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Purpose – This paper aims to determine the affecting factors of the brand authenticity of startups in social media.
Design/methodology/approach – Using a qualitative method based on a grounded theory approach, this research specifies and classifies the affecting factors of brand authenticity of startups in social media through in-depth semi-structured interviews.
Findings – Multiple factors affecting the brand authenticity of startups in social media are determined and categorized as indexical, iconic and existential cues through this research. Connection to heritage and having credible support are determined as indexical cues. Founder intellectuality, brand intellectuality, commitment toward customers and proactive clear and interesting communications are identified as iconic cues. Having self-confidence and self-satisfaction, having intimacy with the brand and a joyful feeling for interactions with the community around the brand are determined as existential cues in this research. This research furthers previous arguments on a multiplicity of brand authenticity by shedding light on the relationship between the different aspects of authenticity and the form that different affecting factors can be organized together. Consumers eventually evaluate a strengthened perception of brand authenticity through existential cues that reflect the cues of other aspects (iconic and indexical) which passed through the goal-based assessment and self-authentication filter.
Research limitations/implications – The research sampling population can be more diversified in terms of sociodemographic attributes. Due to the qualitative methodology of this research, assessment of the findings through quantitative methods can be considered in future research. Practical implications – Using the findings of this research, startup managers can properly build a perception of authenticity in their consumers’ minds by using alternate factors while lacking major indexical cues such as heritage. This research helps startup businesses to design their brand communications better to convey their authenticity to their audiences.
Originality/value – This research determines the factors affecting the authenticity of startup brands in social media. It also defines the process of authenticity perception through different aspects of brand authenticity.
Academic research is vital for innovation and industrial growth. However, a potential burden of processing ever more knowledge could be affecting research output and researchers’ careers. We look at a dataset of researchers who have published in journals in the field of economics during a period of 45 years. For a subset of these researchers, we amass data from journals listed in the EconLit database, supplemented with years of birth from public sources. Our results show an increase in the age of researchers at their first publication, in the number of articles referenced in debut articles, and in the number of co-authors. Simultaneously, we observe a decline in the probability of researchers changing research fields. Our findings extend earlier findings on patents and hint at a burden of knowledge pervading different areas of human progress. Moreover, our results indicate that researchers develop strategies of specialisation to deal with this challenge.
COVID-19 and educational inequality: How school closures affect low- and high-achieving students
(2021)
In spring 2020, governments around the globe shut down schools to mitigate the spread of the novel coronavirus. We argue that low-achieving students may be particularly affected by the lack of educator support during school closures. We collect detailed time-use information on students before and during the school closures in a survey of 1099 parents in Germany. We find that while students on average reduced their daily learning time of 7.4 h by about half, the reduction was significantly larger for low-achievers (4.1 h) than for high-achievers (3.7 h). Low-achievers disproportionately replaced learning time with detrimental activities such as TV or computer games rather than with activities more conducive to child development. The learning gap was not compensated by parents or schools who provided less support for low-achieving students.
Identifikation von Schlaf- und Wachzuständen durch die Auswertung von Atem- und Bewegungssignalen
(2021)
In the current age of innovative business financing opportunities available from fintech apps, social media crowdfunding sites such as Kickstarter, Indiegogo, and RocketHub, et.al., and friends and family private equity investors, start-up firms can strategically source their venture capital funds from many globally disperse organizations and individuals. As the firm in this case learned, the benefit of alternative investing sources comes with a critical hidden risk for corporate governance. After a financial restructuring, a typical Silicon Valley software start-up found itself with close to 300 external individual shareholders, some of whom had not been documented as accredited investors. The regulatory agency could decide that the prior actions of the founders and the decisions of the board had been prejudicial to the interests of the minority investors. The management of this small private company faced an atypical investor relations dilemma, before its initial public offering (IPO).
