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This book is about the challenges that emerge for organizations from an ever faster changing world. While useful at their time, several management tools, including classic strategic planning processes, will no longer suffice to address these challenges in a timely and comprehensive fashion. While individual management tools are still valid to solve specific problems, they need to be employed based on a clear understanding of what the greater challenge is and how they need to be combined and prioritized with other approaches. In order to do so, companies can apply the clarity of thinking from the military with regard to which leadership level is responsible for what and how these levels need to interact in order to produce a single aligned response to an outside opportunity or threat. Finally, the tool of business wargaming, while known for some time, proves to be an ideal approach to quickly and effectively bring all leadership levels together, align them around a common objective and lay the groundwork for effective implementation of targeted responses that will keep the organization competitive and in the game for the long run. The book offers a comprehensive introduction to business wargaming, including a historical account, a classification of different types of games and a number of specific real-world examples. This book is targeted at practicing managers dealing with the aforementioned challenges, as well as for students of business and strategy at every level.
Unprecedented formation of sterically stabilized phospholipid liposomes of cuboidal morphology
(2021)
Sterically stabilized phospholipid liposomes of unprecedented cuboid morphology are formed upon introduction in the bilayer membrane of original polymers, based on polyglycidol bearing a lipid-mimetic residue. Strong hydrogen bonding in the polyglycidol sublayers creates attractive forces, which, facilitated by fluidization of the membrane, bring about the flattening of the bilayers and the formation of cuboid vesicles.
Intermittent time series forecasting is a challenging task which still needs particular attention of researchers. The more unregularly events occur, the more difficult is it to predict them. With Croston’s approach in 1972 (1.Nr. 3:289–303), intermittence and demand of a time series were investigated the first time separately. He proposes an exponential smoothing in his attempt to generate a forecast which corresponds to the demand per period in average. Although this algorithm produces good results in the field of stock control, it does not capture the typical characteristics of intermittent time series within the final prediction. In this paper, we investigate a time series’ intermittence and demand individually, forecast the upcoming demand value and inter-demand interval length using recent machine learning algorithms, such as long-short-term-memories and light-gradient-boosting machines, and reassemble both information to generate a prediction which preserves the characteristics of an intermittent time series. We compare the results against Croston’s approach, as well as recent forecast procedures where no split is performed.
Artificial intelligence (AI) technologies, such as machine learning or deep learning, have been predicted to highly impact future organizations and radically change the way how projects are managed. The Project Management Institute (PMI), the network of around 1.1 million certified project managers, ranked AI as one of the top three disruptors of their profession. In an own study on the effect of AI, 37% of the project management processes can be executed by machine learning and other AI technologies. In addition, Gartner recently postulated that 80% of the work of today's project managers may be eliminated by AI in 2030.
This editorial aims to outline today's project and portfolio management in context of pharmaceutical research and development (R&D), followed by an AI-vision and a more tangible mission, and illustrate what the consequences of an AI-enabled project and portfolio management could be for pharmaceutical R&D.
Study programs in higher education have to reflect important societal and industrial challenges to prepare the next generations of professionals for future tasks. The focus of this paper is the challenge of digitalization and digital transformation. The paper proposes the IS education profile of a Digital Business Architect (DBA). The study program emphasizes design thinking, model centricity, and capability thinking as a response to domain requirements from digital transformation and educational system and structure requirements. Experiences in implementing the DBA include the need for integrating deductive and inductive teaching, a strong basis in real-world cases, and collaborative learning approaches to develop adequate competences in business model management, enterprise modeling, enterprise architecture management, and capability management.
We analyze economics PhDs’ collaborations in peer-reviewed journals from 1990 to 2014 and investigate such collaborations’ quality in relation to each co-author’s research quality, field and specialization. We find that a greater overlap between co-authors’ previous research fields is significantly related to a greater publication success of co-authors’ joint work and this is robust to alternative specifications. Co-authors that engage in a distant collaboration are significantly more likely to have a large research overlap, but this significance is lost when co-authors’ social networks are accounted for. High quality collaboration is more likely to emerge as a result of an interaction between specialists and generalists with overlapping fields of expertise. Regarding interactions across subfields of economics (interdisciplinarity), it is more likely conducted by co- authors who already have interdisciplinary portfolios, than by co-authors who are specialized or starred in different subfields.
