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Identifikation von Schlaf- und Wachzuständen durch die Auswertung von Atem- und Bewegungssignalen
(2021)
In the current age of innovative business financing opportunities available from fintech apps, social media crowdfunding sites such as Kickstarter, Indiegogo, and RocketHub, et.al., and friends and family private equity investors, start-up firms can strategically source their venture capital funds from many globally disperse organizations and individuals. As the firm in this case learned, the benefit of alternative investing sources comes with a critical hidden risk for corporate governance. After a financial restructuring, a typical Silicon Valley software start-up found itself with close to 300 external individual shareholders, some of whom had not been documented as accredited investors. The regulatory agency could decide that the prior actions of the founders and the decisions of the board had been prejudicial to the interests of the minority investors. The management of this small private company faced an atypical investor relations dilemma, before its initial public offering (IPO).
Prior to the introduction of AI-based forecast models in the procurement department of an industrial retail company, we assessed the digital skills of the procurement employees and surveyed their attitudes toward a new digital technology. The aim of the survey was to ascertain important contextual factors which are likely to influence the acceptance and the successful use of the new forecast tool. What we find is that the digital skills of the employees show an intermediate level and that their attitudes toward key aspects of new digital technologies are largely positive. Thus, the conditions for high acceptance and the successful use of the models are good, as evidenced by the high intention of the procurement staff to use the models. In line with previous research, we find that the perceived usefulness of a new technology and the perceived ease of use are significant drivers of the willingness to use the new forecast tool.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
In buchstäblich letzter Minute haben sich die englische Regierung und die Europäische Union auf ein umfangreiches Abkommen geeinigt, um einen ungeregelten Brexit zu verhindern. Nach dem jahrelangen zähen Verhandlungsmarathon fällt der Jubel verhalten aus, dennoch herrscht auf beiden Seiten des Ärmelkanals Erleichterung, weil ein Modus Vivendi gefunden wurde, auf dem sich die künftigen Beziehungen aufbauen und fortführen lassen. Ob sich die englischen Blütenträume, die an den Brexit geknüpft wurden, erfüllen werden, wird die Zukunft erweisen.
Die Strategie und Taktik der englischen Regierungen zum Brexit und bei den Austrittsverhandlungen spiegeln sich in den Erfahrungen wider, die Friedrich List vor genau 175 Jahren bei seinen Bemühungen um eine deutsch-englische Allianz machen musste. Wegen der von England schon damals strikt befolgten Insular und Handelssuprematie musste er sich eingestehen, dass England diese Position hartnäckig verteidigt und deshalb frustriert und ernüchtert seine Pläne aufgeben. Deshalb setzte er seine Hoffnung auf eine "Kontinentalallianz" der europäischen Nationen, wie sie nun nach dem Austritt Großbritanniens aus der Europäischen Union entstanden ist. Vielleicht werden wir uns nun an den Begriff "Kontinentalallianz" gewöhnen müssen und dabei an die Weitsicht von Friedrich List erinnert.
Andererseits gilt auch für die englische Politik das Motto von Lists zweiter Pariser Preisschrift: "Le monde marche - Die Welt bewegt sich", allerdings mit völlig anderen Vorzeichen als vor 175 Jahren: Die Welthandelsachse hat sich von der westlichen auf die östliche Halbkugel verlagert; das britische Weltreich ist Geschichte, die Fließgeschwindigkeit des globalen Wandels hat sich dramatisch beschleunigt und trotz der Lingua Franca erscheint England, vor allem aus asiatischer Sicht, nur noch als kleiner Fleck auf der Weltkarte. Falls die schottische Regierung ihre Absicht durchsetzen und die Unabhängigkeit vom Vereinigten Königreich erreichen sollte, würde sich der Brexit als verhängnisvoller Bumerang erweisen.
Digitalisierung und Mediatisierung prägen die Gesellschaft und auch die Erwachsenenbildung/Weiterbildung. Der Beitrag geht der Frage nach, wie Digitalisierung in Angeboten der Erwachsenenbildung/Weiterbildung gelingt. Damit wird ein Fokus auf den Einsatz digitaler Medien gelegt. Dazu werden die Angebotsentwicklung für Adressatinnen und Adressaten sowie Teilnehmende, medienbezogene Inhalte, Lehr- und Lernarrangements mit digitalen Medien, der Einsatz digitaler Medien und die Zugänglichkeit von Lehr- und Lernmaterialien als relevante Merkmale identifiziert. Insgesamt zeigen die analysierten Interviewdaten, dass der Einsatz digitaler Medien in Angeboten eine Erweiterung der didaktischen Aufgaben darstellt, da Angebote mit digitalen Medien zielgenau auf die Bedarfe und Möglichkeiten von Adressatinnen und Adressaten sowie Teilnehmenden abgestimmt werden müssen.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
Unter den widrigsten wirtschaftlichen und politischen Verhältnissen und Bedingungen wurde die Friedrich-List-Gesellschaft (FLG) 1925 gegründet und bis 1934 fortgeführt. Sie verfolgte vor allem den Zweck, die weit verstreuten, schwer zugänglichen und vielfach unbekannten Schriften, Reden und Briefe von Friedrich List (1789-1846) zusammenzutragen und in Form einer Gesamtausgabe zu publizieren.
