Refine
Year of publication
Institute
- Fachbereich Wirtschaftswissenschaften (1158) (remove)
Language
- German (934)
- English (217)
- Portuguese (6)
- Spanish (1)
Document Type
- Article (705)
- Book (221)
- Part of a Book (72)
- Conference Proceeding (69)
- Other (48)
- Review (13)
- Working Paper (9)
- Contribution to a Periodical (5)
- Doctoral Thesis (5)
- Lecture (5)
Keywords
- Führung (8)
- Leadership (8)
- Telekommunikationsmarkt (6)
- Datenschutz (5)
- Motivation (5)
- Betriebswirtschaftslehre (4)
- Finanzierung (4)
- Liquiditätspolitik (4)
- Datenschutzgrundverordnung (3)
- Self-Leadership (3)
The successful implementation and continuous development of sustainable corporate-level solutions is a challenge. These are endeavours in which social, environmental, and financial aspects must be weighed against each other. They can prove difficult to handle and, in some cases, almost unrealistic. Concepts such as green controlling, IT, and manufacturing look promising and are constantly evolving. This paper aims to achieve a better understanding of the field of corporate sustainability (CS). It will evaluate the hypothesis by which Corporate Sustainability thrives, via being efficient, increasing the performance, and raising the value of the input of the enterprises to the resources used. In fact, Corporate Sustainability on the surface could seem to contradict the idea, which supports the understanding that it encourages the reduction of the heavy reliance on the use of natural resources, the overall environmental impact, and above all, their protection. To understand how the contradictory notion of CS came about, in this part of the paper, the emphasis is placed on providing useful insight to this regard. The first part of this paper summarizes various definitions, organizational theories, and measures used for CS and its derivatives like green controlling, IT, and manufacturing. Second, a case study is given that combines the aforementioned sustainability models. In addition to evaluating the hypothesis, the overarching objective of this paper is to demonstrate the use of green controlling, IT, and manufacturing in the corporate sector. Furthermore, this paper outlines the current challenges and possible directions for CS in the future.
Allgemeines Steuerrecht
(2015)
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Der folgende Bericht fasst Erfahrungen zusammen, die in großen Entwicklungsprojekten der Firma Ericsson über mehrere Jahre gesammelt wurden. Ziel war dabei nicht, agile Methoden und Techniken einzusetzen - Agilität war zu der Zeit noch kein Hype-Thema. Vielmehr wurden Schwächen in den eigenen Projekten identifiziert und verbessert. Der Erfahrungsbericht vergleicht Verbesserungen in diesen Projekten mit den Ansätzen der agilen Entwicklung. Als Ergebnis werden folgende Punkte festgehalten: Erstens, einige Praktiken und Werte der agilen Entwicklung lassen sich auch in Großprojekten einsetzen. Zweitens, bei der Skalierung für Großprojekte werden diese Praktiken langsamer getaktet. Drittens, agile Entwicklung ist nicht nur eine Reihe von Praktiken und Werten, agile Entwicklung ist vielmehr auch eine Frage der Entwicklungs- und Projektkultur. Diese kulturelle Änderung lässt sich in Großprojekten deutlich langsamer umsetzen.
Integrated voice assistants (IVA) receive more and more attention and are widespread for entertainment use cases, such as radio hearing or web searches. At the same time, the health care segment suffers in process inefficiency and missing staff, whereas the usage of IVA has the potential to improve caring processes and patient satisfaction. By applying a design science approach and based on a qualitative study, we identify IVA requirements, barriers and design guidelines for the health care sector. The results reveal three important IVA functions: the ability to set appointments with care service staff, the documentation of health history and the communication with service staff. Integration, system stability and volume control are the most important nonfunctional requirements. Based on the interview results and project experiences, six design and implementation guidelines are derived.