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Learning factories present a promising environment for education, training and research, especially in manufacturing related areas which are a main driver for wealth creation in any nation. While numerous learning factories have been built in industry and academia in the last decades, a comprehensive scientific overview of the topic is still missing. This paper intends to close this gap establishing the state of the art of learning factories. The motivations, historic background, and the didactic foundations of learning factories are outlined. Definitions of the term learning factory and the corresponding morphological model are provided. An overview of existing learning factory approaches in industry and academia is provided, showing the broad range of different applications and varying contents. The state of the art of learning factories curricula design and their use to enhance learning and research as well as potentials and limitations are presented. Conclusions and an outlook on further research priorities are offered.
Product-Service Systems (PSS) in the fashion industry : an analysis of intra-organizational factors
(2018)
The fashion industry is a vast industry that has grown tremendously over the last decades. This growth causes significant environmental impact since the production of clothes involves high input of energy, water, chemicals and generates great volumes of waste. Even though fashion firms have started to address this challenge by adopting environmental standards, it has turned out that the sole use of eco-friendly material and new manufacturing techniques is insufficient. Instead, sustainable business models are increasingly gaining attention to solve the environmental problems. Offers to rent, swap, repair or redesign clothes are among the most prominent and promising examples. For analytical purposes, these concepts can be assigned to the growing research stream of Product-Service Systems (PSS) that shift the focus from the pure sale of a product toward complementary or substitutional service offers. This decouples customer satisfaction from material consumption, prolongs the garments' lifetime and thus diminishes both material input and appertaining waste. Besides environmental sustainability, PSS imply potential economic benefits for organizations. Particularly in highly competitive industries like the fashion industry, PSS allow firms to differentiate, better compete with cost pressure and mitigate the risk of being imitated by rivels since service is more difficult to replicate. However, fashion PSS are still mainly operated in a niche market by small firms and have yet to be anchored in the mainstream fashion industry.
The fashion industry is well documented for causing significant environmental impact. Product-service systems (PSS) present a promising way to solve this challenge. PSS shift the focus toward complementary service offers, which decouples customer satisfaction from material consumption and entails dematerialization. However, PSS are not ecoefficient by nature but need to be accompanied by corporate environmental management (CEM) practices. The objective of this article is to examine the potential of PSS to contribute to the environmental sustainability of today's fashion industry by investigating if fashion firms with a positive attitude toward PSS implementation also pursue goals related to the ecological environment. For this purpose, analysis of variance (ANOVA) is conducted to analyze data of 102 fashion firms. Results reveal that the diffusion of PSS in today's fashion industry is low and few firms consider implementing PSS. Results, furthermore, demonstrate that PSS implementation is positively related to CEM. This indicates that existing structures of CEM favor PSS implementation and unlock the eco-efficient potential of implemented PSS in the fashion industry.
User innovators follow multiple diffusion and adoption pathways for their self-developed innovations. Users may choose to commercialize their self-developed products on the marketplace by becoming entrepreneurs. Few studies exist that focus on understanding personal and interpersonal factors that affect some user innovators’ entrepreneurial decision-making. Hence, this paper focuses on how user innovators make key decisions relating to opportunity recognition and evaluation and when opportunity evaluation leads to subsequent entrepreneurial action in the entrepreneurial process. We conducted an exploratory study using a multi-grounded theory methodology as the user entrepreneurship phenomenon embodies complex social processes. We collected data through the netnography approach that targeted 18 entrepreneurs with potentially relevant differences through crowdfunding platforms. We integrated self-determination, human capital, and social capital theory to address the phenomena under study. This study’s significant findings posit that users’ motives are dissatisfaction with existing goods, interest in innovation, altruism, social recognition, desire for independence, and economic benefits. Besides, use-related experience, product-related knowledge, product diffusion, and iterative feedback positively impact innovative users’ entrepreneurial decision-making.
Influence of the respirator on volatile organic compounds : an animal study in rats over 24 hours
(2015)
Long-term animal studies are needed to accomplish measurements of volatile organic compounds (VOCs) for medical diagnostics. In order to analyze the time course of VOCs, it is necessary to ventilate these animals. Therefore, a total of 10 male Sprague–Dawley rats were anaesthetized and ventilated with synthetic air via tracheotomy for 24 h. An ion mobility spectrometry coupled to multi-capillary columns (MCC–IMS) was used to analyze the expired air. To identify background contaminations produced by the respirator itself, six comparative measurements were conducted with ventilators only. Overall, a number of 37 peaks could be detected within the positive mode. According to the ratio peak intensity rat/ peak intensity ventilator blank, 22 peaks with a ratio >1.5 were defined as expired VOCs, 12 peaks with a ratio between 0.5 and 1.5 as unaffected VOCs, and three peaks with a ratio <0.5 as resorbed VOCs. The peak intensity of 12 expired VOCs changed significantly during the 24 h measurement. These results represent the basis for future intervention studies. Notably, online VOC analysis with MCC–IMS is possible over 24 h in ventilated rats and allows different experimental approaches.
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.
The properties of polyelectrolyte multilayers are ruled by the process parameters employed during self-assembly. This is the first study in which a design of experiment approach was used to validate and control the production of ultrathin polyelectrolyte multilayer coatings by identifying the ranges of critical process parameters (polyelectrolyte concentration, ionic strength and pH) within which coatings with reproducible properties (thickness, refractive index and hydrophilicity) are created. Mathematical models describing the combined impact of key process parameters on coatings properties were developed demonstrating that only ionic strength and pH affect the coatings thickness, but not polyelectrolyte concentration. While the electrolyte concentration had a linear effect, the pH contribution was described by a quadratic polynomial. A significant contribution of this study is the development of a new approach to estimate the thickness of polyelectrolyte multilayer nanofilms by quantitative rhodamine B staining, which might be useful in all cases when ellipsometry is not feasible due to the shape complexity or small size of the coated substrate. The novel approach proposed here overcomes the limitations of known methods as it offers a low spatial sampling size and the ability to analyse a wide area without restrictions on the chemical composition and shape of the substrate.
Herein the optimization of the physicochemical properties and surface biocompatibility of polyelectrolyte multilayers of the natural, biocompatible and biodegradable, linear polysaccharides hyaluronan and chitosan by Hofmeister anions was systematically investigated. We demonstrated that there is an interconnection between the bulk and surface properties of HA/Chi multilayers both varying in accordance with the arrangement of the anions in the Hofmeister series. Kosmotropic anions increased the hydration, thickness, micro- and macro-roughness, and hydrophilicity and improved the biocompatibility of the films by reduction (2 orders of magnitude) of the films stiffness and complete anti-thrombogenicity.
We report the temperature dependence of metal-enhanced fluorescence (MEF) of individual photosystem I (PSI) complexes from Thermosynechococcus elongatus (T. elongatus) coupled to gold nanoparticles (AuNPs). A strong temperature dependence of shape and intensity of the emission spectra is observed when PSI is coupled to AuNPs. For each temperature, the enhancement factor (EF) is calculated by comparing the intensity of individual AuNP-coupled PSI to the mean intensity of ‘uncoupled’ PSI. At cryogenic temperature (1.6 K) the average EF was 4.3-fold. Upon increasing the temperature to 250 K the EF increases to 84-fold. Single complexes show even higher EFs up to 441.0-fold. At increasing temperatures the different spectral pools of PSI from T. elongatus become distinguishable. These pools are affected differently by the plasmonic interactions and show different enhancements. The remarkable increase of the EFs is explained by a rate model including the temperature dependence of the fluorescence yield of PSI and the spectral overlap between absorption and emission spectra of AuNPs and PSI, respectively.