Weder diese 10- bzw. 12-bändige Gesamtausgabe, noch die Namen ihrer Herausgeber haben in der Wirtschaftswissenschaft die gebührende Wertschätzung und Aufmerksamkeit erfahren. Die längst überfällige Dankesschuld wird in dem vorliegenden Beitrag nach nahezu 100 Jahren abgetragen. Ohne den engagierten und mutigen Einsatz der Herausgeber, insbesondere von Edgar Salin, wäre die List-Forschung undenkbar und die deutsche Wirtschaftswissenschaft um ein ruhmreiches Kapitel ärmer.
Seit 5 Jahrzehnten steht die Erforschung von Leben, Werk und Wirkungsgeschichte von Friedrich List (1789–1846) im Zentrum der wissenschaftlichen Arbeit von Eugen Wendler. Im Laufe der Zeit sind ca. 30 Monographien und eine größere Anzahl von wissenschaftlichen Aufsätzen und journalistischen Artikeln entstanden. Dabei baute Eugen Wendler auf der unschätzbaren Vorarbeit der Herausgeber der Gesamtausgabe von Lists Werken von 1925 bis 1935 auf.
Der vorliegende Aufsatz vermittelt einen Überblick über die Buchpublikationen von Eugen Wendler zur List-Forschung. Mit seinem eindrucksvollen Oeuvre bekennt er sich zum letzten lebenden Fossil in der Nachfolge der FLG und erweist damit den Herausgebern die gebührende und längst überfällige Wertschätzung und Achtung.
Digitalization increases the pressure for companies to innovate. While current research on digital transformation mostly focuses on technological and management aspects, less attention has been paid to organizational culture and its influence on digital innovations. The purpose of this paper is to identify the characteristics of organizational culture that foster digital innovations. Based on a systematic literature review on three scholarly databases, we initially found 778 articles that were then narrowed down to a total number of 23 relevant articles through a methodical approach. After analyzing these articles, we determine nine characteristics of organizational culture that foster digital innovations: corporate entrepreneurship, digital awareness and necessity of innovations, digital skills and resources, ecosystem orientation, employee participation, agility and organizational structures, error culture and risk-taking, internal knowledge sharing and collaboration, customer and market orientation as well as open-mindedness and willingness to learn.
The early detection of head and neck cancer is a prolonged challenging task. It requires a precise and accurate identification of tissue alterations as well as a distinct discrimination of cancerous from healthy tissue areas. A novel approach for this purpose uses microspectroscopic techniques with special focus on hyperspectral imaging (HSI) methods. Our proof-of-principle study presents the implementation and application of darkfield elastic light scattering spectroscopy (DF ELSS) as a non-destructive, high-resolution, and fast imaging modality to distinguish lingual healthy from altered tissue regions in a mouse model. The main aspect of our study deals with the comparison of two varying HSI detection principles, which are a point-by-point and line scanning imaging, and whether one might be more appropriate in differentiating several tissue types. Statistical models are formed by deploying a principal component analysis (PCA) with the Bayesian discriminant analysis (DA) on the elastic light scattering (ELS) spectra. Overall accuracy, sensitivity, and precision values of 98% are achieved for both models whereas the overall specificity results in 99%. An additional classification of model-unknown ELS spectra is performed. The predictions are verified with histopathological evaluations of identical HE-stained tissue areas to prove the model’s capability of tissue distinction. In the context of our proof-of-principle study, we assess the Pushbroom PCA-DA model to be more suitable for tissue type differentiations and thus tissue classification. In addition to the HE-examination in head and neck cancer diagnosis, the usage of HSI-based statistical models might be conceivable in a daily clinical routine.
Context:
Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.). The particularities of each study make the aggregation of results untenable.
Objectives:
The goal of this paper is to: increase the accuracy and generalizability of the results achieved in isolated experiments on TDD, provide joint conclusions on the performance of TDD across different industrial and academic settings, and assess the extent to which the characteristics of the experiments affect the quality-related performance of TDD.
Method:
We conduct a family of 12 experiments on TDD in academia and industry. We aggregate their results by means of meta-analysis. We perform exploratory analyses to identify variables impacting the quality-related performance of TDD.
Results:
TDD novices achieve a slightly higher code quality with iterative test-last development (i.e., ITL, the reverse approach of TDD) than with TDD. The task being developed largely determines quality. The programming environment, the order in which TDD and ITL are applied, or the learning effects from one development approach to another do not appear to affect quality. The quality-related performance of professionals using TDD drops more than for students. We hypothesize that this may be due to their being more resistant to change and potentially less motivated than students.