In this work, a comparison between different brushless harmonic-excited wound-rotor synchronous machines is performed. The general idea of all topologies is the elimination of the slip rings and auxiliary windings by using the already existing stator and rotor winding for field excitation. This is achieved by injecting a harmonic airgap field with the help of power electronics. This harmonic field does not interact with the fundamental field, it just transfers the excitation power across the airgap. Alternative methods with varying number of phases, different pole-pair combinations, and winding layouts are covered and compared with a detailed Finite-Element-parameterized model. Parasitic effects due to saturation and coupling between the harmonic and main windings are considered.
Massive data transfers in modern data-intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-Data processing (NDP) and a shift to code-to-data designs may represent a viable solution as packaging combinations of storage and compute elements on the same device has become feasible. The shift towards NDP system architectures calls for revision of established principles. Abstractions such as data formats and layouts typically spread multiple layers in traditional DBMS, the way they are processed is encapsulated within these layers of abstraction. The NDP-style processing requires an explicit definition of cross-layer data formats and accessors to ensure in-situ executions optimally utilizing the properties of the underlying NDP storage and compute elements. In this paper, we make the case for such data format definitions and investigate the performance benefits under RocksDB and the COSMOS hardware platform.
Continuous monitoring of individual vital parameters can provide information for the assessment of one’s health and indications of medical problems in the context of personalized medicine. Correlations between parameters and health issues are to be evaluated. As one project in this topic area, a telemedicine platform is implemented to gather data of outpatients via wearables and accumulate them for physicians and researchers to review. This work extracts requirements, draws use case scenarios, and shows the current system architecture consisting of a patient application, a physician application with a web server, and a backend server application. In further work, the prototype will assist to develop a vendor-free and open monitoring solution. A conclusion on functionality and usability will be evaluated in an imminent first study.
As consumer awareness surrounding impacts of the climate crisis continues to be a notable threat, businesses are searching for new models to make their sustainability profile even better. As a result, the implementation of a company’s sustainability vision following the SDGs has to be linked closely to the integration of customers into strategic action. One success factor is the management of customers over their entire life cycle. The Customer Journey serves as a model to systematise this approach, by designing touchpoints throughout the purchasing process in order to motivate consumers to act sustainably. Based on behaviour models, the authors develop recommendations for the food industry to design a sustainable Customer Journey that helps to reduce the percentage of consumers reporting positive attitudes to sustainable products while not exhibiting corresponding behaviour.
Imagine a world in which the search for tomorrow's trends of (software) products is not subject to a long and laborious data search but is possible with a single mouse click. Through the use of artificial intelligence (AI), this reality is made possible and is to be further advanced through research. The study therefore aims to provide an initial overview of the young research field. Based on research, expert interviews, company and student surveys, current application possibilities of AI in the innovation process (defined as Smart Innovation), existing challenges that slow down the further development are discussed in more detail and future application possibilities are presented. Finally, a recommendation for action is made for business, politics and science to help overcome the current obstacles together and thus drive the future of Smart Innovation.
Imagine a world in which the search for tomorrow's trends is not subject to a long and laborious data search but is possible with a single mouse click. Through the use of artificial intelligence (AI), this reality is made possible and is to be further advanced through research. The study therefore aims to provide an initial overview of the young research field. Based on research, expert interviews, company and student surveys, current application possibilities of AI in the innovation process (defined as Smart Innovation), existing challenges that slow down the further development are discussed in more detail and future application possibilities are presented. Finally, a recommendation for action is made for business, politics and science to help overcome the current obstacles together and thus drive the future of Smart Innovation.
In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper-edges, which allows to present data structures on different abstraction levels. We prove that the model is at least equivalent in expressive power to most popular data models. Therefore, it can be used as a supermodel for model management and data integration. We illustrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, XML model, and RDF Schema.
Deep learning-based EEG detection of mental alertness states from drivers under ethical aspects
(2021)
One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations.
