how to approach the topic in a holistic and strategic way. The aim of this study is therefore to develop a conceptual framework for corporate AI strategy. To address this aim, a systematic literature review of a wide spectrum of AI-related research is conducted, and the results are analyzed based on an inductive coding approach. An important conclusion is that companies should consider diverse aspects when formulating an AI strategy, ranging from technological questions to corporate culture and human resources. This study contributes to knowledge by proposing a novel, comprehensive framework to foster the understanding of crucial aspects that need to be considered when using the emerging technology of AI in a corporate context.
Ganz gleich, ob im privaten oder beruflichen Alltag, begleiten uns digitale Medien heute nahezu überall. Dabei dienen sie nicht nur zur Unterhaltung, sondern helfen uns, Arbeitsabläufe effizienter und produktiver durchzuführen. Doch die Arbeit des Menschen ist bei Weitem nicht überflüssig geworden. Durch die steigenden Anforderungen ist die Nachfrage nach qualifiziertem Fachpersonal heute höher denn je. Währenddessen müssen Mitarbeiter in der Lage sein, mit der rasanten Entwicklung neuer Produkte und Technologien Schritt zu halten. Dabei ist eine qualitative Aus- und Weiterbildung unumgänglich. Beginnend mit der Bildung von Medienkompetenz in Schulen bis hin zur Fach- und Berufsbildung sowie beruflichen Weiterbildung, muss der Umgang mit digitalen Technologien gelehrt sein. Darüber hinaus bieten diese Technologien neue Potenziale zur Verbesserung von Bildungskonzepten und können zudem dabei helfen, den Lernerfolg zu steigern.
Diese Arbeit beschäftigt sich mit der Evaluation einer VR-basierten Lernumgebung und untersucht mögliche Auswirkungen auf den Lernerfolg durch die verkörperte Darstellung eines virtuellen Instruktors. Dazu wurde die technische Implementierung einer kollaborativen Lernumgebung vorgenommen, mit welcher anschließend eine Versuchsreihe mit 16 Probanden durchgeführt wurde. Im Hinblick auf eine mögliche Steigerung der Effizienz in der eigenständigen Bewältigung von Montageaufgaben nach unterschiedlichen Instruktionsarten, wurden keine signifikanten Leistungsverbesserungen festgestellt.
Systemische Betrachtung des therapeutischen Roboters Paro im Vergleich zu dem Haustierroboter AIBO
(2020)
Roboter sind in der heutigen Zeit nicht nur in der Industrie zu finden, sondern werden immer häufiger in privaten Lebensbereichen eingesetzt. Ein Beispiel hierfür ist der soziale Therapie-Roboter Paro. Dieser ist dem Verhalten und Aussehen einer jungen Robbe nachempfunden, drückt Gefühle aus und wird besonders in Pflegeheimen eingesetzt. Dabei zeigt er positive Auswirkungen auf das Wohlbefinden pflegebedürftiger Menschen. Diese Arbeit stellt den Roboter Paro in einer systemischen Analyse dar: hierbei werden Systemkontext, Anwendungsfälle, Anforderungen und Struktur betrachtet. Anschließend erfolgt eine Analyse des Haustierroboters AIBO, welcher einem Welpen ähnelt und verstärkt der Unterhaltung von Privatpersonen dient. Es werden Gemeinsamkeiten und Unterschiede zwischen den Systemen herausgearbeitet. Dabei wird ersichtlich, dass beide Systeme dem Nutzer vorrangig Gesellschaft leisten, jedoch verschiedene Anforderungen besitzen und in unterschiedlichen Anwendungsdomänen eingesetzt werden. Zudem besitzt AIBO vielfältigere Fähigkeiten und einen höheren Bewegungsgrad als Paro. Dies spiegelt sich in einer komplexeren Struktur der Hardware wider.
Ever since the 1980s, researchers in computer science and robotics have been working on making autonomous cars. Due to recent breakthroughs in research and devel- opment, such as the Bertha Benz Project [ZBS+14], the goal of fully autonomous vehicles seems closer than ever before. Yet a lot of questions remain unanswered. Especially now that the automotive industry moves towards autonomous systems in series production vehicles, the task of precise localization has to be solved with automotive grade sensors and keep memory and processing consumption at a mini- mum. This thesis investigates the Simultaneous Localization and Mapping (SLAM) prob- lem for autonomous driving scenarios on a parking lot using low cost automotive sensors. The main focus is herby devoted to the RAdio Detection And Ranging (RADAR) sensor, which has not been widely analyzed in an autonomous driving scenario so far, even though they are abundant in the automotive industry for ap- plications such as Adaptive Cruise Control (ACC). Due to the high noise floor, the radar sensor has widely been disregarded in the Intelligent Transportation Systems and Robotics communities with regards to SLAM applications. However in this thesis, it is shown that the RADAR sensor proves to be an affordable, robust and precise sensor, when modeling its physical properties correctly. In this regard, a GraphSLAM based framework is introduced, which extracts features from the RADAR sensor and generates an optimized map of the surroundings using the RADAR sensor alone. This framework is used to enable crowd based localization, which is not limited to the RADAR sensor alone. By integrating an automotive Light Detection and Ranging (LiDAR) and stereo camera sensor, a robust and precise localization system can be built that that is suitable for autonomous driving even in complex parking lot scenarios. It it is thereby shown that the RADAR sensor is strongly contributing to obtaining good results in a sensor fusion setup. These results were obtained on an extensive dataset on a parking lot, which has been recorded over the course of several months. It contains different weather conditions, different configurations of parked cars and a multitude of different trajectories to validate the approaches described in this thesis and to come to the conclusion that the RADAR sensor is a reliable sensor in series autonomous driving systems, both in a multi sensor framework and as a single component for localization.
On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.