Conclusion:
Previous studies seem to provide conflicting results on TDD performance (i.e., positive vs. negative, respectively). We hypothesize that these conflicting results may be due to different study durations, experiment participants being unfamiliar with the TDD process, or case studies comparing the performance achieved by TDD vs. the control approach (e.g., the waterfall model), each applied to develop a different system. Further experiments with TDD experts are needed to validate these hypotheses.
In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.
Context: Agile practices as well as UX methods are nowadays well-known and often adopted to develop complex software and products more efficiently and effectively. However, in the so called VUCA environment, which many companies are confronted with, the sole use of UX research is not sufficient to find the best solutions for customers. The implementation of Design Thinking can support this process. But many companies and their product owners don’t know how much resources they should spend for conducting Design Thinking.
Objective: This paper aims at suggesting a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent for Design Thinking activities.
Method: A case study was conducted for the development of the DEW index. Design Thinking was introduced into the regular development cycle of an industry Scrum team. With the support of UX and Design Thinking experts, a formula was developed to determine the appropriate effort for Design Thinking.
Results: The developed “Discovery Effort Worthiness Index” provides an easy-to-use tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. A company can map the corresponding Design Thinking methods to the results of the DEW Index calculation, and product owners can select the appropriate measures from this mapping. Therefore, they can optimize the effort spent for discovery and validation.
Context: Many companies are facing an increasingly dynamic and uncertain market environment, making traditional product roadmapping practices no longer sufficiently applicable. As a result, many companies need to adapt their product roadmapping practices for continuing to operate successfully in today’s dynamic market environment. However, transforming product roadmapping practices is a difficult process for organizations. Existing literature offers little help on how to accomplish such a process.
Objective: The objective of this paper is to present a product roadmap transformation approach for organizations to help them identify appropriate improvement actions for their roadmapping practices using an analysis of their current practices.
Method: Based on an existing assessment procedure for evaluating product roadmapping practices, the first version of a product roadmap transformation approach was developed in workshops with company experts. The approach was then given to eleven practitioners and their perceptions of the approach were gathered through interviews.
Results: The result of the study is a transformation approach consisting of a process describing what steps are necessary to adapt the currently applied product roadmapping practice to a dynamic and uncertain market environment. It also includes recommendations on how to select areas for improvement and two empirically based mapping tables. The interviews with the practitioners revealed that the product roadmap transformation approach was perceived as comprehensible, useful, and applicable. Nevertheless, we identified potential for improvements, such as a clearer presentation of some processes and the need for more improvement options in the mapping tables. In addition, minor usability issues were identified.
Since the beginning of the energy sector liberalization, the design of energy markets has become a prominent field of research. Markets nowadays facilitate efficient resource allocation in many fields of energy system operation, such as plant dispatch, control reserve provisioning, delimitation of related carbon emissions, grid congestion management, and, more recently, smart grid concepts and local energy trading. Therefore, good market designs play an important role in enabling the energy transition toward a more sustainable energy supply for all. In this chapter, we retrace how market engineering shaped the development of energy markets and how the research focus shifted from national wholesale markets to more decentralized and location-sensitive concepts.
In a networked world, companies depend on fast and smart decisions, especially when it comes to reacting to external change. With the wealth of data available today, smart decisions can increasingly be based on data analysis and be supported by IT systems that leverage AI. A global pandemic brings external change to an unprecedented level of unpredictability and severity of impact. Resilience therefore becomes an essential factor in most decisions when aiming at making and keeping them smart. In this chapter, we study the characteristics of resilient systems and test them with four use cases in a wide-ranging set of application areas. In all use cases, we highlight how AI can be used for data analysis to make smart decisions and contribute to the resilience of systems.
Several studies analyzed existing Web APIs against the constraints of REST to estimate the degree of REST compliance among state-of-the-art APIs. These studies revealed that only a small number of Web APIs are truly RESTful. Moreover, identified mismatches between theoretical REST concepts and practical implementations lead us to believe that practitioners perceive many rules and best practices aligned with these REST concepts differently in terms of their importance and impact on software quality. We therefore conducted a Delphi study in which we confronted eight Web API experts from industry with a catalog of 82 REST API design rules. For each rule, we let them rate its importance and software quality impact. As consensus, our experts rated 28 rules with high, 17 with medium, and 37 with low importance. Moreover, they perceived usability, maintainability, and compatibility as the most impacted quality attributes. The detailed analysis revealed that the experts saw rules for reaching Richardson maturity level 2 as critical, while reaching level 3 was less important. As the acquired consensus data may serve as valuable input for designing a tool-supported approach for the automatic quality evaluation of RESTful APIs, we briefly discuss requirements for such an approach and comment on the applicability of the most important rules.
