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Requirements for an integration of methods analyzing social issues in knowledge organizations
(2006)
Adaptability of information systems has become a substantial competition factor. Today's insufficient methodical support for the realization of adaptability frequently leads to unused potentials of deployed information technology in enterprises. In this contribution a procedure is presented, which addresses the demand to determine the necessary adaptability of an enterprise related to its surrounding environmental environment.
Skill Management
(2006)
Skill management catalogues built via KMDL : integrating knowledge and business process modelling
(2004)
The efficient use of human capital is one of the most important factors in todays' business competition. Competition is strongly influenced by qualified staff. In order to aid the human resources department to keep up with strategic decisions various skill management systems have been created that make the development of human resources easier and more precise. Skill management systems are only as good as the information that they are based on. The mostly used basic information is the skill catalogue which shows the gaps of each employee or division within the company. But there are nearly no applicable methods yet to create such a catalogue thoroughly. This paper introduces a reasonable approach to create such a catalogue with the description language for knowledge-intensive processes KMDL. The skill catalogue built for skill management systems is one of the most important but still most neglected factors when introducing skill management.
In Organisationen mit mehreren hundert oder mehr Mitarbeitern ist es kaum möglich, einen Überblick über die Kompetenzen und Spezialkenntnisse von Beschäftigten zu behalten. Die Suche nach Fachleuten gestaltet sich dann oft schwierig, zum Beispiel wenn ein Projektteam zusammengestellt werden soll. Hilfe versprechen Skill- Management-Systeme, vorausgesetzt, ihre Datenbank wurde sinnvoll eingerichtet und wird laufend aktualisiert. Die Autoren beschreiben Aufbau und Struktur derartiger Systeme, fragen nach ihren kosten und nennen Kriterien für professionelle Lösungen.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
This paper shows the KMDL Knowledge Management Approach which is based on the SECI and ba model by Nonaka and Takeuchi and the KMDL Knowledge modeling language. The approach illustrates the creation of knowledge with the focus on the knowledge conversions by Nonaka and Takeuchi. Furthermore, it emphasizes the quality of knowledge being embodied in persons and creates a personalization and socialization strategy which integrates business process modeling, skill management and the selection of knowledge management systems. The paper describes the theoretical foundations of the approach and practical effects which have been seen in the use of this approach.
Künstliche Intelligenz ist in aller Munde. Immer mehr Anwendungsbereiche werden durch die Auswertung von vorliegenden Daten mit Algorithmen und Frameworks z.B. des Maschinellen Lernens erschlossen. Dieses Buch hat das Ziel, einen Überblick über gegenwärtig vorhandene Lösungen zu geben und darüber hinaus konkrete Hilfestellung bei der Auswahl von Algorithmen oder Tools bei spezifischen Problemstellungen zu bieten. Um diesem Anspruch gerecht zu werden, wurden 90 Lösungen mittels einer systematischen Literaturrecherche und Praxissuche identifiziert sowie anschließend klassifiziert. Mit Hilfe dieses Buches gelingt es, schnell die notwendigen Grundlagen zu verstehen, gängige Anwendungsgebiete zu identifizieren und den Prozess zur Auswahl eines passenden ML-Tools für das eigene Projekt systematisch zu meistern.
Trends in der ERP Branche
(2017)