The digital transformation is today’s dominant business transformation having a strong influence on how digital services and products are designed in a service-dominant way. A popular underlying theory of value creation and economic exchange that is known as the service-dominant (S-D) logic can be connected to many successful digital business models. However, S-D logic by itself is abstract. Companies cannot directly use it as an instrument for business model innovation and design in an easy way. To address this a comprehensive ideation method based on S-D logic is proposed, called service-dominant design (SDD). SDD is aimed at supporting firms in the transition to a service- and value-oriented perspective. The method provides a simplified way to structure the ideation process based on four model components. Each component consists of practical implications, auxiliary questions and visualization techniques that were derived from a literature review, a use case evaluation of digital mobility and a focus group discussion. SDD represents a first step of having a toolset that can support established companies in the process of service- and value-orientation as part of their digital transformation efforts.
Rotating machinery occupies a predominant place in many industrial applications. However, rotating machines are often encountered with severe vibration problems. The measurement of these machines’ vibrations signal is of particular importance since it plays a crucial role in predictive maintenance. When the vibrations are too high, they often cause fatigue failure. They announce an unexpected stop or break and, consequently, a significant loss of productivity or an attack on the personnel’s safety. Therefore, fault identification at early stages will significantly enhance the machine’s health and significantly reduce maintenance costs. Although considerable efforts have been made to master the field of machine diagnostics, the usual signal processing methods still present several drawbacks. This paper examines the rotating machinery condition monitoring in the time and frequency domains. It also provides a framework for the diagnosis process based on machine learning by analyzing the vibratory signals.
Employing diffuse reflection ultraviolet visible (UV–Vis) spectroscopy we developed an approach that is capable to quantitatively determine flux residues on a technical copper surface. The technical copper surface was soldered with a no-clean flux system of organic acids. By a post-solder cleaning step with different cleaning parameters, various levels of residues were produced. The surface was quantitatively and qualitatively characterized using X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES), Fourier transform infrared spectroscopy (FTIR) and diffuse reflection UV–Vis spectroscopy. With the use of a multivariate analysis (MVA) we examined the UV–Vis data to create a correlation to the carbon content on the surface. The UV–Vis data could be discriminated for all groups by their level of organic residues. Combined with XPS the data were evaluated by a partial least squares (PLS) regression to establish a model. Based on this predictive model, the carbon content was calculated with an absolute error of 2.7 at.%. Due to the high correlation of predictive model, the easy-to-use measurement and the evaluation by multivariate analysis the developed method seems suitable for an online monitoring system. With this system, flux residues can be detected in a manufacturing cleaning process of technical surfaces after soldering.
Context: Currently, most companies apply approaches for product roadmapping that are based on the assumption that the future is highly predicable. However, nowadays companies are facing the challenge of increasing market dynamics, rapidly evolving technologies, and shifting user expectations. Together with the adaption of lean and agile practices it makes it increasingly difficult to plan and predict upfront which products, services or features will satisfy the needs of the customers. Therefore, they are struggling with their ability to provide product roadmaps that fit into dynamic and uncertain market environments and that can be used together with lean and agile software development practices.
Objective: To gain a better understanding of modern product roadmapping processes, this paper aims to identify suitable processes for the creation and evolution of product roadmaps in dynamic and uncertain market environments.
Method: We performed a Grey Literature Review (GLR) according to the guidelines from Garousi et al.
Results: 32 approaches to product roadmapping were identified. Typical characteristics of these processes are the strong connection between the product roadmap and the product vision, an emphasis on stakeholder alignment, the definition of business and customer goals as part of the roadmapping process, a high degree of flexibility with respect to reaching these goals, and the inclusion of validation activities in the roadmapping process. An overall goal of nearly all approaches is to avoid waste by early reducing development and business risks. From the list of the 32 approaches found, four representative roadmapping processes are described in detail.
Given the increasing internationalisation of higher education, universities compete more and more not only for national but even more for international students. Selecting the best candidates from the pool of international applicants is a challenge. In our study, we analysed which criteria are best to predict the academic performance of students coming from different countries with different education systems, using different grade point average (GPA) standards. Using an administrative data set from an International Business programme at a German university of applied sciences, we explored the predictive power of adjusted high school GPA, IQ test result, interview score and first year grades in English, maths, and statistics.
A systematic study using a central composite design of experiments (DoE) was performed on the oxygen plasma surface modifications of two different polymers—Pellethane 2363-55DE, which is a polyurethane, and vinyltrimethoxysilane-grafted ethylene-propylene (EPR-g-VTMS), a cross-linked ethylene-propylene rubber. The impacts of four parameters—gas pressure, generator power, treatment duration, and process temperature—were assessed, with static contact angles and calculated surface free energies (SFEs) as the main responses in the DoE. The plasma effects on the surface roughness and chemistry were determined using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Through the sufficiently accurate DoE model evaluation, oxygen gas pressure was established as the most impactful factor, with the surface energy and polarity rising with falling oxygen pressure. Both polymers, though different in composition, exhibited similar modification trends in surface energy rise in the studied system. The SEM images showed a rougher surface topography after low pressure plasma treatments. XPS and subsequent multivariate data analysis of the spectra established that higher oxidized species were formed with plasma treatments at low oxygen pressures of 0.2 mbar.
In the IGF project No. 19617 N, nitrogen and phosphorous substituted alkoxysilanes were prepared and their ability to inhibit fire growth and spread for fabrics was explored. To this end, a series of flame retardants were synthesized using different strategies including click chemistry and nucleophilic substitution of commercial organophosphorus compounds with amino-based trialkoxysilanes and/or cyanuric chloride. The new halogen-free and aldehyde-free flame retardants were applied to different fabrics such as cotton (CO), polyethylene terephthalate (PET), polyamide (PA) and their blends using the well-known pad-dry-cure technique and sol-gel method. The flame-retarding efficiencies were evaluated by EN ISO 15025 test methods (protective clothing-protection against heat and flame method of test for limited flame spread). Good flame retardancy of the hybrid organic-inorganic materials was achieved with the addition of as small amount as 3-5 wt.% for cotton fabrics. Moreover, the water solubility and the washing resistance could be controlled through the functional groups attached to the phosphor atom or through the optimization of the curing temperature. Overall, the research project demonstrated that N-P-silanes are very good permanent flame retardants for textiles.
Nanocoatings based on sol–gel coatings are presented as suitable tool to modify materials based on polymers. The main focus is set onto textiles as the most common polymer materials. It presents which types of functionalization can be reached by modified sol–gel processes. Also a suitable categorization of functions is given and set into relation to common applications. A special focus is set on the functional properties, antimicrobial, UV protective, and flame retardant. The concept of bifunctional coatings is discussed and especially the combination of water-repellent and antistatic is presented.
On 5 May 2020, the Federal Constitutional Court of Germany announced in a momentous ruling that the Public Sector Purchase Programme (PSPP) of the European Central Bank (ECB) exceeds European Union (EU) competences. This decision initiated a lively debate in law and economics all over Europe. This article provides a unique interdisciplinary reading of the ruling in order to clarify the line of argument. Considering a cross-disciplinary view enlightens the understanding of the historic judgment.
This book highlights new trends and challenges in intelligent systems, which play an essential 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 business and intelligent systems based on human practices, as well as the study of interaction and co-adaptation of humans and systems. All papers were originally presented at the International KES Conference on Human Centred Intelligent Systems 2021 (KES HCIS 2021) held on June 14–16, 2021 in the KES Virtual Conference Centre.
Automotive technology is in a state of upheaval. IN the field of human machine interface (HMI), the increasing interaction between vehicles, users, and the Internet results in an increment of controls needed, which ultimately has a negative impact on usability and overall car weight. An interdisciplinary team of researchers has been developing for the past two years more intuitive and lighter in-car user interfaces through smart textiles at Reutlingen University. With the newly developed operating and feedback properties, a 1:1 demonstrator was realized and then integrated into a car driving simulator.
The strong demand to transform the textile and fashion industry towards sustainability requires continuous implementation of the Education for Sustainable Development (ESD) mission statement in education and industry. To achieve this goal, the European research project "Fashion DIET - Sustainable Fashion Curriculum at Textile Universities in Europe. Development, Implementation and Evaluation of a Teaching Module for Educators", co-funded by the Erasmus+ programme of the European Union (2020-1-DE01-KA203-005657), aims to create an ESD module for university lecturers and research-based teaching and learning materials delivered through an e-learning portal. First, an online questionnaire was rolled out to assess university faculty attitudes toward and needs for ESD content and methods. The feedback questionnaire enabled the selection of the most relevant data for the elaboration of an action and research-oriented professional development module for ESD in textile education, which will be accessible through an information & e-learning portal. The e-learning portal can be used as a web-based tool to apply and evaluate the project outcomes, e.g. the further education module and the teaching and learning materials for educators, such as manuals, broadcasts and the provision of interactive and physical materials. It thus ensures that the teaching materials can be used sustainably in the classroom. It also provides country-specific data for the fashion and textile industry and its market, taking into account the different perspectives of universities and schools. In any case, the portal represents (1) the web-based platform to support the dissemination of ESD as a guiding principle and (2) a central contact point for the target group to obtain relevant information on ESD. Fashion DIET explores the use of e-learning to improve teaching and learning on ESD, by training educators and empowering them as multipliers for a sustainable textile and fashion industry. At a higher level, the European project strengthens the quality and relevance of learning provision in education towards the latest developments in textile research and innovation in terms of a more sustainable fashion.