The Internet of Things (IoT) is coined by many different standards, protocols, and data formats that are often not compatible to each other. Thus, the integration of different heterogeneous (IoT) components into a uniform IoT setup can be a time-consuming manual task. This lacking interoperability between IoT components has been addressed with different approaches in the past. However, only very few of these approaches rely on Machine Learning techniques. In this work, we present a new way towards IoT interoperability based on Deep Reinforcement Learning (DRL). In detail, we demonstrate that DRL algorithms, which use network architectures inspired by Natural Language Processing (NLP), can be applied to learn to control an environment by merely taking raw JSON or XML structures, which reflect the current state of the environment, as input. Applied to IoT setups, where the current state of a component is often reflected by features embedded into JSON or XML structures and exchanged via messages, our NLP DRL approach eliminates the need for feature engineering and manually written code for pre-processing of data, feature extraction, and decision making.
The current advancement of Artificial Intelligence (AI) combined with other digitalization efforts significantly impacts service ecosystems. Artificial intelligence has a substantial impact on new opportunities for the co-creation of value and the development of intelligent service ecosystems. Motivated by experiences and observations from digitalization projects, this paper presents new methodological perspectives and experiences from academia and practice on architecting intelligent service ecosystems and explores the impact of artificial intelligence through real cases supporting an ongoing validation. Digital enterprise architecture models serve as an integral representation of business, information, and technological perspectives of intelligent service-based enterprise systems to support management and development. This paper focuses on architectural models for intelligent service ecosystems, showing the fundamental business mechanism of AI-based value co-creation, the corresponding digital architecture, and management models. The focus of this paper presents the key architectural model perspectives for the development of intelligent service ecosystems.
The digitization of factories will be a significant issue for the 2020s. New scenarios are emerging to increase the efficiency of production lines inside the factory, based on a new generation of robots’ collaborative functions. Manufacturers are moving towards data-driven ecosystems by leveraging product lifecycle data from connected goods. Energy-efficient communication schemes, as well as scalable data analytics, will support these various data collection scenarios. With augmented reality, new remote services are emerging that facilitate the efficient sharing of knowledge in the factory. Future communication solutions should generally ensure connectivity between the various production sites spread worldwide and new players in the value chain (e.g., suppliers, logistics) transparent, real-time, and secure. Industry 4.0 brings more intelligence and flexibility to production. Resulting in more lightweight equipment and, thus, offering better ergonomics. 5G will guarantee real-time transmissions with latencies of less than 1 ms. This will provide manufacturers with new possibilities to collect data and trigger actions automatically.
Platforms and their surrounding ecosystems are becoming increasingly important components of many companies' strategies. Artificial Intelligence, in particular, has created new opportunities to create and develop ecosystems around the platform. However, there is not yet a methodology to systematically develop these new opportunities for enterprise development strategy. Therefore, this paper aims to lay a foundation for the conceptualization of Artificial Intelligence-based service ecosystems exploiting a Service-Dominant Logic. The basis for conceptualization is the study of value creation and particularly effective network effects. This research investigates the fundamental idea of extending specific digital concepts considering the influence of Artificial Intelligence on the design of intelligent services, along with their architecture of digital platforms and ecosystems, to enable a smooth evolutionary path and adaptability for human-centric collaborative systems and services. The paper explores an extended digital enterprise conceptual model through a combined, iterative, and permanent task of co-creating value between humans and intelligent systems as part of a new idea of cognitively adapted intelligent services.
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.
Context
Microservices as a lightweight and decentralized architectural style with fine-grained services promise several beneficial characteristics for sustainable long-term software evolution. Success stories from early adopters like Netflix, Amazon, or Spotify have demonstrated that it is possible to achieve a high degree of flexibility and evolvability with these systems. However, the described advantageous characteristics offer no concrete guidance and little is known about evolvability assurance processes for microservices in industry as well as challenges in this area. Insights into the current state of practice are a very important prerequisite for relevant research in this field.
Objective
We therefore wanted to explore how practitioners structure the evolvability assurance processes for microservices, what tools, metrics, and patterns they use, and what challenges they perceive for the evolvability of their systems.
Method
We first conducted 17 semi-structured interviews and discussed 14 different microservice-based systems and their assurance processes with software professionals from 10 companies. Afterwards, we performed a systematic grey literature review (GLR) and used the created interview coding system to analyze 295 practitioner online resources.
Results
The combined analysis revealed the importance of finding a sensible balance between decentralization and standardization. Guidelines like architectural principles were seen as valuable to ensure a base consistency for evolvability and specialized test automation was a prevalent theme. Source code quality was the primary target for the usage of tools and metrics for our interview participants, while testing tools and productivity metrics were the focus of our GLR resources. In both studies, practitioners did not mention architectural or service-oriented tools and metrics, even though the most crucial challenges like Service Cutting or Microservices Integration were of an architectural nature.
Conclusions
Practitioners relied on guidelines, standardization, or patterns like Event-Driven Messaging to partially address some reported evolvability challenges. However, specialized techniques, tools, and metrics are needed to support industry with the continuous evaluation of service granularity and dependencies. Future microservices research in the areas of maintenance, evolution, and technical debt should take our findings and the reported industry sentiments into account.
