TY - THES A1 - Beel, Leon T1 - Teilen von Wissen im Offboarding in der öffentlichen Verwaltung Deutschlands T1 - Knowledge sharing during offboarding in German public administration N2 - 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. N2 - This bachelor thesis examines the extent to which extra-personal influencing factors shape the behavior of knowledge sharing in offboarding processes in German public administration. There is a research gap here that needs to be closed urgently, especially given the approaching wave of retirements and the resulting risk of a massive loss of knowledge. For this purpose, different levels of analysis are linked, influencing factors are identified and integrated into the Theory of Planned Behavior. Hypotheses are then formulated as to how extra-personal influencing factors resulting from administration as an organizational context and the process of offboarding promote or inhibit knowledge sharing behavior. The hypotheses are tested by collecting and analyzing qualitative interview data. The findings make it clear that the upcoming wave of retirements in the German public administration requires a stronger orientation of organizational knowledge management towards the process of offboarding and its design in order to reduce knowledge losses. T3 - Schriftenreihe für Public und Nonprofit Management - 29 KW - Wissensmanagement KW - knowledge management KW - Teilen von Wissen/Wissensteilung KW - knowledge sharing Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-562108 SN - 2190-4561 ER - TY - GEN A1 - Chujfi, Salim A1 - Meinel, Christoph T1 - Patterns to explore cognitive preferences and potential collective intelligence empathy for processing knowledge in virtual settings N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 409 KW - computer science KW - telework KW - knowledge management KW - thinking styles KW - learning styles KW - self-government KW - collective intelligence KW - collaborative work KW - cognitive patterns Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-401789 ER - TY - THES A1 - Chujfi-La-Roche, Salim T1 - Human Cognition and natural Language Processing in the Digitally Mediated Environment N2 - Organizations continue to assemble and rely upon teams of remote workers as an essential element of their business strategy; however, knowledge processing is particular difficult in such isolated, largely digitally mediated settings. The great challenge for a knowledge-based organization lies not in how individuals should interact using technology but in how to achieve effective cooperation and knowledge exchange. Currently more attention has been paid to technology and the difficulties machines have processing natural language and less to studies of the human aspect—the influence of our own individual cognitive abilities and preferences on the processing of information when interacting online. This thesis draws on four scientific domains involved in the process of interpreting and processing massive, unstructured data—knowledge management, linguistics, cognitive science, and artificial intelligence—to build a model that offers a reliable way to address the ambiguous nature of language and improve workers’ digitally mediated interactions. Human communication can be discouragingly imprecise and is characterized by a strong linguistic ambiguity; this represents an enormous challenge for the computer analysis of natural language. In this thesis, I propose and develop a new data interpretation layer for the processing of natural language based on the human cognitive preferences of the conversants themselves. Such a semantic analysis merges information derived both from the content and from the associated social and individual contexts, as well as the social dynamics that emerge online. At the same time, assessment taxonomies are used to analyze online comportment at the individual and community level in order to successfully identify characteristics leading to greater effectiveness of communication. Measurement patterns for identifying effective methods of individual interaction with regard to individual cognitive and learning preferences are also evaluated; a novel Cyber-Cognitive Identity (CCI)—a perceptual profile of an individual’s cognitive and learning styles—is proposed. Accommodation of such cognitive preferences can greatly facilitate knowledge management in the geographically dispersed and collaborative digital environment. Use of the CCI is proposed for cognitively labeled Latent Dirichlet Allocation (CLLDA), a novel method for automatically labeling and clustering knowledge that does not rely solely on probabilistic methods, but rather on a fusion of machine learning algorithms and the cognitive identities of the associated individuals interacting in a digitally mediated environment. Advantages include: a greater perspicuity of dynamic and meaningful cognitive rules leading to greater tagging accuracy and a higher content portability at the sentence, document, and corpus level with respect to digital communication. N2 - Zunehmend bauen Organisationen