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.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
Machine learning (ML) techniques are rapidly evolving, both in academia and practice. However, enterprises show different maturity levels in successfully implementing ML techniques. Thus, we review the state of adoption of ML in enterprises. We find that ML technologies are being increasingly adopted in enterprises, but that small and medium-size enterprises (SME) are struggling with the introduction in comparison to larger enterprises. In order to identify enablers and success factors we conduct a qualitative empirical study with 18 companies in different industries. The results show that especially SME fail to apply ML technologies due to insufficient ML knowhow. However, partners and appropriate tools can compensate this lack of resources. We discuss approaches to bridge the gap for SME.
The number of publications in the field of breath analysis using different types of ion mobility spectrometers (IMS) has increased over the last few years. In this paper, the publications between 2010 and 2013 are reviewed with respect to different types of IMS such as differential mobility spectrometers, high-field asymmetric waveform ion mobility spectrometers and multi-capillary columns coupled to conventional IMS. The analytes detected by IMS and declared with significance to a specific medical question were considered further with respect to medical and analytical questions. In total, 42 different analytes were found to be detected using IMS on a high significance level and were compared to findings using other analytical methods with respect to the individual analyte.
Since its early beginnings in the form of correspondence schools, e-learning has generally sought to provide flexibility and high quality education. While these are indeed noble intentions, the reality of today's connected world demands that such programs focus on a different purpose. As the main purpose of e-learning shifts, so must be the design approaches.
Rethinking e-learning requires open-mindedness on the part of academies, designers, cyber educators, legislators, IT and administrators, but also the learners themselves. All who are involved in or impacted by e-learning programs must speak up and finally share their perspectives, but who will be listening? The key to rethinking e-learning lies in the ability of the stakeholders to listen to each other and make decisions which are in the best interest of the learner.
This chapter will propose a new purpose for e-learning and explore promising possibilities for learner-centered design. The future of e-learning can be shaped by the decisions made today, but before any decisions can be made, one must acknowledge e-learning's successes as well as its shortcomings. The purpose of this chapter is to encourage those who are impacted by e-learning to think about the future.
There is no denying that organizations, whether domestic or global, whether educational, governmental, or business, are undergoing rapid transformation. However, what is causing it? Prompted by the need to remain relevant and competitive, organizations constantly try to reinvent themselves. Those that do not, according to the laws of economics, will simply serve no purpose and will eventually cease to exist. Regardless of sector or industry, an organization's success pivots around its human talent. Hence, it is crucial to manage it and cultivate certain traits, knowledge, and skills. In today's global economy, organizations are more interconnected than ever before and thus the challenges they face require that employees possess not only expert knowledge, problem-solving, cross-cultural, and cross-functional teaming skills, but also good communications skills and agile thinking.
Many researchers have explored the phenomenon of intercultural communication since Edward T. Hall first brought it to light in the late 1950s. Although the literature is quite extensive, the ongoing sociopolitical struggles are evidence that even in the twenty-first century, society has limited intercultural as well as intracultural communication competence. This limited understanding continues to bring about discord in every facet of life, including work.
The modern workforce is expected to possess certain knowledge, skills, and attitudes that are inherently different from those expected from previous generations. Due to globalization, intercultural competence and highly effective communication skills are at the top of the list - a working knowledge of English as the lingua franca of today's business world can be considered as a first step.
Long-term stability of membranes in membrane distillation operation is a problem nowadays which prevents the industrial breakthrough of this separation process. Fouling or slow pore wetting are the basic reasons for this.
Membrane distillation membranes were made by NIPS process rendering the membrane asymmetrically to achieve low permeation resistance and pores which can be over coated with polyelectrolyte polymers thus leading to thermopervaporation membranes. Those membranes prohibit pore wetting and may strongly reduce resorption of organic substances on for membrane distillation typically used hydrophobic surfaces thus leading to longterm operation stability in dewatering including stable membrane cleaning.
Asymmetric PVDF membranes have been coated with cation exchange polyelectrolyte leading to a very thin, defect-free layer which has a high permeation rate for water due to the domain structure of phase-separated hydrophilic and hydrophobic three-dimensional structures.
This study analyses the impact of Basel III on the fair pricing of bank guarantee facilities.Guarantees are an important risk mitigation instrument between exporters and importers in international trade and regularly a prerequisite for cross border sales contracts to be closed. Basel III – which shall be introduced from 2013 onwards - is a new regulation stipulating higher capital requirements for banks compared to the predecessor Basel II. It will therefore have an impact on the pricing of guarantee facilities which banks provide to exporting companies, making it also a crucial regulation for the cost of exportation overall. The study compares those contents of Basel III and Basel II which are particularly relevant for guarantees in order to identify and crystallize pricing-relevant changes in the regulations and their respective impact potential. The Basel frameworks are analyzed part by part and reviewed in terms of relevance for guarantees. In case of ambiguity the analysis is verified by complementary expert interviews. References and examples are mainly focusing on the German banking system but the basic conclusions can be generalized for those countries adopting Basel III.1 As the result, a case study expresses the quantitative outcomes of different scenarios and the impact of the different price determining factors on the overall fair pricing of bank guarantee facilities.
Motivation
In order to enable context-aware behavior of surgical assistance systems, the acquisition of various information about the current intraoperative situation is crucial. To achieve this, the complex task of situation recognition can be delegated to a specialized system. Consequently, a standardized interface is required for the seamless transfer of the recognized contextual information to the assistance systems, enabling them to adapt accordingly.
Methods
Our group analyzed four medical interface standards to determine their suitability for exchanging intraoperative contextual information. The assessment was based on a harmonized data and service model derived from the requirements of expected context-aware use cases. The Digital Imaging and Communications in Medicine (DICOM) and IEEE 11073 for Service-oriented Device Connectivity (SDC) were identified as the most appropriate standards.
Results
We specified how DICOM Unified Procedure Steps (UPS), can be used to effectively communicate contextual information. We proposed the inclusion of attributes to formalize different granularity levels of the surgical workflow.
Conclusions
DICOM UPS SOP classes can be used for the exchange of intraoperative contextual information between a situation recognition system and surgical assistance systems. This can pave the way for vendor-independent context awareness in the OR, leading to targeted assistance of the surgical team and an improvement of the surgical workflow.
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.
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.
Due to the consequential impact of technological breakdowns, companies have to be prepared to deal with breakdowns or even better prevent them. In today's information technology, several methods and tools exist to downscale this concern. Therefore, this paper deals with the initial determination of a resilient enterprise architecture supporting predictive maintenance in the information technology domain and furthermore, concerns several mechanisms on how to reactively and proactively secure the state of resiliency on several abstraction levels. The objective of this paper is to give an overview on existing mechanisms for resiliency and to describe the foundation of an optimized approach, combining infrastructure and process mining techniques.
Gamification is one of the recognized methods of motivating people in various life processes, and it has spread to many spheres of life, including healthcare. This article proposes a system design for long-term care patients using the method mentioned. The proposed system aims to increase patient engagement in the treatment and rehabilitation process via gamification. Literature research on available and earlier proposed systems was conducted to develop a suited system design. The primary target group includes bedridden patients and a sedentary lifestyle (predominantly lying in bed). One of the main criteria for selecting a suitable option was its contactless realization for the mentioned target groups in long-term care cases. As a result, we developed the system design for hardware and software that could prevent bedsores and other health problems from occurring because of low activity. The proposed design can be tested in hospitals, nursing homes, and rehabilitation centers.
Lithographical hotspot (LH) detection using deep learning (DL) has received much attention in the recent years. It happens mainly due to the facts the DL approach leads to a better accuracy over the traditional, state-of-the-art programming approaches. The purpose of ths study is to compare existing data augmentation (DA) techniques for the integrated circuit (IC) mask data using DL methods. DA is a method which refers to the process of creating new samples similar to the training set, thereby helping to reduce the gap between classes as well as improving the performance of the DL system. Experimental results suggest that the DA methods increase overall DL models performance for the hotspot detection tasks.