Programmable nano-bio interfaces driven by tuneable vertically configured nanostructures have recently emerged as a powerful tool for cellular manipulations and interrogations. Such interfaces have strong potential for ground-breaking advances, particularly in cellular nanobiotechnology and mechanobiology. However, the opaque nature of many nanostructured surfaces makes non-destructive, live-cell characterization of cellular behavior on vertically aligned nanostructures challenging to observe. Here, a new nanofabrication route is proposed that enables harvesting of vertically aligned silicon (Si) nanowires and their subsequent transfer onto an optically transparent substrate, with high efficiency and without artefacts. We demonstrate the potential of this route for efficient live-cell phase contrast imaging and subsequent characterization of cells growing on vertically aligned Si nanowires. This approach provides the first opportunity to understand dynamic cellular responses to a cell-nanowire interface, and thus has the potential to inform the design of future nanoscale cellular manipulation technologies.
Organisationale Identität in digitalisierten Arbeitswelten: Grundlagen für gelingende Kooperation
(2021)
Organisationen bilden Identitäten aus und beantworten dabei die Fragen „Wer sind wir? Und wer sind wir nicht?“. Vorstellungen zur organisationalen Identität gehen zunächst von traditionellen Organisationen aus. Durch die Digitalisierung können bisher integrierte Aufgaben stärker modularisiert werden, sodass die Koordination der organisatorischen Gesamtaufgabe stärker sach- und weniger personenorientiert erfolgt. Zudem lassen sich organisationale Aufgaben zunehmend projektorientiert und virtuell abbilden, sodass externe Aufgabenträger leichter integriert werden können. Unsere Vorstellungen zu Organisationsgrenzen und -mitgliedschaften verändern sich dadurch. Dies wirft die Frage auf, inwiefern sich in solchen sach- und projektorientierten, grenzaufgelösten Organisationen eine gemeinsame organisationale Identität ausbildet. Im Beitrag wird argumentiert, dass sich die Wege der Identitätsentwicklung verändern, die Funktionen der organisationalen Identität für gelingende Kooperation aber erhalten bleiben.
Die digitale Arbeitswelt in ihrer Mehrdimensionalität verstehen: Digitalisierungsatlas und -index
(2021)
Die digitale Transformation der Arbeitswelt ist deshalb so herausfordernd, da die Arbeitswelt für sich bereits ein komplexes mehrdimensionales System ist, das sich kaum überblicken lässt. Für Unternehmen ist es deshalb wichtig, die Mehrdimensionalität und Komplexität der digitalen Arbeitswelt zu verstehen, hierfür ein gemeinsames Sprachspiel zu entwickeln und auf dieser Basis eine gemeinsame Einschätzung des Status quo der eigenen Arbeitswelt zu beschreiben. Mithilfe von zwei Instrumenten, dem Digitalisierungsatlas und dem Digitalisierungsindex, kann dies gelingen. In diesem Beitrag werden diese Instrumente im Detail dargestellt und es wird erklärt, wie sie Organisationen dabei helfen, zu beschreiben und zu verstehen, wo sie selbst in der digitalen Transformation der Arbeitswelt stehen.
Wenn Unternehmen den Schritt in die digitale Arbeitswelt gehen wollen, stehen sie vor der Herausforderung, konkrete Vorstellungen, Ziele und Maßnahmen zu entwickeln und umzusetzen. Häufig fehlt es Unternehmen an Wissen, ihre Transformation der Arbeitswelt strategisch zu gestalten und zu planen. Das Projekt DigiTraIn 4.0 setzt hier an und bietet mit dem Digitalisierungskompass ein Instrument, welches Unternehmen dabei unterstützt, eine Vision und spezifische Ziele für die Digitalisierung ihrer eigenen Arbeitswelt zu entwickeln. Im Anschluss daran unterstützt die Transformationsagenda Unternehmen dabei, konkrete Handlungsmaßnahmen zu entwickeln und deren Ablauf zu planen.
Arbeitswelten strategisch entwicklen: mit den DigiTraIn-Instrumenten zur digitalen Transformation
(2021)
Der Weg in die digitale Arbeitswelt ist für viele Unternehmen eine herausfordernde und komplexe Transformation. Um diesen Weg erfolgreich zu beschreiten, benötigen Unternehmen funktionierende Managementinstrumente. Im Projekt DigiTraIn 4.0 wurden vier Instrumente für eine gelingende Transformation in das digitale Arbeiten entwickelt und in der Unternehmenspraxis erprobt. Diese Instrumente werden im vorliegenden Beitrag, ausgehend von der Zielsetzung des Projekts, einführend dargestellt. Zudem wird ein Überblick über die weiteren Beiträge in diesem Buch gegeben, in denen die Instrumente im Detail erläutert werden und spezifische Aspekte des Wandels in die digitale Arbeitswelt im Fokus stehen.