Logistics has undergone tremendous changes over the past few decades. Above all with the advent of the digital age, we have witnessed the significant impact of new technologies on supply chains in terms of business transformation, increased agility and performance. However, many businesses have chosen to harness the full potential of these technologies to create further value (Bughin et al, 2017). High investment costs, fears for cyber security, a lack of expertise in the workforce and insufficient awareness of the concrete benefits of these technologies are just some of the factors hampering the decision to adopt digital technologies.
The following chapter draws on the findings of both recent quantitative and qualitative research conducted by practitioners und academics.
By 2019, Germany-based Kärcher, “the world’s leading provider of cleaning technology,” had turned its professional cleaning devices into IoT products. The data generated by these IoT-connected cleaning devices formed a key ingredient in the company’s ongoing strategic shift in its B2B business: Kärcher was transforming from a seller of cleaning devices to a provider of consulting services in order to help professional cleaning companies improve their cleaning processes. Based on interviews with seven IT- and non-IT executives, the case illustrates how the company learned to generate value from IoT products. And it demonstrates how a family-owned company transformed its organization in order to be able to more effectively develop and provide IoT products, while adding roles, developing technology platforms, and changing organizational structures and ways of working.
Health monitoring in a home environment can have broader use since it may provide continuous control of health parameters with relatively minor intrusiveness into regular life. This work aims to verify if it is possible to replace the typical in some sleep medicine areas subjective questioning by an objective measurement using electronic devices. For this purpose, a study was conducted with ten subjects, in which objective and subjective measurement of relevant sleep parameters took place. The results of both measurement methods were evaluated and analyzed. The results showed that while for some measures, such as Total Time in Bed, there is a high agreement between objective and subjective measurements, for others, such as sleep quality, there are significant differences. For this reason, currently, a combination of both measurement methods may be beneficial and provide the most detailed results, while a partial replacement can already reduce the number of questions at the subjective measurement by measurement through electronic devices.
Uncontrolled movements of laparoscopic instruments can lead to inadvertent injury of adjacent structures. The risk becomes evident when the dissecting instrument is located outside the field of view of the laparoscopic camera. Technical solutions to ensure patient safety are appreciated. The present work evaluated the feasibility of an automated binary classification of laparoscopic image data using Convolutional Neural Networks (CNN) to determine whether the dissecting instrument is located within the laparoscopic image section. A unique record of images was generated from six laparoscopic cholecystectomies in a surgical training environment to configure and train The CNN. By using a temporary version of the neural network, the annotation of the training image files could be automated and accelerated. A combination of oversampling and selective data augmentation was used to enlarge the fully labelled image data set and prevent loss of accuracy due to imbalanced class volumes. Subsequently the same approach was applied to the comprehensive, fully annotated Cholec80 database. The described process led to the generation of extensive and balanced training image data sets. The performance of the CNN-based binary classifiers was evaluated on separate test records from both databases. On our recorded data, an accuracy of 0.88 with regard to the safety-relevant classification was achieved. The subsequent evaluation on the Cholec80 data set yielded an accuracy of 0.84. The presented results demonstrate the feasibility of a binary classification of laparoscopic image data for the detection of adverse events in a surgical training environment using a specifically configured CNN architecture.
Sustainability is a development that meets the needs of the present without compromising the ability of future generations to meet their own needs.
Business Model is a plan for the successful operation of a business, identifying sources of revenue, the intended customer base, products, and details of financing.
Circular economy is an approach of how a company creates, captures and delivers value, with a value creation logic designed to improve resource efficiency through contributing to extending the useful life of products and parts (e.g., through long-life design, repair and remanufacturing) and closing material loops.