Telearbeit als zentrales Element ihrer Geschäftsstrategie auf. Allerdings führt die Wissensverarbeitung in solchen digital vermittelnden -weitegehend aber nicht interaktiv strukturierten- Kontexten zu Schwierigkeiten. Dabei liegt die wesentliche Herausforderung für wissensbasierte Organisationen nicht in der Frage, wie Individuen mithilfe von Technologien zusammenarbeiten sollten, sondern darin, wie effektiv die Zusammenarbeit und ein effektiver Wissensaustausch zu erreichen sind. Gegenwärtige Untersuchungen fokussieren weit mehr auf Technologien selbst als auf den menschlichen Voraussetzungen von kognitiven Fähigkeiten und Präferenzen bei der online basierten Zusammenarbeit. Genauso ist der Umstand noch nicht hinreichend berücksichtigt worden, dass Natural Language Processing (NLP) den generellen Begleiterscheinungen von Sprache wie Missverständnissen und Mehrdeutigkeiten unterworfen ist. Diese Arbeit setzt auf vier wissenschaftlichen Feldern auf, die in der Verarbeitung und Interpretation von großen, teils unstrukturierten Datenmengen wesentlich sind: Wissensmanagement, Kognitionswissenschaft, Linguistik und Künstliche Intelligenz. Auf dieser breiten Grundlage wird ein Modell angeboten, das auf verlässliche Art, den nicht-deterministischen Charakter von Sprache betont und vor diesem Hintergrund Verbesserungspotentiale digital gestützter Zusammenarbeit aufzeigt. Menschliche Kommunikation kann entmutigend unpräzise sein und ist von linguistischer Mehrdeutigkeit geprägt. Dies bildet eine wesentliche Herausforderung für die computertechnische Analyse natürlicher Sprache. In dieser Arbeit entwickle ich unter Berücksichtigung kognitiver Präferenzen von Gesprächspartnern den Vorschlag für einen neuen Interpretationsansatz von Daten. Im Rahmen dieser semantischen Analyse werden Informationen zusammengeführt, die sowohl den zu vermittelnden Inhalt als auch die damit verbundenen sozialen und individuellen Kontexte, sowie die Gruppendynamik im Online-Umfeld einbeziehen. Gleichzeitig werden Bewertungstaxonomien verwendet, um das Online-Verhalten sowohl auf individueller wie gruppendynamischer Ebene zu analysieren, um darin Merkmale für eine größere Effektivität der Kommunikation zu identifizieren. Es werden Muster zur Identifizierung und Messung wirksamer Methoden der Interaktion in Hinblick auf individuelle kognitive und lernpsychologische Präferenzen bewertet. Hierzu wird der Begriff einer Cyber-Cognitive Identity (CCI) vorgeschlagen, der unterschiedliche Wahrnehmungsprofile kognitiver und lernpsychologischer Stile verschiedener Individuen beschreibt. Die Bezugnahme auf solche kognitiven Präferenzen kann das Wissensmanagement in geografisch verteilten, kollaborativen digitalen Umgebungen erheblich erleichtern und damit das Wissensaustausch verbessern. Cognitive Labeled Latent Dirichlet Allocation (CLLDA) wird als generatives Wahrscheinlichkeitsmodell für die automatische Kennzeichnung und Clusterbildung von CCI-gewonnenen Profilen verwendet. Dabei dominieren methodologisch die Kognitionstypen gegenüber den Wahrscheinlichkeitsaspekten. Mit der Einführung und Weiterverarbeitung des CCI-Begriffs wird der bisherige Forschungsstand um ein fundiertes Verfahrensmodell erweitert, das eine Grundlage für sich potentiell anschließende Forschungsarbeiten und praktische Anwendungen bietet. KW - cognitive science KW - natural language processing KW - knowledge management KW - thinking styles KW - artificial intelligence KW - Kognitionswissenschaft KW - Verarbeitung natürlicher Sprache KW - Wissensmanagement KW - Denkstile KW - künstliche Intelligenz Y1 - 2020 ER - TY - JOUR A1 - Chujfi-La-Roche, Salim A1 - Meinel, Christoph T1 - Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities JF - AI & society : the journal of human-centred systems and machine intelligence N2 - 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. KW - argumentation research KW - cyber humanistic KW - cognition KW - collaboration KW - knowledge building KW - knowledge management KW - teamwork KW - virtual groups Y1 - 2017 U6 - https://doi.org/10.1007/s00146-017-0780-x SN - 0951-5666 SN - 1435-5655 VL - 35 IS - 1 SP - 5 EP - 15 PB - Springer CY - New York ER - TY - JOUR A1 - Fischer, Caroline T1 - Incentives can’t buy me knowledge BT - the missing effects of appreciation and aligned performance appraisals on knowledge sharing of public employees JF - Review of public personnel administration N2 - This study examines whether incentives affect public employees' intention to share knowledge. Tested incentives satisfy needs for either achievement or appreciation. Both treatments were tested on implicit as well as explicit knowledge sharing. A 2 x 3 factorial survey experiment was designed to observe within-person and between-person effects. Data were collected from public employees in the core administration and healthcare sector (n = 623) in 2018. The analysis indicates that both treatments positively affect knowledge-sharing intention if it is explicit knowledge that ought to be shared. However, no effects of either treatment can be found in either type of knowledge