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The existence of several mobile operating systems, such as Android and iOS, is a challenge for developers because the individual platforms are not compatible with each other and require separate app developments. For this reason, cross-platform approaches have become popular but lack in cloning the native behavior of the different operating systems. Out of the plenty cross-platform approaches, the progressive web app (PWA) approach is perceived as promising but needs further investigation. Therefore, the paper at hand aims at investigating whether PWAs are a suitable alternative for native apps by developing a PWA clone of an existing app. Two surveys are conducted in which potential users test and evaluate the PWA prototype with regard to its usability. The survey results indicate that PWAs have great potential, but cannot be treated as a general alternative to native apps. For guiding developers when and how to use PWAs, four design guidelines for the development of PWA-based apps are derived based on the results.
Leveraging Social Network Data for Analytical CRM Strategies - The Introduction of Social BI.
(2012)
Bitcoin is a cryptocurrency and is considered a high-risk asset
class whose price changes are difficult to predict. Current research focusses
on daily price movements with a limited number of predictors. The paper at
hand aims at identifying measurable indicators for Bitcoin price movement s
and the development of a suitable forecasting model for hourly changes. The
paper provides three research contributions. First, a set of significant
indicators for predicting the Bitcoin price is identified. Second, the results of
a trained Long Short-term Memory (LSTM) neural network that predicts
price changes on an hourly basis is presented and compared with other
algorithms. Third, the results foster discussions of the applicability of neural
nets for stock price predictions. In total, 47 input features for a period of
over 10 months could be retrieved to train a neural net that predicts the
Bitcoin price movements with an error rate of 3.52 %.
Many of today’s factors make software development more and more complex, such as time pressure, new technologies, IT security risks, et cetera. Thus, a good preparation of current as well as future software developers in terms of a good software engineering education becomes progressively important. As current research shows, Competence Developing Games (CDGs) and Serious Games can offer a potential solution.
This paper identifies the necessary requirements for CDGs to be conducive in principle, but especially in software engineering (SE) education. For this purpose, the current state of research was summarized in the context of a literature review. Afterwards, some of the identified requirements as well as some additional requirements were evaluated by a survey in terms of subjective relevance.
Häufig bremsen geringe IT-Ressourcen, fehlende Softwareschnittstellen oder eine veraltete und komplex gewachsene Systemlandschaft die Automatisierung von Geschäftsprozessen. Robotic Process Automation (RPA) ist eine vielversprechende Methode, um Geschäftsprozesse oberflächenbasiert und ohne größere Systemeingriffe zu automatisieren und Medienbrüche abzubauen. Die Auswahl der passenden Prozesse ist dabei für den Erfolg von RPA-Projekten entscheidend. Der vorliegende Beitrag liefert dafür Selektionskriterien, die aus einer qualitativen Inhaltanalyse von elf Interviews mit RPA-Experten aus dem Versicherungsumfeld resultieren. Das Ergebnis umfasst eine gewichtetet Liste von sieben Dimensionen und 51 Prozesskriterien, welche die Automatisierung mit Softwarerobotern begünstigen bzw. deren Nichterfüllung eine Umsetzung erschweren oder sogar verhindern. Die drei wichtigsten Kriterien zur Auswahl von Geschäftsprozessen für die Automatisierung mittels RPA umfassen die Entlastung der an dem Prozess mitwirkenden Mitarbeiter (Arbeitnehmerüberlastung), die Ausführbarkeit des Prozesses mittels Regeln (Regelbasierte Prozessteuerung) sowie ein positiver Kosten-Nutzen-Vergleich. Praktiker können diese Kriterien verwenden, um eine systematische Auswahl von RPA-relevanten Prozessen vorzunehmen. Aus wissenschaftlicher Perspektive stellen die Ergebnisse eine Grundlage zur Erklärung des Erfolgs und Misserfolgs von RPA-Projekten dar.
Das Gesundheitswesen ist konfrontiert mit steigenden Kosten und einer immer schwieriger werdenden Personalsituation. Zeitgleich versprechen moderne Sprachsteuerungssysteme Prozesse in Arztpraxen und Krankenhäusern zu verschlanken und Vorgänge zu beschleunigen. Dennoch wird derzeit der Einsatz von Sprachsteuerungssystemen in Arztpraxen oder Krankenhäusern nur selten beobachtet, was auch an den besonders strengen Datenschutzauflagen der Datenschutzgrundverordnung (DSGVO) liegt. Darüber hinaus wirft die niedrige Nutzungsrate die Frage nach den konkreten Anforderungen und ihrer Umsetzbarkeit auf, was durch den vorliegenden Beitrag adressiert wird, indem die Ergebnisse von Interviews mit acht medizinischen Fachexperten ausgewertet werden. Ergänzend wird die technische Umsetzbarkeit einzelner Anforderungen mit unterschiedlichen Cloud-Anbietern erprobt.
Digital start-ups are perceived as an engine for innovation and job promotor. While success factors for non-IT start-ups have already been extensively researched, this study sheds light on digital entrepreneurs, whose business model relies primarily on services based on digital technologies. Applying the Grounded Theory method, we identify relevant environmental success factors for digital entrepreneurs. The study’s research contribution is threefold. First, we provide 16 relevant and less relevant environmental success factors, which enables a comparison with prior identified factors. We found out that several prior environmental success factors, such as accessibility to transportation or the availability of land and facilities are less relevant for a digital entrepreneur. Second, we derive and discuss hypotheses for the influence of these factors on digital start-up success. Third, we present a theoretical model that lays the foundation for explaining the environmental influence on digital
entrepreneurship success.
The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores.