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- Fachbereich Wirtschaftswissenschaften (1100) (remove)
In Fortschreibung des Jahresrückblicks 2018 (Olbertz, NWB 5/2019 S. 266 ) skizziert der vorliegende Beitrag die jüngsten nennenswerten Entwicklungen im Arbeitsrecht des Jahres 2019. Im Bereich der Gesetzgebung, mit dem sich der erste Teil des Beitrags befasst, betrifft dies etwa das Fachkräfteeinwanderungsgesetz, die angestoßenen Schutzvorschriften für Whistleblower oder das gesetzlich verankerte Recht auf Brückenteilzeit. In der arbeitsrechtlichen höchstrichterlichen Rechtsprechung stand das Jahr 2019 insbesondere im Zeichen des Befristungs- und des Urlaubsrechts. Was hier und darüber hinaus wegweisend war, zeigt der zweite Teil des Beitrags.
Eigenkapitalkosten sind eine wesentliche Determinante bei der Wertbestimmung von Unternehmen und Unternehmensteilen. Die Eigenkapitalkosten werden regelmäßig mittels des CAPM bestimmt. Für sog. konzerninterne Routinefunktionen mit geringem Risiko stellt diese Bestimmung mittels CAPM ein Problem dar, da börsennotierte Peergroups für eine zuverlässige Bestimmung des Beta-Faktors meist nicht identifizierbar sind. Damit ergeben sich bei Bewertungen von Routineunternehmen Unsicherheiten und Konfliktpotenzial in steuerlichen Betriebsprüfungen. Dieser Beitrag gibt einen Überblick der in der Praxis genutzten Ansätze und stellt eine theoretische Fundierung zur Bestimmung der Eigenkapitalkosten von konzerninternen Routinefunktionen vor. Dabei wird verdeutlicht, dass Eigenkapitalkosten von konzerninternen Routinefunktionen nicht denen des Gesamtkonzerns entsprechen und Praktikeransätze eine grundsätzliche Berechtigung besitzen.
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 %.
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
In the past decade, many IS researchers focused on researching the phenomenon of Big Data. At the same time, the relevance of data protection gets more attention than ever before. In particular, since the enactment of the European General Data Protection Regulation in May 2018 Information Systems research should provide answers for protecting personal data. The article at hand presents a structuring framework for Big Data research outcome and the consideration of data protection. IS Researchers might use the framework in order to structure Big Data literature and to identify research gaps that should be addressed in the future.
Small Claims Regulation
(2017)
Names of individuals
(2017)
Einleitung vor § 1297
(2014)
Vorbemerkung vor § 1297
(2014)
Vorbemerkung vor § 1353
(2014)
Einleitung vor § 1297 BGB
(2011)
This Research Briefing, issued in July 2010, concluded that:
- Small and medium-sized enterprises (SMEs) in Europe have long called for a matching legal form valid across the EU (similar to that of the European company (SE) for large firms)
- The main benefits would be the availability of uniform Europe-wide company structures, significant cost reductions for businesses and further integration of the internal market
- Given the differing national views regarding the concrete features of the new legal form there is currently no sign of an agreement being reached at the European level in the short term; however, it is possible that progress will be made in negotiations during the year
- The key issues being discussed in depth are company formation, transnationality and employee participation rights in the new European private company (SPE).