The rapid development and growth of knowledge has resulted in a rich stream of literature on various topics. Information systems (IS) research is becoming increasingly extensive, complex, and heterogeneous. Therefore, a proper understanding and timely analysis of the existing body of knowledge are important to identify emerging topics and research gaps. Despite the advances of information technology in the context of big data, machine learning, and text mining, the implementation of systematic literature reviews (SLRs) is in most cases still a purely manual task. This might lead to serious shortcomings of SLRs in terms of quality and time. The outlined approach in this paper supports the process of SLRs with machine learning techniques. For this purpose, we develop a framework with embedded steps of text mining, cluster analysis, and network analysis to analyze and structure a large amount of research literature. Although the framework is presented using IS research as an example, it is not limited to the IS field but can also be applied to other research areas.
Purpose: This paper is to show what sustainable fashion is and how it has developed in recent years. Also the paper discusses which factors are important in order to be sustainable. Above all, it's about customers who show a lot interest in sustainable fashion. Child labor, working conditions, poor quality and poisonous substances are stricty rejected by these consumers. Amazingly, fashion companies that repeatedly hit the headlines with bad properties are very successful. It's about the sustainable oxymoron, the act and want of the consumer.
Findings: It is difficult to be sustainable. The reasons for that are the consumption, not much transparency in textile chains, fast fashion and much more. It's almost impossible for a product to achieve the 100 percent sustainability. On one hand the consumers want to have sustainable products, on the other hand they purchase for newness and cheap clothes. It has become clear that they buy in a conflict.
In order to decouple economic growth from global material consumption it is necessary to implement material efficiency strategies at the level of single enterprises and their supply chains, and to implement circular economy aspects. Manufacturing firms face multiple implementation challenges like cost limitations, competition, innovation and stakeholder pressure, and supplier and customer relationships, among others
. An extended evaluation of triggers and barriers to improve material efficiency in manufacturing companies, along the supply chain and concerning circular economy considerations is provided. This paper delivers an extended literature review, a critical discussion of the current situation and resulting challenges concerning material efficiency approaches in manufacturing supply chains. Finally, a conclusion and outlook on further research direction is given.
Mature economies which are driven mainly by small and medium sized enterprises (SMEs) are increasingly becoming dependent on material imports. Global material consumption is ever increasing, mainly driven by population increases. Decoupling of material consumption from economic growth is one of the greatest challenges of the 21st century. Within this paper available methods for the assessment of material efficiency on different economic scales are investigated and those detected that are particulary suitable for the use in SMEs. Recommendations for further improvements of the selected tools and an outlook concerning planned research activities in the field of material efficiency in enterprises, supply chains and circular economy aspects are given.
Public transport maps are typically designed in a way to support route finding tasks for passengers while they also provide an overview about stations, metro lines, and city-specific attractions. Most of those maps are designed as a static representation, maybe placed in a metro station or printed in a travel guide. In this paper we describe a dynamic, interactive public transport map visualization enhanced by additional views for the dynamic passenger data on different levels of temporal granularity. Moreover, we also allow extra statistical information in form of density plots, calendar-based visualizations, and line graphs. All this information is linked to the contextual metro map to give a viewer insights into the relations between time points and typical routes taken by the passengers. We illustrate the usefulness of our interactive visualization by applying it to the railway system of Hamburg in Germany while also taking into account the extra passenger data. As another indication for the usefulness of the interactively enhanced metro maps we conducted a user experiment with 20 participants.
In order to evaluate the performance of different stapes prosthesis types, a coupled finite element (FE) model of human ear was developed. First, the middle-ear FE model was developed and validated using the middle-ear transfer function measurements available in literature including pathological cases. Then, the inner-ear FE model was developed and validated using tonotopy, impedance, and level of cochlea amplification curves from literature. Both models are based on pre-existing research with some improvements and were combined into one coupled FE model. The stapes in the coupled FE ear model was replaced with a model of a stapes prosthesis to create a reconstructed ear model that can be used to estimate how different types of protheses perform relative to each other as well as to the natural ear. This will help in designing of new innovative types of stapes prostheses or any other type of middle-ear prostheses as well as to improve the ones that are already available on the market.
An apparatus and method for analyzing a flow of material having an inlet region, a measurement range and an outlet region, and having a first diverter and a second diverter, and a deflection area, wherein in a first state of operation, the two diverters form a continuous first material flow space from the inlet region via the first diverter through the measurement range, via the second diverter to the outlet region, and in a second state of operation, form a continuous second material flow space from the inlet region via the first diverter through the deflection area, via the second diverter to the outlet region.
Here, we report the continuous peroxide-initiated grafting of vinyltrimethoxysilane (VTMS) onto a standard polyolefin by means of reactive extrusion to produce a functionalized liquid ethylene propylene copolymer (EPM). The effects of the process parameters governing the grafting reaction and their synergistic interactions are identified, quantified and used in a mathematical model of the extrusion process. As process variables the VTMS and peroxide concentrations and the extruder temperature setting were systematically studied for their influence on the grafting and the relative grafting degree using a face-centered central composite design (FCD). The grafting degree was quantified by 1H NMR spectroscopy. Response surface methodology (RSM) was used to calculate the most efficient grafting process in terms of chemical usage and graft yield. With the defined processing window, it was possible to make precise predictions about the grafting degree with at the same time highest possible relative degree of grafting.
This introductory chapter starts with a brief discussion about the differences between the long-standing perspective of sports marketing and more modern sports marketing approach. The discussion leads to the ultimate question whether sports marketing can be seen as a new and independent marketing discipline rather than a normal form of marketing. In addition, a coherent definition of sports marketing will be presented which serves as the underlining definition of this edition volumen. Then the most important characteristics of sports of a marketing perspective will be explained using some real-life examples. The structure as well as the individual chapters of this book will be introduced in the following. This first chapter concludes with the introduction of the German Institute for Sports Marketing which has been founded by the editors of this book.
Marketing in sports
(2014)
In this chapter the principals of marketing will be explained an transferred to the contex of sports. Following a brief introduction the principles of marketing will be outlined and explained in further detail. Then the subject of sports marketing will be introduced from different perspectives using various definitions and approaches. Afterwards the focus is on the unique characteristics of sports marketing before a model of sports marketing will be presented. Then it will be shown how professional sporting organisations might market their products an themselves. The chapter concludes with a detailed case study using the example of FC St. Pauli which is one of only few real brands in German sports.
This chapter presents the diverse facets of sports marketing in Western Europe. It showcases the most important types of sports, most significant leagues, bestknown clubs, most popular athletes and the biggest sporting events in Western Europe while elaborating on the relevant aspects of sports marketing. We examine European sportsconsumers, characterise the sports marketing market in Western Europe an explain the current scientific/academic status of sports marketing. Moreover, we illustrate the motives for the internationalisation taking place in sports marketing. In conclusion, this chapter includes an international case study on the entry of the NFL into the European market.
Although sports is generally defined as motor activity, it has always been much more than that. Since management and sports follow the same objective of achieving highest performance, correlation between these two fields nowadays become increasingly interesting in terms of corporate strategy. This chapter aims to point out how organisations as well as individuals can benefit from the general and psychological values and strategies of sports, by first looking at the general framework of professional sports an futher applying approaches from various types of sports directly to certain business functions like general management, human resource management and marketing management. The chapter concludes with an international case study and brief outlook.
This concluding chapter summarises and discusses the different parts and findings of the anthology on hand. The main statements and conclusions of each chapter are presented. Following up, the editors try to look into the future of the sports business and sports management in general and the future of sports marketing in particular and draw a final conclusion.
