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The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Die vorliegende Arbeit untersucht, inwiefern extrapersonale Einflussfaktoren das Verhalten der Wissensteilung im Offboarding in der öffentlichen Verwaltung Deutschlands beeinflussen. Hier besteht eine Forschungslücke, die es insbesondere vor dem Hintergrund einer nahenden Pensionierungswelle und der daraus resultierenden Gefahr eines massiven Wissensverlusts zu schließen gilt. Zu diesem Zweck werden unterschiedliche Analyseebenen verknüpft, Einflussfaktoren aus der Literatur herausgearbeitet und in die Theorie des geplanten Verhaltens eingebunden. Anschließend werden Hypothesen formuliert, wie extrapersonale Einflussfaktoren, die sich aus der Verwaltung als organisationalen Kontext und dem Prozess des Offboarding ergeben, das Verhalten der Wissensteilung fördern oder hemmen. Die Testung der Hypothesen erfolgt durch die Erhebung und Auswertung qualitativer Interviewdaten. Daraus resultierende Erkenntnisse verdeutlichen, dass die anstehende Pensionierungswelle in der deutschen Verwaltung eine stärkere Ausrichtung des organisationalen Wissensmanagements auf den Prozess des Offboarding und dessen Gestaltung erfordert, um Wissensverluste zu reduzieren.
Faced with the triad of time-cost-quality, the realization of knowledge-intensive tasks at economic conditions is not trivial. Since the number of knowledge-intensive processes is increasing more and more nowadays, the efficient design of knowledge transfers at business processes as well as the target-oriented improvement of them is essential, so that process outcomes satisfy high quality criteria and economic requirements. This particularly challenges knowledge management, aiming for the assignment of ideal manifestations of influence factors on knowledge transfers to a certain task. Faced with first attempts of knowledge transfer-based process improvements [1], this paper continues research about the quantitative examination of knowledge transfers and presents a ready-to-go experiment design that is able to examine quality of knowledge transfers empirically and is suitable to examine knowledge transfers on a quantitative level. Its use is proven by the example of four influence factors, which namely are stickiness, complexity, competence and time pressure.
In light of the debate on the consequences of competitive contracting out of traditionally public services, this research compares two mechanisms used to allocate funds in development cooperation—direct awarding and competitive contracting out—aiming to identify their potential advantages and disadvantages.
The agency theory is applied within the framework of rational-choice institutionalism to study the institutional arrangements that surround two different money allocation mechanisms, identify the incentives they create for the behavior of individual actors in the field, and examine how these then transfer into measurable differences in managerial quality of development aid projects. In this work, project management quality is seen as an important determinant of the overall project success.
For data-gathering purposes, the German development agency, the Gesellschaft für Internationale Zusammenarbeit (GIZ), is used due to its unique way of work. Whereas the majority of projects receive funds via direct-award mechanism, there is a commercial department, GIZ International Services (GIZ IS) that has to compete for project funds.
The data concerning project management practices on the GIZ and GIZ IS projects was gathered via a web-based, self-administered survey of project team leaders. Principal component analysis was applied to reduce the dimensionality of the independent variable to total of five components of project management. Furthermore, multiple regression analysis identified the differences between the separate components on these two project types. Enriched by qualitative data gathered via interviews, this thesis offers insights into everyday managerial practices in development cooperation and identifies the advantages and disadvantages of the two allocation mechanisms.
The thesis first reiterates the responsibility of donors and implementers for overall aid effectiveness. It shows that the mechanism of competitive contracting out leads to better oversight and control of implementers, fosters deeper cooperation between the implementers and beneficiaries, and has a potential to strengthen ownership of recipient countries. On the other hand, it shows that the evaluation quality does not tremendously benefit from the competitive allocation mechanism and that the quality of the component knowledge management and learning is better when direct-award mechanisms are used. This raises questions about the lacking possibilities of actors in the field to learn about past mistakes and incorporate the finings into the future interventions, which is one of the fundamental issues of aid effectiveness. Finally, the findings show immense deficiencies in regard to oversight and control of individual projects in German development cooperation.
Organizations continue building virtual working teams (Teleworkers) to become more dynamic as part of their strategic innovation, with great benefits to individuals, business and society. However, during such transformations it is important to note that effective knowledge communication is particularly difficult in distributed environments as well as in non-interactive settings, because the interlocutors cannot use gestures or mimicry and have to adapt their expressions without receiving any feedback, which may affect the creation of tacit knowledge. Collective Intelligence appears to be an encouraging alternative for creating knowledge. However, in this scenario it faces an important goal to be achieved, as the degree of ability of two or more individuals increases with the need to overcome barriers through the aggregation of separately processed information, whereby all actors follow similar conditions to participate in the collective. Geographically distributed organizations have the great challenge of managing people’s knowledge, not only to keep operations running, but also to promote innovation within the organization in the creation of new knowledge. The management of knowledge from Collective Intelligence represents a big difference from traditional methods of information allocation, since managing Collective Intelligence poses new requirements. For instance, semantic analysis has to merge information, coming both from the content itself and the social/individual context, and in addition, the social dynamics that emerge online have to be taken into account. This study analyses how knowledge-based organizations working with decentralized staff may need to consider the cognitive styles and social behaviors of individuals participating in their programs to effectively manage knowledge in virtual settings. It also proposes assessment taxonomies to analyze online comportments at the levels of the individual and community, in order to successfully identify characteristics to help evaluate higher effectiveness of communication. We aim at modeling measurement patterns to identify effective ways of interaction of individuals, taking into consideration their cognitive and social behaviors.
Industry 4.0, i.e. the connection of cyber-physical systems via the Internet in production and logistics, leads to considerable changes in the socio-technical system of the factory. The effects range from a considerable need for further training, which is exacerbated by the current shortage of skilled workers, to an opening of the previously inaccessible boundaries of the factory to third-party access, an increasing merging of office IT and manufacturing IT, and a new understanding of what machines can do with their data. This results in new requirements for the modeling, analysis and design of information processing and performance mapping business processes.
In the past, procedures were developed under the name of “process-oriented knowledge management” with which the exchange and use of knowledge in business processes could be represented, analyzed and improved. However, these approaches were limited to the office environment. A method that makes it possible to document, analyze and jointly optimize the new possibilities of knowledge processing by using artificial intelligence and machine learning in production and logistics in the same way and in a manner compatible with the approach in the office environment does not exist so far. The extension of the modeling language KMDL, which is described in this paper, will contribute to close this research gap.
This paper describes first approaches for an analysis and design method for a knowledge management integrating man and machine in the age of Industry 4.0.
Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers.
Marktüberblick
(2005)
Diese Marktstudie vermittelt einen Überblick über Software, die zur Unterstützung von Wissensmanagement eingesetzt werden kann und berücksichtigt dabei die Spannweite von spezialisierten Suchmaschinen bis zu umfassenden integrierten Wissensmanagementsystemen. Die untersuchte Software bietet sowohl Unterstützung bei Community-orientierten Wissensmanagementansätzen als auch bei Information Retrieval. Die Einsatzmöglichkeiten sind genauso unterschiedlich wie die heterogenen Anforderungen von Unternehmen und Organisationen, die diese an Wissensmanagement stellen. Eine direkte Vergleichbarkeit aller untersuchten Softwareprodukte ist daher nicht sinnvoll.
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.