Lehre und Lernen unterliegt einem stetigen Wandel, wobei Interaktion als ein zentrales Element der Motivationssteigerung im Lernkontext angesehen wird. Der vorliegende Beitrag zeigt verschiedene Ansätze zur Gestaltung von interaktivem und kollaborativem Lehren und Lernen in einem virtuellen Klassenzimmer auf und stellt ein Beispiel für die Umsetzung und den Einsatz eines solchen Systems vor. Die Mehrwerte und Erfolgsfaktoren, die sich beim Einsatz virtueller Klassenzimmer und deren Gestaltung in Form einer interaktiven blended-learning Umgebung ergeben, werden dargestellt und diskutiert. Mit dem System Accelerator wird eine CSILT (Computer Supported Interactive Learning and Teaching)-Umgebung vorgestellt, in der diese Faktoren zum Einsatz kommen.
Das Weltwirtschaftswachstum der vergangenen Jahrzehnte war durch die Dynamik der Digitalisierung und Globalisierung in den Lieferketten geprägt. Die Corona-Pandemie hat die Abhängigkeit und Verletzlichkeit der Lieferketten offengelegt. Trotz einer Vielzahl verbindlicher Standards haben Unternehmen die Digitalisierung und Arbeitsteilung auch für regulatorische Arbitrage genutzt. Einerseits erhöht das die Effizienz der Wirtschaft - was mithin ökologische Ressourcen schont - andererseits werden damit internationale Standards konterkariert. Globalisierung und Digitalisierung sind Segen und Fluch zugleich.
Das Projekt DigiTraIn 4.0 hat ein Beratungskonzept entwickelt und erprobt, das Unternehmen bei der erfolgreichen Digitalisierung ihrer Arbeitswelt unterstützt. Das Beratungskonzept basiert auf vier anwendungsorientierten Instrumenten: Der Digitalisierungsatlas bildet die Digitalisierung der Arbeitswelt in all ihren Dimensionen ab und ermöglicht es, die Notwendigkeit sowie Chancen und Risiken der Veränderungen zu verstehen. Hierauf aufbauend können Unternehmen mit dem Digitalisierungsindex ihren aktuellen Ist-Digitalisierungsgrad der Arbeitswelt individuell bestimmen. Der individuelle Digitalisierungsgrad dient als Ausgangspunkt für den Digitalisierungskompass, der es dem Unternehmen ermöglicht, die Soll-Vorstellung der digitalen Arbeitswelt zu illustrieren und eine unternehmensspezifische Transformationsagenda abzuleiten. Der Beratungsprozess und die Entwicklung der zentralen Instrumente werden in diesem Beitrag dargestellt.
Technologische, sozioökonomische und kulturelle Entwicklungen der letzten Jahrzehnte sowie zuletzt die Covid-19-Pandemie führten zu einer erhöhten Nachfrage nach flexiblen Arbeitsformen wie Homeoffice. In der Forschung wird danach gefragt, welche Faktoren die Umsetzung von flexiblen Arbeitsmodellen in Unternehmen beeinflussen und wie die Faktoren miteinander zusammenhängen. Bisher bietet die Forschung allerdings zu wenige Ansatzpunkte, um relevante Handlungsempfehlungen für eine erfolgreiche Umsetzung von Homeoffice für die Praxis abzuleiten. In dieser Fallstudie können auf organisationaler Ebene technologische, formelle und informelle Rahmenbedingungen, auf interaktionaler Ebene das Team und die Kommunikation sowie auf individueller Ebene Präferenzen, Kompetenzen und personenbezogene Rahmenbedingungen der Beschäftigten als relevante Einflussfaktoren identifiziert werden. Die Themenfelder sind eng miteinander verbunden, wobei sich vor allem stark vernetzte und einflussreiche Faktoren, wie formelle und technologische Rahmenbedingungen sowie Kommunikation, als Ansatzpunkte für die Gestaltung von Homeoffice eignen.
The article analyzes experimentally and theoretically the influence of microscope parameters on the pinhole-assisted Raman depth profiles in uniform and composite refractive media. The main objective is the reliable mapping of deep sample regions. The easiest to interpret results are found with low magnification, low aperture, and small pinholes. Here, the intensities and shapes of the Raman signals are independent of the location of the emitter relative to the sample surface. Theoretically, the results can be well described with a simple analytical equation containing the axial depth resolution of the microscope and the position of the emitter. The lower determinable object size is limited to 2–4 μm. If sub-micrometer resolution is desired, high magnification, mostly combined with high aperture, becomes necessary. The signal intensities and shapes depend now in refractive media on the position relative to the sample surface. This aspect is investigated on a number of uniform and stacked polymer layers, 2–160 μm thick, with the best available transparency. The experimental depth profiles are numerically fitted with excellent accuracy by inserting a Gaussian excitation beam of variable waist and fill fraction through the focusing lens area, and by treating the Raman emission with geometric optics as spontaneous isotropic process through the lens and the variable pinhole, respectively. The intersectional area of these two solid angles yields the leading factor in understanding confocal (pinhole-assisted) Raman depth profiles.
A hybrid deep registration of MR scans to interventional ultrasound for neurosurgical guidance
(2021)
Despite the recent advances in image-guided neurosurgery, reliable and accurate estimation of the brain shift still remains one of the key challenges. In this paper, we propose an automated multimodal deformable registration method using hybrid learning-based and classical approaches to improve neurosurgical procedures. Initially, the moving and fixed images are aligned using classical affine transformation (MINC toolkit), and then the result is provided to the convolutional neural network, which predicts the deformation field using backpropagation. Subsequently, the moving image is transformed using the resultant deformation into a moved image. Our model was evaluated on two publicly available datasets: the retrospective evaluation of cerebral tumors (RESECT) and brain images of tumors for evaluation (BITE). The mean target registration errors have been reduced from 5.35 ± 4.29 to 0.99 ± 0.22 mm in the RESECT and from 4.18 ± 1.91 to 1.68 ± 0.65 mm in the BITE. Experimental results showed that our method improved the state-of-the-art in terms of both accuracy and runtime speed (170 ms on average). Hence, the proposed method provides a fast runtime for 3D MRI to intra-operative US pair in a GPU-based implementation, which shows a promise for its applicability in assisting the neurosurgical procedures compensating for brain shift.
Purpose
Injury or inflammation of the middle ear often results in the persistent tympanic membrane (TM) perforations, leading to conductive hearing loss (HL). However, in some cases the magnitude of HL exceeds that attributable by the TM perforation alone. The aim of the study is to better understand the effects of location and size of TM perforations on the sound transmission properties of the middle ear.
Methods
The middle ear transfer functions (METF) of six human temporal bones (TB) were compared before and after perforating the TM at different locations (anterior or posterior lower quadrant) and to different degrees (1 mm, ¼ of the TM, ½ of the TM, and full ablation). The sound-induced velocity of the stapes footplate was measured using single-point laser-Doppler-vibrometry (LDV). The METF were correlated with a Finite Element (FE) model of the middle ear, in which similar alterations were simulated.
Results
The measured and calculated METF showed frequency and perforation size dependent losses at all perforation locations. Starting at low frequencies, the loss expanded to higher frequencies with increased perforation size. In direct comparison, posterior TM perforations affected the transmission properties to a larger degree than anterior perforations. The asymmetry of the TM causes the malleus-incus complex to rotate and results in larger deflections in the posterior TM quadrants than in the anterior TM quadrants. Simulations in the FE model with a sealed cavity show that small perforations lead to a decrease in TM rigidity and thus to an increase in oscillation amplitude of the TM mainly above 1 kHz.
Conclusion
Size and location of TM perforations have a characteristic influence on the METF. The correlation of the experimental LDV measurements with an FE model contributes to a better understanding of the pathologic mechanisms of middle-ear diseases. If small perforations with significant HL are observed in daily clinical practice, additional middle ear pathologies should be considered. Further investigations on the loss of TM pretension due to perforations may be informative.
Distributed ledger technologies such as the blockchain technology offer an innovative solution to increase visibility and security to reduce supply chain risks. This paper proposes a solution to increase the transparency and auditability of manufactured products in collaborative networks by adopting smart contract-based virtual identities. Compared with existing approaches, this extended smart contract-based solution offers manufacturing networks the possibility of involving privacy, content updating, and portability approaches to smart contracts. As a result, the solution is suitable for the dynamic administration of complex supply chains.
Dieser Beitrag entwickelt ein Managementmodell, das Unternehmen dabei unterstützt, relevante Aktionsfelder zur nachhaltigen Steuerung von Konsumenten entlang der eigenen Customer Journey zu identifizieren. Aufbauend auf dem SHIFT-Modell, als strukturelle Abbildung des nachhaltigen Käuferverhaltens, wird die Customer Journey entlang der owned, paid und earned Touchpoints aufgezogen. Mithilfe des faktisch analytischen Ansatzes, der die Integration neuer Erkenntnisse in die Forschungsstrategie unterstützt, werden Aktionsfelder identifiziert, die als grundlegende Logik Unternehmen dazu anleiten sollen, bei der Ausgestaltung der eigenen nachhaltigen Customer Journey dieses Strukturraster anzunehmen.
The main aim of presented in this manuscript research is to compare the results of objective and subjective measurement of sleep quality for older adults (65+) in the home environment. A total amount of 73 nights was evaluated in this study. Placing under the mattress device was used to obtain objective measurement data, and a common question on perceived sleep quality was asked to collect the subjective sleep quality level. The achieved results confirm the correlation between objective and subjective measurement of sleep quality with the average standard deviation equal to 2 of 10 possible quality points.
Public enterprises find themselves in increasingly competitive markets, a situation that makes having an entrepreneurial orientation (EO) an urgent need, given that EO is an indispensable driver of performance. Research describes politicians delaying the strategic change of public enterprises when serving as board members, but empirical evidence of the impact of board behavior on EO in public enterprises is lacking. We draw on stakeholder-agency theory (SAT) and resource dependence theory (RDT) and use structural equation modeling (SEM) to investigate survey data collected from 110 German energy suppliers that are majority government owned. Results indicate that board strategy control and board networking do not seem to predict EO on first sight. Closer analysis reveals a board networking–EO relationship depending on ownership structure. Remarkably, we find that it is not the usually suspected local municipal owner who hinders EO in our sample organizations but minority shareholders engaging in board networking activities. The results shed light on the intersection of governance and entrepreneurship with special reference to the fine-grained conceptualization of RDT.