As long as there have been professional sports, there have been relationships on different levels. For example, sponsorship (or patronage as it was called in the early days) was mostly based on personal relations between the local benefactors and their favourite sports club. Regarding media, clubs always maintained special relationships with selected journalists. The bond between fans and their clubs was always a close and mutually beneficial one. All these relationships existed from the start of the sports business. Therefore, relationship marketing is nothing new in the context of sports. Many sporting organisations always knew to value a deep and good relationship with their stakeholders and practised relationship marketing without being aware of it. Successful sports managers, however, take the old wisdom and turn it into a modern relationship marketing approach by structuring the various relationships in order to make them more effective and profitable for the own sporting organisation and the various stakeholders. This chapter ... illustrates the many facets of relationship marketing and the possibilities it offers in the context of the sports business.
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.
Urgent action is needed to keep the chance of limiting global warming to 1.5°C or even 2.0°C. Current outlooks by IPCC, and many other organisations forecast that this will be impossible at current pace of emission 'reductions' – Germany has already hit 1.5° warming this year. Across 2019, particularly during the UN New York Climate summit, numerous organisations declared their ambition to become net carbon neutral. Amongst these were investors and companies, including quite a number of German ones.
We apply a mixed methods approach, utilising data gathered from approx. 900 companies after Climate Week in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on decarbonisation plans announced and initiatives pledging climate action.
With this, we analyse how German companies in the manufacturing sectors react to rising societal pressure and emerging policies, particularly what measures they have taken or plan to implement to reduce the footprint of their company, their products and their supply chain. In this, we particularly analyse whether and in what way energy- and resource consumption, as well as carbon emissions are considered in the development and lifecycle of goods manufactured. This is of huge relevance as these goods determine the future footprint of buildings, vehicles and industry.
Regarding the supply chain, current articles indicate that small and medium-sized enterprises (SME) are particularly challenged by increasing demands from their large corporate clients and an alleged lack of preparedness to be able to take and afford prompt decarbonisation action themselves (Buchenau et. al. 2019). Notably the automotive industry recently announced new models that will be 100% carbon neutral all the way through (ibid). We thus analyse if and how factors such as company size, energy intensity and sector affiliation influence a company’s plan to fully decarbonize. Ownership structure and corporate culture, it appears, significantly impact on the degree of decarbonisation action underway.
IGBT modules with anti-parallel FWDs are widely used in inductive load switching power applications, such as motor drive applications. Nowadays there is a continuous effort to increase the efficiency of such systems by decreasing their switching losses. This paper addresses the problems arising in the turn-on process of an IGBT working in hard-switching conditions. A method is proposed which achieves – contrary to most other approaches – a high switching speed and, at the same time, a low peak reverse-recovery current. This is done by applying an improved gate current waveform that is briefly lowered during the turn-on process. The proposed method achieves low switching losses. Its effectiveness is demonstrated by experimental results with IGBT modules for 600V and 1200V.
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.
Power line communications (PLC) reuse the existing power-grid infrastructure for the transmission of data signals. As power line the communication technology does not require a dedicated network setup, it can be used to connect a multitude of sensors and Internet of Things (IoT) devices. Those IoT devices could be deployed in homes, streets, or industrial environments for sensing and to control related applications. The key challenge faced by future IoT-oriented narrowband PLC networks is to provide a high quality of service (QoS). In fact, the power line channel has been traditionally considered too hostile. Combined with the fact that spectrum is a scarce resource and interference from other users, this requirement calls for means to increase spectral efficiency radically and to improve link reliability. However, the research activities carried out in the last decade have shown that it is a suitable technology for a large number of applications. Motivated by the relevant impact of PLC on IoT, this paper proposed a cooperative spectrum allocation in IoT-oriented narrowband PLC networks using an iterative water-filling algorithm.
An autonomous vehicle is a robotic vehicle with decision and action capability capable of performing assigned tasks without or with minimal human intervention. Autonomous cars have been in development for many years. The Society of Automotive Engineers (SAE International) published in 2014 a classification in five levels of driving automation, with level 0 corresponding to completely manual driving, and level 5 to an ideal dream where the vehicle would be able to navigate entirely autonomously for all missions and in all environments. This work addressed the navigation of an autonomous vehicle in general. We focus on one of the most complex scenarios of the road network and crossing of road intersections. In this paper, the critical features of autonomous intelligent vehicles are reviewed. Furthermore, the associated problems are presented, and the most advanced solutions are derived. This article aims to allow a novice in this field to understand the different facets of localization and perception problems for autonomous vehicles.
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.
In today’s education, healthcare, and manufacturing sectors, organizations and information societies are discussing new enhancements to corporate structure and process efficiency using digital platforms. These enhancements can be achieved using digital tools. Industry 5.0 and Society 5.0 give several potentials for businesses to enhance the adaptability and efficacy of their industrial processes, paving the door for developing new business models facilitated by digital platforms. Society 5.0 can contribute to a super-intelligent society that includes the healthcare industry. In the past decade, the Internet of Things, Big Data Analytics, Neural Networks, Deep Learning, and Artificial Intelligence (AI) have revolutionized our approach to various job sectors, from manufacturing and finance to consumer products. AI is developing quickly and efficiently. We have heard of the latest artificial intelligence chatbot, ChatGPT. OpenAI created this, which has taken the internet by storm. We tested the effectiveness of a considerable language model referred to as ChatGPT on four critical questions concerning “Society 5.0”, “Healthcare 5.0”, “Industry,” and “Future Education” from the perspectives of Age 5.0.
In this work, a web-based software architecture and framework for management and diagnosis of large amounts of medical data in an ophthalmologic reading center is proposed. Data management for multi-center studies requires merging of standing data and repeatedly gathered clinical evidence such as vital signs and raw data. If ophthalmologic questions are involved the data acquisition is often provided by non-medical staff at the point of care or a study center, whereas the medical finding is mostly provided by an ophthalmologist in a specialized reading center. The study data such as participants, cohorts and measured values are administrated at a single data center for the entire study. Since a specialized reading center maintains several studies, the medical staff must learn the different data administration for the different data center. With respect to the increasing number and sizes of clinical studies, two aspects must be considered. At first, an efficient software framework is required to support the data management, processing and diagnosis by medical experts at the reading center. In the second place, this software needs a standardized user-interface that has not to be trained/taylore /adapted for each new study. Furthermore different aspects of quality and security controls have to be included. Therefore, the objective of this work is to establish a multi purpose ophthalmologic reading center, which can be connected to different data centers via configurable data interfaces in order to treat various topics simultaneously.
Personalized remote healthcare monitoring is in continuous development due to the technology improvements of sensors and wearable electronic systems. A state of the art of research works on wearable sensors for healthcare applications is presented in this work. Furthermore, a state of the art of wearable devices, chest and wrist band and smartwatches available on the market for health and sport monitoring is presented in this paper. Many activity trackers are commercially available. The prices are continuously reducing and the performances are improving, but commercial devices do not provide raw data and are therefore not useful for research purposes.
Traditional communication of research on climate change fails to encourage individual, corporate, and political leaders to take appropriate action. We argue that this problem is based on an overly simplistic unidirectional model of science communication. Conversely, theory shows that active learning processes are better suited to initiate and mobilize engagement among all stakeholders. Here, we integrate theoretical insights on active learning with empirical evidence from serious gaming: communication should be understood as an integral design feature that relates active learning on climate change to tangible action.
Ion Mobility Spectrometry (IMS) is a widely used and `well-known’ technique of ion separation in the gaseous phase based on the differences in ion mobilities under an electric field. All IMS instruments operate with an electric field that provides space separation, but some IMS instruments also operate with a drift gas flow that provides also a temporal separation. In this review we will summarize the current IMS instrumentation. IMS techniques have received an increased interest as new instrumentation and have become available to be coupled with mass spectrometry (MS). For each of the eight types of IMS instruments reviewed it is mentioned whether they can be hyphenated with MS and whether they are commercially available. Finally, out of the described devices, the six most-consolidated ones are compared. The current review article is followed by a companion review article which details the IMS hyphenated techniques (mainly gas chromatography and mass spectrometry) and the factors that make the data from an IMS device change as a function of device parameters and sampling conditions. These reviews will provide the reader with an insightful view of the main characteristics and aspects of the IMS technique.
