Nicht ermittelbar
Filtern
Volltext vorhanden
- nein (162)
Dokumenttyp
- Teil eines Buches (Kapitel) (162) (entfernen)
Gehört zur Bibliographie
- ja (162)
Schlagworte
- Integration (4)
- Migration (3)
- Verwaltung (3)
- Corona (2)
- Digitalisierung (2)
- Gleichstellung (2)
- Koordinierung (2)
- artificial intelligence (2)
- browser platforms (2)
- lokale Behörden (2)
Institut
- Fachgruppe Politik- & Verwaltungswissenschaft (61)
- Öffentliches Recht (30)
- Fachgruppe Betriebswirtschaftslehre (26)
- Strafrecht (13)
- Bürgerliches Recht (10)
- Fachgruppe Soziologie (9)
- Sozialwissenschaften (8)
- Lehreinheit für Wirtschafts-Arbeit-Technik (5)
- Fachgruppe Volkswirtschaftslehre (4)
- Historisches Institut (3)
BBodSchG § 5 Entsiegelung
(2000)
Appropriation Art
(2020)
A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS.
Rechnungshöfe
(2020)
As part of the digitization, the role of artificial systems as new actors in knowledge-intensive processes requires to recognize them as a new form of knowledge bearers side by side with traditional knowledge bearers, such as individuals, groups, organizations. By now, artificial intelligence (AI) methods were used in knowledge management (KM) for knowledge discovery, for the reinterpreting of information, and recent works focus on the studying of different AI technologies implementation for knowledge management, like big data, ontology-based methods and intelligent agents [1]. However, a lack of holistic management approach is present, that considers artificial systems as knowledge bearers. The paper therefore designs a new kind of KM approach, that integrates the technical level of knowledge and manifests as Neuronal KM (NKM). Superimposing traditional KM approaches with the NKM, the Symbiotic Knowledge Management (SKM) is conceptualized furthermore, so that human as well as artificial kinds of knowledge bearers can be managed as symbiosis. First use cases demonstrate the new KM, NKM and SKM approaches in a proof-of-concept and exemplify their differences.
Comparative methods B
(2020)
This chapter outlines the relevance and value of comparative approaches and methods in studying Public Administration (PA). It discusses the roots and current developments of comparative research in PA and discusses various methodological venues for cross-country comparisons, such as most similar/dissimilar systems designs, the method of concomitant variation and the difference-in-difference method. Besides the description of these approaches, we highlight their conceptual value for theory-driven empirical comparative research. Drawing on selected pieces of comparative research, the chapter furthermore provides examples for the application of comparative methods in practice presenting empirical findings and highlighting strengths and weaknesses. The chapter finally emphasizes that the methodological development in comparative PA research has by far not yet reached its end, and that some future challenges need to be addressed, such as the issues of causality, generalizability, and mixed-methods approaches.