Effektives Risiko-Management sollte neben quantifizierbaren, bekannten Risiken auch Ereignisse berücksichtigen, die entweder in ähnlicher Art bereits eingetreten oder grundsätzlich vorstellbar sind. Für eine Identifikation dieser "Grauen Schwäne" müssen institutionell-organisatorische Voraussetzungen geschaffen und analytisch-konzeptionelle Instrumente bereitgestellt werden.
The cloud evolved into an attractive execution environment for parallel applications, which make use of compute resources to speed up the computation of large problems in science and industry. Whereas Infrastructure as a Service (IaaS) offerings have been commonly employed, more recently, serverless computing emerged as a novel cloud computing paradigm with the goal of freeing developers from resource management issues. However, as of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other and benefit from on-demand and elastic compute resources as well as per-function billing. In this work, we discuss how to employ serverless computing platforms to operate parallel applications. We specifically focus on the class of parallel task farming applications and introduce a novel approach to free developers from both parallelism and resource management issues. Our approach includes a proactive elasticity controller that adapts the physical parallelism per application run according to user-defined goals. Specifically, we show how to consider a user-defined execution time limit after which the result of the computation needs to be present while minimizing the associated monetary costs. To evaluate our concepts, we present a prototypical elastic parallel system architecture for self-tuning serverless task farming and implement two applications based on our framework. Moreover, we report on performance measurements for both applications as well as the prediction accuracy of the proposed proactive elasticity control mechanism and discuss our key findings.
Unternehmen wenden insbesondere bei IT-nahen Projekten seit einigen Jahren auch im Controlling verstärkt ein agiles Vorgehen an. Erfahrungen zeigen jedoch, dass dies nicht bei allen Projekten in jedem Unternehmen funktioniert. Hybride Ansätze, die agile mit klassischen Projekt-Management-Methoden verbinden, bieten eine Lösung.
Annotations of character IDs in news images are critical as ground truth for news retrieval and recommendation system. Universality and accuracy optimization of deep neural network models constitutes the key technology to improve the precision and computing efficiency of automatic news character identification, which is attracting increased attention globally. This paper explores the optimized deep neural network model for automatic focus personage identification in multi-lingual news. First, the face model of the focus personage is trained by using the corresponding face images from German news as positive samples. Next, the scheme of Recurrent Convolutional Neural Network (RCNN) + Bi-directional Long-Short Term Memory (Bi-LSTM) + Conditional Random Field (CRF) is utilized to label the focus name, and the RCNN-RCNN encoder–decoder is applied to translate names of people into multiple languages. Third, face features are described by combining the advantages of Local Gabor Binary Pattern Histogram Sequence (LGBPHS) and RCNN, and iterative quantization (ITQ) is used to binarize codes. Finally, a name semantic network is built for different domains. Experiments are performed on a dataset which comprises approximately 100,000 news images. The experimental results demonstrate that the proposed method achieves a significant improvement over other algorithms.
Context: Nowadays, companies are challenged by increasing market dynamics, rapid changes and disruptive participants entering the market. To survive in such an environment, companies must be able to quickly discover product ideas that meet the needs of both customers and the company and deliver these products to customers. Dual-track agile is a new type of agile development that combines product discovery and delivery activities in parallel, iterative, and cyclical ways. At present, many companies have difficulties in finding and establishing suitable approaches for implementing dual-track agile in their business context.
Objective: In order to gain a better understanding of how product discovery and product delivery can interact with each other and how this interaction can be implemented in practice, this paper aims to identify suitable approaches to dual-track agile.
Method: We conducted a grey literature review (GLR) according to the guidelines to Garousi et al.
Results: Several approaches that support the integration of product discovery with product delivery were identified. This paper presents a selection of these approaches, i.e., the Discovery-Delivery Cycle model, Now-Next-Later Product Roadmaps, Lean Sprints, Product Kata, and Dual-Track Scrum. The approaches differ in their granularity but are similar in their underlying rationales. All approaches aim to ensure that only validated ideas turn into products and thus promise to lead to products that are better received by their users.
Die Annexion der Krim, die Kriegsführung in Syrien, das finanzielle Engagement in Zypern, das Tauziehen um die Ukraine und Weißrussland oder die Namensgebung Sputnik 5 für den Impfstoff gegen die Corona Epidemie sind eindeutige Belege für das aktuelle russische Machtstreben – und seine Expansionspolitik. Deshalb ist es nicht uninteressant zu fragen, welches Meinungsbild Friedrich List (1789–1846) von Russland hatte, zumal es heute noch so aktuell, wie vor 180 bis 190 Jahren erscheint und in seinen Schriften dargelegt ist. Dieses Meinungsbild wird in diesem Aufsatz erstmals untersucht und umfassend dargestellt.