Ion Mobility Spectrometry (IMS) is a widely used and ‘well-known’ technique of ion separation in the gaseous phase based on the differences of ion mobilities under an electric field. This technique has received increased interest over the last several decades as evidenced by the pace and advances of new IMS devices available. In this review we explore the hyphenated techniques that are used with IMS, specifically mass spectrometry as an identification approach and a multi-capillary column as a pre-separation approach. Also, we will pay special attention to the key figures of merit of the ion mobility spectrum and how data sets are treated, and the influences of the experimental parameters on both conventional drift time IMS (DTIMS) and miniaturized IMS also known as high Field Asymmetric IMS (FAIMS) in the planar configuration. The present review article is preceded by a companion review article which details the current instrumentation and contains the sections that configure both conventional DTIMS and FAIMS devices. These reviews will give the reader an insightful view of the main characteristics and aspects of the IMS technique.
Customer relationship management (CRM) is one of the most frequently adopted management tools and has received much attention in the literature. From a company-wide perspective, CRM is viewed as a complex process requiring interventions in different company areas. Previous research has already highlighted the pitfalls and failures related to a partial and incomplete view of CRM. This study advances research on CRM by investigating the impact of the relative implementation time according to which interventions are implemented in different areas (customer management, CRM technology, organizational alignment, and CRM strategy) on CRM performance. The results of the empirical study reveal that compared to other critical CRM activities, a later implementation of organizational alignment activities has a negative impact on performance. Further, our results show that CRM implementations do not equally address the areas of customer acquisition, growth, and loyalty, since this clearly depends on company objectives and also on geographical differences.
The impact of stress of every human being has become a serious problem. Reported impact on persons are a higher rate or health disorders like heart problems, obesity, asthma, diabetes, depressions and many others. An individual in a stressful situation has to deal with altered cognition as well as an affected decision making skill and problem solving. This could lead to a higher risk for accidents in dynamic environments such as automotive. Different papers faced the estimation as well as prediction of drivers’ stress level during driving. Another important question is not only the stress level of the driver himself, but also the influence on and of a group of other drivers in the near area. This paper proposes a system, which determines a group of drivers in a near area as clusters and it derives or computes the individual stress level. This information will be analyzed to generate a stress map, which represents a graphical view about road section with a higher stress influence. Aggregated data can be used to generate navigation routes with a lower stress influence as well as recommend driving behavior to decrease stress influenced driving as well as improve road safety.
Over the last 50 years, neoclassical financial theory has been dominating our perception of what is happening in financial markets. It has spurred numerous valuable theories and concepts all based on the concept of Homo Economicus, the strictly rational economic man. However, humans do not always act in a strictly rational manner. For students and practitioners alike, our book aims at opening the door to another perspective on financial markets: a behavioral perspective based on a Homo Oeconomicus Humanus. This agent acts with limited rationality when making decisions. He/she uses heuristics and shortcuts and is prone to the influence of emotions. This sounds familiar in real life and can be transferred to what happens in financial markets, too.
Indicators of disruption potentials - analysis of the blockchain technology’s potential impact
(2019)
The goal of this paper was to answer the question whether blockchain has the potential to become a disruption according to Clayton Christensen’s disruption theory. Therefore, the theory and the five characteristics that define the process of disruption were outlined in the first part of the paper. That and the following explanation of the blockchain technology served as the basis for the analysis and evaluation in chapters four to seven. For the analysis, three applications of the DLT, namely payment methods, intermediaries, as well as data storage and transfer, were considered. The fulfillment of the five characteristics of disruption was assessed using an example for each of the three applications.
Additionally, the paper might serve as a basis for future research on the topic, once the technology develops further, since it is generally hard to tell whether the fourth and fifth characteristics are fulfilled by blockchain at this point. Therefore, the results of the paper also back criticism of Christensen’s theory regarding its usefulness for predictions.
This paper suggests that, in the financial services industry, too, the impact of blockchain will be significant. However, given the manifoldness of the services that are part of the industry, it cannot generally be concluded whether the DLT will disrupt the industry. For example, in services related to payment methods, blockchain is unlikely to follow disruptive pattern, despite the recent hype surrounding blockchain-based cryptocurrencies. However, regarding data storage and transfer, the technology might as well follow disruptive pattern in the financial services industry just as the application of blockchain solutions has been doing in the healthcare industry.
The intention of this paper is to show that the statistical approach to risk is not enough to explain the behavior of investors. It furthermore proposes ideas and alternative approaches on how to deal with risk. Psychological findings are of particular interest as they might enhance our understanding of risk perception and assessment. The chapter “From the normal distribution to fat tails” starts with the rejection of the normal distribution as a simplifying basis for risk and return. This rejection is supported by several empirical observations like clustering of volatility and fat tails. This leads to a two-step approach for modeling risk and return based on the distinction of conditional and un-conditional changes. Conditional time series models (ARMA, ARCH, GARCH) and alternative distributions are presented (Stable Paretian, Student’s T, EVT) as a way to improve the art of risk and return modeling beyond the normal distribution assumption. The chapter ends with the conclusion that each model is only a statistical approximation and never encompasses the unpredictability of black swans and the nature of human behavior in the financial markets. After having discussed the limitations of the purely statistical approach to risk and return this paper goes beyond the standard theory of finance for two purposes. Firstly, behavioral finance provides some arguments for the limitation of statistics in assessing risk. Secondly, an alternative approach to risk perception is presented. This alternative is called Prospect Theory, a rather psychology-based approach using preferences to explain investors’ actions by human behavior in decision making processes. Starting point is the utility function and the value function followed by a description of the two phases: framing and evaluation. The value function is then clearly distinguished from the utility function by elaborating certain effects like reference points, loss aversion or the weighting function. In this section the paper enters the arena of human risk perception which is far from being monetarily rational in the sense of the homo oeconomicus. With Cumulative Prospect Theory there exists an extension to multiple outcome scenarios where risk does not necessarily have to be known. In such a situation, besides risk, there also exists immeasurable uncertainty. Current research confirms and rejects parts of (Cumulative) Prospect Theory which is not necessarily a bad sign as human behavior is rarely exactly replicable and the complexity does not really allow generalizations. Therefore, even if the theory is not completely correct it still enhances our understanding of risk perception and human decision making which can be a very valuable input for agent-based models. The next chapter analyses in more detail possible distortions from psychological biases in the assessment of risk. In this context the law of small numbers, overconfidence and feelings/experience are discussed. Knowing these biases complicates the idea of developing a risk model even further. However, this is again another step to better understand the underlying processes and motives of decision making in the context of financial markets. The last chapter is an attempt to link the different aspects to get a holistic view on risk behavior. Two possibilities are discussed: Hedonic psychology, with the distinction between blow up and bleeding strategy, and heuristic-based explanations for real observations like clustering of expectations and trust in experts. This leaves space for further research as we do not have a tool that is based on current findings and can actually help us in explaining and predicting behavior in financial markets. One possibility would be to link all these aspects in the approach of computational finance to develop agent-based models in which market observations, psychological findings and the situational context can be integrated.
In a recent publication Novy-Marx (2013) finds evidence that the variable gross profitability has a strong statistical influence on the common variation of stock returns. He also points out that there is common variation in stock returns related to firm profitability that is not captured by the three-factor model of Fama and French (1993). Thus, this thesis augments the three-factor model by the factor gross profitability and examines whether a profitability-based four-factor model is able to better explain monthly portfolio excess returns on the German stock market compared to the three-factor model of Fama and French (1993) and the Capital Asset Pricing Model (CAPM). Based on monthly stock returns of the CDAX over the period July 2008 to June 2014 this thesis documents four main findings. First, a significant positive market risk premium and a significant positive value premium can be identified. No evidence is found for a size or a profitability effect. Second, all included factors have a strong significant effect on monthly portfolio excess returns. Third, the four-factor model clearly outperforms both the three-factor model of Fama and French (1993) and the CAPM in capturing the common variation in monthly portfolio excess returns. The CAPM performs worst. Finally, the results indicate that the three-factor model of Fama and French (1993) is somewhat better in explaining the cross-section of portfolio excess returns than the four-factor model. Again, the CAPM performs worst. Nevertheless, the four-factor model is considered to be an improvement over the three-factor model of Fama and French (1993) and the CAPM in determining stock returns on the German stock market.
In a corporation’s financial life “going public” by means of an IPO is probably the single most important decision. It turns a private company into a public one. Our book will provide an inside view of the IPO process. On the one hand, it draws on the insights of an experienced investment banker, who has gone through numerous IPO transactions. On the other hand, it relates the story of an actual IPO through the eyes of a Chief Executive Officer who has taken two of his companies public. This unique double perspective is our book’s defining feature. We do not discuss initial public offerings in a textbook style fashion. What we would like to bring out is a more comprehensive portrayal of a “once-in-a-lifetime” event for most companies and their management, alike.
The transmembrane Ca2+ − activated Cl− channel - human bestrophin-1 (hBest1) is expressed in retinal pigment epithelium and mutations of BEST1 gene cause ocular degenerative diseases colectivelly referred to as “bestrophinopathies”. A large number of genetical, biochemical, biophysical and molecular biological studies have been performed to understand the relationship between structure and function of the hBest1 protein and its pathophysiological significance. Here, we review the current understanding of hBest1 surface organization, interactions with membrane lipids in model membranes, and its association with microdomains of cellular membranes. These highlights are significant for modulation of channel activity in cells.
The Commitment of Traders report (CoT) has been around for over 30 years, consistently revealing the futures positions of key market players. This study's primary aim is to use the comprehensive data from the Commitment of Traders reports to develop a short-term reversal trading strategy. Against the benchmark, a S&P 500 buy-and-hold approach with a Sharpe ratio of 1.07, the CoT long only strategy generated significant results in six individual markets. Extending the strategy to long-and-short, two markets outperformed the benchmark significantly. However, a scenario analysis indicated underperformance of the CoT strategy when traded in a portfolio, confirming that the chosen strategy parameters could not generate excess Sharpe ratios. Our results indicate that the Commodity Futures Trading Commission, more specifically the CoT report, contributed to efficient derivatives market.
Public transport causes in rural areas high costs per passenger and kilometer as the frequency of scheduled busses is low and therefore, many people avoid using public transport. With the trend of moving from urban regions to countryside individual traffic will further increase. To tackle issues of emissions, mobility for young and elderly people and provide economically meaningful public transport a new concept was elaborated in Germany. This consists of (partly) autonomous shuttle busses which are remote controlled. For implementation rural districts of Germany have worked together and set up a three-phase plan consisting of a project with public funding, a highly frequent used pilot region and industrial partners with the commitment and possibilities for necessary investments. The concept promises economical value with respect to installation, service and maintaining costs, it leads to lower barriers for public transport of young and elderly people and ultimately reduces emissions and congestions.
Urban platforms are essential for smart and sustainable city planning and operation. Today they are mostly designed to handle and connect large urban data sets from very different domains. Modelling and optimisation functionalities are usually not part of the cities software infrastructure. However, they are considered crucial for transformation scenario development and optimised smart city operation. The work discusses software architecture concepts for such urban platforms and presents case study results on the building sector modelling, including urban data analysis and visualisation. Results from a case study in New York are presented to demonstrate the implementation status.
On the design of an urban data and modeling platform and its application to urban district analyses
(2020)
An integrated urban platform is the essential software infrastructure for smart, sustainable and resilitent city planning, operation and maintenance. Today such platforms are mostly designed to handle and analyze large and heterogeneous urban data sets from very different domains. Modeling and optimization functionalities are usually not part of the software concepts. However, such functionalities are considered crucial by the authors to develop transformation scenarios and to optimized smart city operation. An urban platform needs to handle multiple scales in the time and spatial domain, ranging from long term population and land use change to hourly or sub-hourly matching of renewable energy supply and urban energy demand.
Customer foresight is a relatively new research field. We introduce the customer foresight territory by discussing it localization between customer research and foresight research. For this purposse, we look at a variety of methods that help to understand customers and future realities. On this basis we provide an overwiew of customer foresight methods and outline an ideal-typical research journey.
Purpose: Emotions play a central role in approach-avoidance customer conflicts in retailing. The purpose of this paper is to assess the influence of emotions in the fashion retail environment, in particular to investigate how emotions can be best defined and clustered as well as how emotions affect the costumer behavior.
Findings: The conceptual paper reveals a framework explaining diverse theories of emotional models existing in literature. Moreover, the stimulus-organism-response model is applied to costumer behaviour in the fashion retail to explain the shopping experience under the influence of cognitive and affective emotional processes. Finally, it is concluded that point of sales have to be turned to point of emotions in order retailers are able to develop sustainable relationships with their customers.
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.
The pH value of the human skin is not in the neutral range but is slightly acidic with values of – depending on the body part – 3.5 to 6. This provides a suitable habitat for the commensal skin floral but has a killing effect on some pathogenic micro-organisms and an inactivating effect on some viruses. This protective acid mantle of the skin thus represents a first external protective layer against infestation by pathogens. An appropriate surface pH on textiles can help to minimize the transmission of pathogens through the clothing of healthcare workers while at the same time not exerting a negative influence on the skin’s own flora. In addition, the colonization of e.g. bed linen by pathogenic microorganisms can be reduced. This can also have a positive influence on bacteria-associated odor formation on functional clothing.
The pH value of the human skin is not in the neutral range but is slightly acidic with values of – depending on the body part – 3.5 to 6. This provides a suitable habitat for the commensal skin floral but has a killing effect on some pathogenic micro-organisms and an inactivating effect on some viruses. This protective acid mantle of the skin thus represents a first external protective layer against infestation by pathogens. An appropriate surface pH on textiles can help to minimize the transmission of pathogens through the clothing of healthcare workers while at the same time not exerting a negative influence on the skin’s own flora. In addition, the colonization of e.g. bed linen by pathogenic microorganisms can be reduced. This can also have a positive influence on bacteria-associated odor formation on functional clothing.
High-performance liquid chromatography is one of the most important analytical tools for the identification and separation of substances. The efficiency of this method is largely determined by the stationary phase of the columns. Although monodisperse mesoporous silica microspheres (MPSM) represent a commonly used material as stationary phase their tailored preparation remains challenging. Here we report on the synthesis of four MPSMs via the hard template method. Silica nanoparticles (SNPs) which form the silica network of the final MPSMs were generated in situ from tetraethyl orthosilicate (TEOS) in the presence of (3-aminopropyl) triethoxysilane (APTES) functionalized p(GMA-co-EDMA) as hard template. Methanol, ethanol, 2-propanol, and 1-butanol were applied as solvents to control the size of the SNPs in the hybrid beads (HB). After calcination, MPSMs with different sizes, morphology and pore properties were obtained and characterized by scanning electron microscopy, nitrogen adsorption and desorption measurements, thermogravimetric analysis, solid state NMR and DRIFT IR spectroscopy. Interestingly, the 29Si NMR spectra of the HBs show T and Q group species which suggests that there is no covalent linkage between the SNPs and the template. The MPSMs were functionalized with trimethoxy (octadecyl) silane and used as stationary phases in reversed-phase chromatography to separate a mixture of eleven different amino acids. The separation characteristics of the MPSMs strongly depend on their morphology and pore properties which are controlled by the solvent during the preparation of the MPSMs. Overall, the separation behavior of the best phases is comparable with those of commercially available columns. The phases even achieve faster separation of the amino acids without loss of quality.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Business models for renewable energy are compound on different logic than business models for larger scale power plants. Following a design science research approach, we examined the business models of three enterprises in the energy domain in a first step. We identified that these business models result in complex ecosystems with multiple actors and difficult relationships between them. One cause is the fast changing and complicated state regulation in Germany. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed the prototype Business Model Configurator (BMConfig) based on the e3Value Ontology on the metamodelling platform ADOxx. We demonstrate the feasibility of our approach in business model of energy efficiency service based on smart meter data.
