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To this date, it is difficult to find high-level statistics on YouTube that paint a fair picture of the platform in its entirety. This study attempts to provide an overall characterization of YouTube, based on a random sample of channel and video data, by showing how video provision and consumption evolved over the course of the past 10 years. It demonstrates stark contrasts between video genres in terms of channels, uploads and views, and that a vast majority of on average 85% of all views goes to a small minority of 3% of all channels. The analytical results give evidence that older channels have a significantly higher probability to garner a large viewership, but also show that there has always been a small chance for young channels to become successful quickly, depending on whether they choose their genre wisely.
Virtual reality (VR) offers the opportunity to create virtual worlds that could replace real experiences. This research investigates the influence of user motivation, temporal distance and experience type on the satisfaction with the VR experience, and the degree of acceptance of a VR experience as a substitute for a real experience. The results suggest that the degree of acceptance of a VR experience as a substitute for a real experience is higher for passive VR experiences compared to active VR experiences. Furthermore, the results support the assumption that users are more satisfied with passive VR experiences.
Virtual reality in the hotel industry: assessing the acceptance of immersive hotel presentation
(2019)
In the hotel industry, it is crucial to reduce the inherent information asymmetry with regard to the goods offered. This asymmetry can be minimised through the use of smartphone-based virtual reality applications (SBVRs), which allow virtual simulation of real experiences and thus enable more efficient information retrieval. The aim of the study is to determine for the first time the user acceptance of these immersive hotel presentations for assessing the performance of a travel accommodation. For this purpose, the Technology Acceptance Model (TAM) was used to explain the acceptance behaviour for this new technology. A virtual reality application was specially developed, in which the participants could explore a hotel virtually. A total of 569 participants took part in the study. The structural equation model and the hypotheses were tested using a Partial Least Squares (PLS) analysis. The results illustrate that the immersive product experience leads to more efficient information gathering. The perceived usefulness significantly affects the attitude towards using the technology as well as the intention to use it. In contrast to the traditional TAM, the perceived ease of use of SBVRs has no effect on the perceived usefulness or attitude towards using the technology.
Für viele Studierende sind Vorkurse der erste Kontakt zu Hochschullehre und Mitstudierenden. Wie kann der fachliche Einstieg in einem digitalen Lehrformat trotz fehlender Präsenz gelingen und persönliche Unterstützung, ein erstes Kennenlernen und soziale Eingebundenheit gefördert werden? Diesem Erkenntnisinteresse folgend stellt der folgende Beitrag ein digitales Brückenkursformat mit Elementen zur Interaktion, Kommunikation und Kollaboration vor, das mit ca. 400 Studierenden in zehn Kursen mit acht Lehrbeauftragten umgesetzt und entlang der o.g. Frage evaluiert wurde. Um den Transfer auf andere Lehrveranstaltungen zu erleichtern, wurde das Konzept in ein didaktisches Entwurfsmuster übertragen.
Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques
(2020)
This study evaluates four machine learning (ML) techniques (Decision Trees (DT), Random Forests (RF), Neural Networks (NN) and Probabilistic Neural Networks (PNN)) on their ability to accurately predict export credit insurance claims. Additionally, we compare the performance of the ML techniques against a simple benchmark (BM) heuristic. The analysis is based on the utilisation of a dataset provided by the Berne Union, which is the most comprehensive collection of export credit insurance data and has been used in only two scientific studies so far. All ML techniques performed relatively well in predicting whether or not claims would be incurred, and, with limitations, in predicting the order of magnitude of the claims. No satisfactory results were achieved predicting actual claim ratios. RF performed significantly better than DT, NN and PNN against all prediction tasks, and most reliably carried their validation performance forward to test performance.