Seit über 12 Jahren findet nun die Informatics Inside als Informatikkonferenz an der Hochschule Reutlingen statt, in diesem Jahr zum zweiten Mal in einem halbjährigen Rhythmus, d.h. auch im Herbst. Diese Wissenschaftliche Konferenz des Masterstudiengangs Human-Centered Computing wird von den Studierenden selbst organisiert und durchgeführt. Sie erhalten während ihres Masterstudiums die Gelegenheit sich in einem selbstgewählten Fachthema zu vertiefen. Dies kann an der Hochschule, in einem Unternehmen, einem Forschungsinstitut oder im Ausland durchgeführt werden. Gerade diese flexible Ausgestaltung des Moduls „Wissenschaftliche Vertiefung“ führt zu einem sehr breiten Themenspektrum, das von den Studierenden bearbeitet wird. Neben der eigentlichen fachlichen Vertiefung spielt auch die Präsentation und Verteidigung von wissenschaftlichen Ergebnissen eine wichtige Rolle und dies weit über das Studium hinaus. Ein gewähltes Fachgebiet so allgemeinverständlich aufzubereiten und zu vermitteln, dass es auch für Nicht-Spezialisten verständlich wird, stellt immer wieder eine besondere Herausforderung dar. Dieser Herausforderung stellen sich die Studierenden im Rahmen der Herbstkonferenz zur Wissenschaftlichen Vertiefung am 24. November 2021. Bereits zum vierten Mal wird die Veranstaltung in einem online-Modus stattfinden, einschließlich eines virtuellen Begleitprogramms.
Das Themenspektrum der diesjährigen Herbstkonferenz ist wieder sehr vielfältig und breit gefächert. So erwarten Sie u.a. Beiträge aus dem Gesundheitssektor, dem Maschinellen Lernen, der KI und VR sowie dem Marketing und E-Learning. Allen gemein ist ein sehr starker Bezug zu innovativen Informatikansätzen, was sich auch in dem Wortspiel und Motto „RockIT Science“ der Konferenz widerspiegelt. Die Informatik durchdringt fast alle beruflichen und privaten Anwendungsbereiche und hat zunehmend größeren Einfluss auf unser tägliches Leben. Dies kann einerseits Besorgnis und andererseits Begeisterung auslösen. Gerade letzteres wollen die Studierenden mit Ihren Beiträgen erreichen und es auch mal im Informatiksektor „rocken“ lassen.
Context-aware systems to support actors in the operating room depending on the status of the intervention require knowledge about the current situation in the intra-operative area. In literature, solutions to achieve situation awareness already exist for specific use cases, but applicability and transferability to other conditions are less addressed. It is assumed that a unified solution that can be adapted to different processes and sensors would allow for greater flexibility, applicability, and thus transferability to different applications. To enable a flexible and intervention-independent system, this work proposes a concept for an adaptable situation recognition system. The system consists of four layers with several modular components for different functionalities. The feasibility is demonstrated via prototypical implementation and functional evaluation of a first basic framework prototype. Further development goal is the stepwise extension of the prototype.
Silicon photonic micro-ring resonators (MRR) developed on the silicon-on-insulator (SOI) platform, owing to their high sensitivity and small footprint, show great potential for many chemical and biological sensing applications such as label-free detection in environmental monitoring, biomedical engineering, and food analysis. In this tutorial, we provide the theoretical background and give design guidelines for SOI-based MRR as well as examples of surface functionalization procedures for label-free detection of molecules. After introducing the advantages and perspectives of MRR, fundamentals of MRR are described in detail, followed by an introduction to the fabrication methods, which are based on a complementary metal-oxide semiconductor (CMOS) technology. Optimization of MRR for chemical and biological sensing is provided, with special emphasis on the optimization of waveguide geometry. At this point, the difference between chemical bulk sensing and label-free surface sensing is explained, and definitions like waveguide sensitivity, ring sensitivity, overall sensitivity as well as the limit of detection (LoD) of MRR are introduced. Further, we show and explain chemical bulk sensing of sodium chloride (NaCl) in water and provide a recipe for label-free surface sensing.
Together with many success stories, promises such as the increase in production speed and the improvement in stakeholders' collaboration have contributed to making agile a transformation in the software industry in which many companies want to take part. However, driven either by a natural and expected evolution or by contextual factors that challenge the adoption of agile methods as prescribed by their creator(s), software processes in practice mutate into hybrids over time. Are these still agile In this article, we investigate the question: what makes a software development method agile We present an empirical study grounded in a large-scale international survey that aims to identify software development methods and practices that improve or tame agility. Based on 556 data points, we analyze the perceived degree of agility in the implementation of standard project disciplines and its relation to used development methods and practices. Our findings suggest that only a small number of participants operate their projects in a purely traditional or agile manner (under 15%). That said, most project disciplines and most practices show a clear trend towards increasing degrees of agility. Compared to the methods used to develop software, the selection of practices has a stronger effect on the degree of agility of a given discipline. Finally, there are no methods or practices that explicitly guarantee or prevent agility. We conclude that agility cannot be defined solely at the process level. Additional factors need to be taken into account when trying to implement or improve agility in a software company. Finally, we discuss the field of software process-related research in the light of our findings and present a roadmap for future research.
Prior to the introduction of AI-based forecast models in the procurement department of an industrial retail company, we assessed the digital skills of the procurement employees and surveyed their attitudes toward a new digital technology. The aim of the survey was to ascertain important contextual factors which are likely to influence the acceptance and the successful use of the new forecast tool. What we find is that the digital skills of the employees show an intermediate level and that their attitudes toward key aspects of new digital technologies are largely positive. Thus, the conditions for high acceptance and the successful use of the models are good, as evidenced by the high intention of the procurement staff to use the models. In line with previous research, we find that the perceived usefulness of a new technology and the perceived ease of use are significant drivers of the willingness to use the new forecast tool.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
In buchstäblich letzter Minute haben sich die englische Regierung und die Europäische Union auf ein umfangreiches Abkommen geeinigt, um einen ungeregelten Brexit zu verhindern. Nach dem jahrelangen zähen Verhandlungsmarathon fällt der Jubel verhalten aus, dennoch herrscht auf beiden Seiten des Ärmelkanals Erleichterung, weil ein Modus Vivendi gefunden wurde, auf dem sich die künftigen Beziehungen aufbauen und fortführen lassen. Ob sich die englischen Blütenträume, die an den Brexit geknüpft wurden, erfüllen werden, wird die Zukunft erweisen.
Die Strategie und Taktik der englischen Regierungen zum Brexit und bei den Austrittsverhandlungen spiegeln sich in den Erfahrungen wider, die Friedrich List vor genau 175 Jahren bei seinen Bemühungen um eine deutsch-englische Allianz machen musste. Wegen der von England schon damals strikt befolgten Insular und Handelssuprematie musste er sich eingestehen, dass England diese Position hartnäckig verteidigt und deshalb frustriert und ernüchtert seine Pläne aufgeben. Deshalb setzte er seine Hoffnung auf eine "Kontinentalallianz" der europäischen Nationen, wie sie nun nach dem Austritt Großbritanniens aus der Europäischen Union entstanden ist. Vielleicht werden wir uns nun an den Begriff "Kontinentalallianz" gewöhnen müssen und dabei an die Weitsicht von Friedrich List erinnert.
Andererseits gilt auch für die englische Politik das Motto von Lists zweiter Pariser Preisschrift: "Le monde marche - Die Welt bewegt sich", allerdings mit völlig anderen Vorzeichen als vor 175 Jahren: Die Welthandelsachse hat sich von der westlichen auf die östliche Halbkugel verlagert; das britische Weltreich ist Geschichte, die Fließgeschwindigkeit des globalen Wandels hat sich dramatisch beschleunigt und trotz der Lingua Franca erscheint England, vor allem aus asiatischer Sicht, nur noch als kleiner Fleck auf der Weltkarte. Falls die schottische Regierung ihre Absicht durchsetzen und die Unabhängigkeit vom Vereinigten Königreich erreichen sollte, würde sich der Brexit als verhängnisvoller Bumerang erweisen.