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.
To remain relevant and mitigate disruption, traditional companies have to engage in multiple fast-paced experiments in digital offerings: revenue-generating solutions that leverage digital technologies to address customer needs. After launching several digital offering initiatives, reinsurance giant Munich Re noticed that many experienced similar challenges. This briefing describes how Munich Re addressed these common challenges by building a foundation for experimenting more systematically and successfully with digital offerings. The foundation has enabled Munich Re to become a serial innovator of digital offerings.
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.
A device including a first and second monitoring unit, the first monitoring unit detecting a first voltage potential and the second monitoring unit detecting a second voltage potential, the monitoring units comparing the first voltage potential and the second voltage potential to the value of the supply voltage and activate a control unit as a function of the comparisons, the control unit determining a switching point in time of a second power transistor, and an arrangement being present which generates current when the second power transistor is being switched on, the current changing the first voltage potential, and the control unit activates a first power transistor when the first voltage potential has the same value as the supply voltage, so that the first power transistor is de-energized.
While academia and industry see large potential for human-robot collaboration (HRC), only a small number of realized HRC application is currently found in industry. To gather more data about current hindrances to wider implementation of collaborative robots, a study among 15 robot manufactureres and 14 system integrators of collaborative robot technology has been conducted through a predesigned questionnaire procedure. Additionally, five industrial users of human-robot collaboration have been interviewed on the main challenges they experienced during the initial implementation process. The quantitative data has been analyzed using the Wilcoxon-Signed-Rank-Test. Accoring to the study participants, the main challenges within the implementation currently are the identification of HRC-suitable processes, the application of relevant safety norms (such as ISO 10218, ISO/TS 15066) and the application-individual risk assessment.
In many cases continuous monitoring of vital signals is required and low intrusiveness is an important requirement. Incorporating monitoring systems in the hospital or home bed could have benefits for patients and caregivers. The objective of this work is the definition of a measurement protocol and the creation of a data set of measurements using commercial and low-cost prototypes devices to estimate heart rate and breathing rate. The experimental data will be used to compare results achieved by the devices and to develop algorithms for feature extraction of vital signals.
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.
The recovery of our body and brain from fatigue directly depends on the quality of sleep, which can be determined from the results of a sleep study. The classification of sleep stages is the first step of this study and includes the measurement of vital data and their further processing. The non-invasive sleep analysis system is based on a hardware sensor network of 24 pressure sensors providing sleep phase detection. The pressure sensors are connected to an energy-efficient microcontroller via a system-wide bus. A significant difference between this system and other approaches is the innovative way in which the sensors are placed under the mattress. This feature facilitates the continuous use of the system without any noticeable influence on the sleeping person. The system was tested by conducting experiments that recorded the sleep of various healthy young people. Results indicate the potential to capture respiratory rate and body movement.
In recent decades, it can be observed that a steady increase in the volume of tourism is a stable trend. To offer travel opportunities to all groups, it is also necessary to prepare offers for people in need of long-term care or people with disabilities. One of the ways to improve accessibility could be digital technologies, which could help in planning as well as in carrying out trips. In the work presented, a study of barriers was first conducted, which led to selecting technologies for a test setup after analysis. The main focus was on a mobile app with travel information and 360° tours. The evaluation results showed that both technologies could increase accessibility, but some essential aspects (such as usability, completeness, relevance, etc.) need to be considered when implementing them.
Concrete is significant for construction. A problem in application is the appearance of cracks that will damage its strength. An autogenous crack-healing mechanism based on bacteria receives increasing attention in recent years. The bacteria are able to form calcium carbonate (CaCO3) precipitations in suitable conditions to protect and reinforce the concrete. However, a large number of spores are crushed in aged specimens, resulting in a loss of viability. A new kind of hydrogel crosslinked by alginate, chitosan and calcium ions was introduced in this study. It was observed that the addition of chitosan improved the swelling properties of calcium alginate. Opposite pH response to calcium alginate was observed when the chitosan content in the solution reached 1.0%. With an addition of 1.0% chitosan in hydrogel beads, 10.28% increase of compressive strength and 13.79% increase of flexural strength to the control were observed. The results reveal self-healing properties of concretes. A healing crack of 4 cm length and 1 mm width was observed when using cement PO325, with the addition of bacterial spores (2.54–3.07 × 105/cm3 concrete) encapsulated by hydrogel containing no chitosan.
Acting like a startup - using corporate startup structures to manage the digital transformation
(2023)
Digital transformation is proving to be a significant challenge for firms and companies when it comes to maintaining their market position. It is evident that many companies are struggling to find their particular way through this transformation. A corporate startup structure is one way to find a suitable solution quickly. Therefore, we are presenting a model for corporate startup activities, which we will instantiate in an appropriate tool to support the management of corporate startups by their parent firms. We have derived the first requirements and design principles from a comprehensive problem analysis and literature study. In addition to this,we are presenting a first artifact, which should realize the design principles by implementing a practical tool. Forming a cooperation with an automotive firm has enabled us to gain access to real-world data for the design and evaluation of the artifact.
This book investigates and highlights the most critical challenges the pharmaceutical industry faces in an increasingly competitive environment of inflationary R&D investments and tightening cost control pressures. The authors present three sources of pharmaceutical innovation: new management methods in the drug development pipeline; new technologies as enablers for cutting-edge R&D; and new forms of cooperation and internationalization, such as open innovation in the early phases of R&D. New models and methods are illustrated with cases from Europe, the US, and Asia. This third fully revised edition was expanded to reflect the latest updates in open and collaborative innovation, the greater strategic importance of venture capital and early stage investments, and the new range of emerging technologies now being put to use in pharmaceutical innovation.
Purpose: The purpose of this paper is to assess the state of the art concerning the information demand of the sustainable consumer focusing on the characterization of the sustainable customer, the demanded information content with regard to fashion products and the expected information frame.
Findings: Key findings of this paper are that sustainable consumers share certain psychographics such as sustainable knowledge and perceived customer effectiveness. So demanded information content is about general sustainable knowledge and the concrete impact of sustainable purchase behavior. Fashion product attributes demanded are details about production, material and the after-purchase use. Concerning the information frame, consumers expect information to be credible, transparent and comprehensible. Eco-labels play an important role within the information frame.
The surface properties of human meibomian lipids (MGS), the major constituent of the tear film (TF) lipid layer, are of key importance for TF stability. The dynamic interfacial properties of films by MGS from normal eyes (nMGS) and eyes with meibomian gland dysfunction (dMGS) were studied using a Langmuir surface balance. The behavior of the samples during dynamic area changes was evaluated by surface pressure–area isotherms and isocycles. The surface dilatational rheology of the films was examined in the frequency range 10−5 to 1 Hz by the stress-relaxation method. A significant difference was found, with dMGS showing slow viscosity-dominated relaxation at 10−4 to 10−3 Hz, whereas nMGS remained predominantly elastic over the whole range. A Cole–Cole plot revealed two characteristic processes contributing to the relaxation, fast (on the scale of characteristic time τ < 5 s) and slow (τ > 100 s), the latter prevailing in dMGS films. Brewster angle microscopy revealed better spreading of nMGS at the air–water interface, whereas dMGS layers were non-uniform and patchy. The distinctions in the interfacial properties of the films in vitro correlated with the accelerated degradation of meibum layer pattern at the air–tear interface and with the decreased stability of TF in vivo. These results, and also recent findings on the modest capability of meibum to suppress the evaporation of the aqueous subphase, suggest the need for a re-evaluation of the role of MGS. The probable key function of meibomian lipids might be to form viscoelastic films capable of opposing dilation of the air–tear interface. The impact of temperature on the meibum surface properties is discussed in terms of its possible effect on the normal structure of the film.
We investigate the toxicity of different types and sizes of microplastic particles (0.3–4 mm) under different conditions (new particles, aged particles with biofilm, and particles with adsorbed Tributyltin) on the freshwater amphipod Gammarus fossarum in 3-week exposures. All types of plastic particles, which were randomly taken up to a small extent, were mostly Polyphenylenoxide, Polybutylentherephthalate and Polypropylene, with particles < 1 mm in size. Plastic particles did not affect the feeding and locomotory behaviour of gammarids, and there was no strong difference between pristine plastic particles and aged particles with biofilm. Mortality tended to be higher compared with the control. Tributyltinhydride (TBTH) adsorbed to microplastic particles had no effect on uptake, survival, feeding and locomotory behaviour during the 3 weeks of exposure. Dissolved TBTH, however, was already very toxic after few days of exposure (LC50-96h < 1 ng l–1).
What does the factory of tomorrow have to offer for companies? This question and its aspects are the focus of many actual articles and publications. According to Gartner digital twins, one of 2017 strategic technology trends will play a big role for the future of manufacturing. At the moment digital twins are gaining more importance for the industrial application. If companies want to be competitive in the future they have to implement the digital twin in the factories of today. Therefore this paper provides a basic overview of the concept of the smart factory and its requirements. In addition, digital twins are identified as a necessary concept for the evolution of the factory of today.
Purpose: The purpose of this paper is to analyse the main elements of successful customer loyalty programs in general and emotional components of the buying process in order to determine loyalty programs for fashion retailers.
Findings: The results of this study indicate that loyalty programs in fashion retail require considerable non-monetary benefits such as sense of exclusive membership and enhanced status to distinguish from competitors customer loyalty programs.
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.
Ein wichtiges Qualifikationsziel von heutigen Wirtschaftsingenieurstudien-programmen ist, Studierende dazu zu befähigen, vernetzt, ganzheitlich, interkulturell und interdisziplinär zu denken und zu handeln. Die Lehr- und Lerninnovation Quest 3C fördert durch ein integratives Blended-Learning Format sowohl die Vermittlung von grundlegendem Fachwissen als auch von berufsqualifizierenden Schlüsselkompetenzen.
This article explores current debate on the use of soft power in international higher education, highlighting existing tensions between competing political and academic discourses. It draws on examples from practice and relevant insights in soft power scholarship to capture varying paradoxes and dilemmas that emerge as nations try to leverage the power of international tertiary education to enhance their brand and attract foreign audiences in the name of public diplomacy. Whilst exposing cases of hubris and hidden agendas, this study also addresses issues of inequality and responds to a growing call for knowledge diplomacy aimed at tackling common global problems.
The use of gamification in workplace learning to encourage employee motivation and engagement
(2019)
When we think about playing a game, be it a card game, board game, sport, or video game, we generally associate the act of playing with a positive experience like having fun, enjoying the interaction with others, or feeling a greater motivation to reach a certain goal. By contrast, workplace learning is often perceived as being dull. Employees are likely at some point in their career to find themselves stuck in a rigidly defined seminar for a long period of time or in front of their computer navigating through a mandatory e-learning course on a dry topic such as standards of business conduct of safety policies.
In recent years, organizations have tried to leverage the motivating quality of games for more serious learning contexts. Gamification entails transferring those elements and principles from games to nongaming context that improve user experience and engagement. In this chapter, we will specifically focus on the context of workplace learning.
This article examines centralised and decentralised approaches towards managing internationalisation by means of a case study. Reutlingen University (Hochschule Reutlingen), a university of applied sciences in Southern Germany, has three decades of experience in managing internationalisation. Its strongly integrated and hybrid approach combines centralised and decentralised strategies with the aim of achieving responsiveness, innovation, transparency, quality, and goal alignment. Centralisation and decentralisation are manifested on two levels: university versus schools, and school versus individual programmes. Since internationalisation is embedded in virtually all areas of the university’s operations, examples will be provided ranging from administration and marketing to research, international programme management and curricula.
Based on a survey among customers of seven German municipal utilities, we estimate two regression models to identify the most prospective customer segments and their preferences and motivations for participating in peer-to-peer (P2P) electricity trading and develop implications for decision-makers in the energy sector and policy-makers for this currently relatively unknown product. Our results show a large general openness of private households towards P2P electricity trading, which is also the main predictor of respondents' intention to participate. It is mainly influenced by individuals’ environmental attitude, technical interest, and independence aspiration. Respondents with the highest willingness to participate in P2P electricity trading are mainly motivated by the ability to share electricity, and to a lesser extent by economic reasons. They also have stronger preferences for innovative pricing schemes (service bundles, time-of-use tariffs). Differences between individuals can be observed depending on their current ownership (prosumers) or installation probability of a microgeneration unit (consumers, planners). Rather than current prosumers, especially planners willing to install microgeneration in the foreseeable future are considered to be the most promising target group for P2P electricity trading. Finally, our results indicate that P2P electricity trading could be a promising niche option in the German energy transition.
Based on a survey among customers of seven German municipal utilities, we estimate hierarchical multiple regression models to identify consumer motivations for participating in P2P electricity trading and develop implications for marketing strategies for this currently relatively unknown product. Our results show a low importance of socio-demographics in explaining differences between consumer groups, but high influence of attitudes, knowledge and likelihood to purchase related products. The most valuable target groups for P2P electricity trading marketing strategies of municipal utilities first and foremost should aim at are innovators, especially prosumers. They are well-informed about and open minded concerning electricity sharing and highly environmentally aware. They ask for transparency and are willing to purchase related products. They are attracted by the ability to share generation and consumption and to a lesser extent by economic reasons. Our results indicate that the marketing efforts should to a special degree take peer effects into account, as they are found to wield great influence on general openness towards and purchase intention for P2P electricity products. Finally, municipal utilities should build on the high level of satisfaction and trust of consumers and use P2P electricity trading as measure to keep and win customers willing to change their supplier.
Rational strain engineering requires solid testing of phenotypes including productivity and ideally contributes thereby directly to our understanding of the genotype-phenotype relationship. Actually, the test step of the strain engineering cycle becomes the limiting step, as ever advancing tools for generating genetic diversity exist. Here, we briefly define the challenge one faces in quantifiying phenotypes and summarize existing analytical techniques that partially overcome this challenge. We argue that the evolution of volatile metabolites can be used as proxy for cellular metabolism. In the simplest case, the product of interest is a volatile (e.g., from bulk alcohols to special fragrances) that is directly quantified over time. But also nonvolatile products (e.g., from bulk long-chain fatty acids to natural products) require major flux rerouting that result potentially in altered volatile production. While alternative techniques for volatile determination exist, rather few can be envisaged for medium to high-throughput analysis required for phenotype testing. Here, we contribute a detailed protocol for an ion mobility spectrometry (IMS) analysis that allows volatile metabolite quantification down to the ppb range. The sensivity can be exploited for small-scale fermentation monitoring. The insights shared might contribute to a more frequent use of IMS in biotechnology, while the experimented aspects are of general use for researchers interested in volatile monitoring.