This research-oriented book presents key contributions on architecting the digital transformation. It includes the following main sections covering 20 chapters: · Digital Transformation · Digital Business · Digital Architecture · Decision Support · Digital Applications Focusing on digital architectures for smart digital products and services, it is a valuable resource for researchers, doctoral students, postgraduates, graduates, undergraduates, academics and practitioners interested in digital transformation.
This chapter presents an introduction to the emerging trends for architecting the digital transformation having a strong focus on digital products, intelligent services, and related systems together with methods, models and architectures. The primary aim of this book is to highlight some of the most recent research results in the field. We are providing a focused set of brief descriptions of the chapters included in the book.
Enterprises are currently transforming their strategy, processes, and their information systems to extend their degree of digitalization. The potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems both drives and enables new business designs. Digitalization deeply disrupts existing businesses, technologies and economies and fosters the architecture of digital environments with many rather small and distributed structures. This has a strong impact for new value producing opportunities and architecting digital services and products guiding their design through exploiting a Service-Dominant Logic. The main result of the book chapter extends methods for integral digital strategies with value-oriented models for digital products and services which are defined in the framework of a multi-perspective digital enterprise architecture reference model.
Enterprises and societies currently face crucial challenges, while Industry 4.0 becomes important in the global manufacturing industry all the more. Industry 4.0 offers a range of opportunities for companies to increase the flexibility and efficiency of production processes. The development of new business models can be promoted with digital platforms and architectures for Industry 4.0. Therefore, products from the healthcare sector can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 is expected to promote and implement the digital platforms and robotics for healthcare and medical communities efficiently. In this paper, we propose that various digital platforms and robotics are designed and evaluated for digital healthcare as for manufacturing industry with Industry 4.0. We argue that the design of an open healthcare platform “Open Healthcare Platform 2030 - OHP2030” for medical product design and robotics can be developed with AIDAF. The vision of AIDAF applications to enable Industry 4.0 in the OHP2030 research initiative is explained and referenced, extended in the context of Society 5.0.
Due to digitalization, constant technological progress and ever shorter product life cycles, enterprises are currently facing major challenges. In order to succeed in the market, business models have to be adapted more often and more quickly to changing market conditions than they used to be. Fast adaptability, also called agility, is a decisive competitive factor in today’s world. Because of the ever-growing IT part of products and the fact that they are manufactured using IT, changing the business model has a major impact on the enterprise architecture (EA). However, developing EAs is a very complex task, because many stakeholders with conflicting interests are involved in the decision-making process. Therefore, a lot of collaboration is required. To support organizations in developing their EA, this article introduces a novel integrative method that systematically integrates stakeholder interests into decision-making activities. By using the method, collaboration between stakeholders involved is improved by identifying points of contact between them. Furthermore, standardized activities make decision-making more transparent and comparable without limiting creativity.
Many scientific reports have warned about the catastrophic consequences of unchecked climate change, with the latest international report calling for emissions of climate pollutants to reach net zero by around 2050 (IPCC, 2018). Limiting warming to 1.5°C could save more than 100 million people from water shortages, as many as 2 billion people from dangerous heatwaves, and the majority of species from climate change extinction risks (IPCC, 2018; Warren et al., 2018). The actions taken to achieve these climate outcomes would generate benefits of more than $20 trillion while easing global economic inequality (Burke et al., 2018). Scientists make it clear that it is physically possible to meet these goals using today’s technologies (Holz et al., 2018). Yet emissions of climate pollutants continue to grow, reaching a new record high in 2018 (Jackson et al., 2018). Clearly, scientific evidence has failed to spark needed climate action. The question now is: what can?
Autonomous navigation is one of the main areas of research in mobile robots and intelligent connected vehicles. In this context, we are interested in presenting a general view on robotics, the progress of research, and advanced methods related to this field to improve autonomous robots’ localization. We seek to evaluate algorithms and techniques that give robots the ability to move safely and autonomously in a complex and dynamic environment. Under these constraints, we focused our work in the paper on a specific problem: to evaluate a simple, fast and light SLAM algorithm that can minimize localization errors. We presented and validated a FastSLAM 2.0 system combining scan matching and loop closure detection. To allow the robot to perceive the environment and detect objects, we have studied one of the best deep learning technique using convolutional neural networks (CNN). We validate our testing using the YOLOv3 algorithm.