sharing. No negative effect of the tested incentives on knowledge sharing was observed. Hence, incentives might not harm knowledge sharing but also do not pay off in organizational practice. In contrast to these motivation-enhancing human resource practices, ability and opportunity-enhancing practices should be tested to foster knowledge sharing. KW - knowledge sharing KW - knowledge management KW - work behavior KW - rewards KW - survey KW - experiment Y1 - 2021 U6 - https://doi.org/10.1177/0734371X20986839 SN - 0734-371X SN - 1552-759X VL - 42 IS - 2 SP - 368 EP - 389 PB - Sage CY - London ER - TY - THES A1 - Fischer, Caroline T1 - Knowledge Sharing in the Public Sector T1 - Wissensteilung im öffentlichen Sektor BT - How and why public employees share their knowledge at the workplace and how to foster that behavior? BT - Wie und warum teilen öffentlich Beschäftigte ihr Wissen am Arbeitsplatz und wie kann dieses Verhalten gefördert werden? N2 - This dissertation examines the activity of knowledge sharing by public employees in the workplace. Building on the Rubicon model of human behavior formation, I use a threefold approach to analyze the knowledge-sharing process: public employees’ motivation to share knowledge, their intention to share, and knowledge sharing behavior as such. The first article maps the knowledge-sharing behavior of public employees. It builds a typology of behavioral patterns and shows that public employees mainly share their knowledge responsively and directly with a knowledge receiver rather than an information medium. The second article elaborates on the construct of knowledge-sharing motivation and develops a scale to measure this kind of work motivation in a selective and domain-specific way. Data from three studies indicate three dimensions of knowledge-sharing motivation, namely appreciation, growth and altruism, and tangible rewards. Based on these dimensions, the third article analyzes whether the satisfaction of public employees’ underlying needs can foster ther knowledge-sharing intention. The study indicates that both tested treatments (appreciation by co-workers, benefits in a performance appraisal) positively affect knowledge-sharing intention if it is explicit knowledge that ought to be shared. However, no effects of either treatment can be found if implicit knowledge is shared. Hence, to foster sharing of explicit knowledge, the analyzed motivation-enhancing rewards can be used in public management practice. To enhance implicit knowledge sharing, ability- and opportunity-enhancing management instruments are discussed. All in all, this dissertation integrates a micro-level perspective on human knowledge sharing into a meso-level perspective on organizational knowledge management. It adds to the literature on workplace behaviors of public employees and knowledge management and aims to incorporate knowledge sharing and management into the public administration and management literature. N2 - Diese Dissertation beschäftigt sich mit der Wissensteilung von Mitarbeiter*innen der öffentlichen Verwaltung am Arbeitsplatz. Basierend auf dem Rubikon-Modell der menschlichen Verhaltensformierung nutze ich einen dreiteiligen Ansatz zur Analyse des Prozesses der Wissensteilung: die Motivation von Verwaltungsmitarbeiter*innen ihr Wissen zu teilen, ihre Intention zu teilen und das eigentliche Wissensteilverhalten. Der erste Artikel kartiert Wissensteilverhalten von Verwaltungsmitarbeiter*innen. Er erstellt eine Typologie von Verhaltensweisen und zeigt, dass Wissen vor allem auf Nachfrage und direkt mit Wissensnehmer*innen geteilt wird statt mit einem Trägermedium. Der zweite Artikel bearbeitet das Konstrukt der ‚Motivation Wissen zu teilen‘ und entwickelt eine Skala zur Messung dieser Art von Arbeitsmotivation, die bereichspezifisch ist und sich von Verhalten abgrenzt. Die Erhebungen zeigen drei Dimensionen der Motivation Wissen zu teilen auf: Anerkennung, Entwicklung und Altruismus, und materielle Belohnung. Auf Basis dieser Dimensionen, analysiert der dritte Artikel ob die Befriedigung der zugrundeliegenden Bedürfnisse die Intention von Verwaltungsmitarbeiter*innen Wissen zu teilen fördert. Beide getesteten Interventionen (kollegiale Anerkennung, Vorteil in Leistungsbewertung) erhöhen die Intention zu teilen wenn explizites Wissen geteilt werden soll. Soll implizites Wissen geteilt werden, zeigen beide Interventionen keine Effekte. Daher können die getesteten motivationsstärkenden Anreize genutzt werden um explizite Wissensteilung zu fördern. Zur Erhöhung impliziter Wissensteilung werden Managementinstrumente diskutiert, die individuelle Fähigkeiten stärken und Gelegenheiten zur Wissensteilung erhöhen. Alles in allem integriert diese Arbeit eine Mikrolevel-Perspektive menschlichen Verhaltens in eine Mesolevel-Perspektive auf organisationales Wissensmanagement. Sie trägt zur Literatur zum Arbeitsverhalten von Verwaltungsmitarbeiter*innen und zur Wissensmanagementliteratur bei and bringt das Thema der Wissensteilung in die verwaltungswissenschaftliche Literatur ein. KW - public management KW - knowledge sharing KW - knowledge management KW - knowledge sharing motivation KW - scale development KW - survey experiment KW - öffentliche BWL KW - Wissensteilung KW - Wissensmanagement KW - Motivation zur Wissensteilung KW - Skalenentwicklung KW - Survey-Experiment Y1 - 2020 ER - TY - CHAP A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Modeling the handling of knowledge for Industry 4.0 T2 - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings N2 - 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. KW - 4th industrial revolution KW - knowledge management KW - business process management Y1 - 2021 SN - 978-3-030-79975-5 SN - 978-3-030-79976-2 U6 - https://doi.org/10.1007/978-3-030-79976-2_12 VL - 422 SP - 207 EP - 223 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Gronau, Norbert T1 - Marktüberblick T1 - Applications and systems for knowledge management BT - Anwendungen und Systeme für das Wissensmanagement BT - a market survey N2 - 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. N2 - Applications and systems for knowledge management : a market survey: This market survey gives an overview on software for the support of knowledge management. The survey overlooks the span from specialized search engines to integrated knowledge management systems with a broad range of functions. The investigated software supports community-oriented approaches as well as information retrieval. Usage possibilities are as different as the heterogenous requirements of enterprises and organizations for knowledge management. Therefore a direct comparison between the investigated tools is not useful. ----- © GITO mbH Berlin KW - Wissensmanagement KW - Portal KW - Suchmaschine KW - Diskussion KW - Marktübersicht KW - Community KW - knowledge management KW - community KW - portal KW - search engine KW - discussion KW - market survey Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-6814 ER - TY - CHAP A1 - Grum, Marcus ED - Shishkov, Boris T1 - Managing human and artificial knowledge bearers BT - the creation of a symbiotic knowledge management approach T2 - Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings N2 - 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. KW - knowledge management KW - artificial intelligence KW - neuronal systems KW - design of knowledge-driven systems KW - symbiotic system design Y1 - 2020 SN - 978-3-030-52305-3 SN - 978-3-030-52306-0 U6 - https://doi.org/10.1007/978-3-030-52306-0_12 SP - 182 EP - 201 PB - Springer International Publishing AG CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Blunk, Oliver A1 - Rojahn, Marcel A1 - Fettke, Peter A1 - Gronau, Norbert T1 - Research challenges of knowledge modelling and the outline of a research agenda T2 - Knowledge in digital age : IFKAD 2020 KW - knowledge management KW - process modelling KW - research challenges Y1 - 2020 SN - 978-88-96687-13-0 SN - 2280-787X PB - The Arts of Business Institute CY - Matera, Italy ER - TY - CHAP A1 - Grum, Marcus A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Quantification of knowledge transfers BT - the design of an experiment setting for the examination of knowledge transfers T2 - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings N2 - 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. KW - knowledge management KW - knowledge transfer KW - conversion KW - empirical examination KW - experiment Y1 - 2021 SN - 978-3-030-79975-5 SN - 978-3-030-79976-2 U6 - https://doi.org/10.1007/978-3-030-79976-2_13 VL - 422 SP - 224 EP - 242 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Klippert, Monika A1 - Albers, Albert A1 - Gronau, Norbert A1 - Thim, Christof T1 - Examining the quality of knowledge transfers BT - the draft of an empirical research T2 - Proceedings of the Design Society N2 - Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers. KW - knowledge management KW - new product development KW - evaluation Y1 - 2021 U6 - https://doi.org/10.1017/pds.2021.404 SN - 2732-527X VL - 1 SP - 1431 EP - 1440 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Kluge, Annette A1 - Gronau, Norbert T1 - Intentional forgetting in organizations BT - the Importance of Eliminating Retrieval Cues for Implementing New Routines JF - Frontiers in psychology N2 - To cope with the already large, and ever increasing, amount of information stored in organizational memory, "forgetting," as an important human memory process, might be transferred to the organizational context. Especially in intentionally planned change processes (e.g., change management), forgetting is an important precondition to impede the recall of obsolete routines and adapt to new strategic objectives accompanied by new organizational routines. We first comprehensively review the literature on the need for organizational forgetting and particularly on accidental vs. intentional forgetting. We discuss the current state of the art of theory and empirical evidence on forgetting from cognitive psychology in order to infer mechanisms applicable to the organizational context. In this respect, we emphasize retrieval theories and the relevance of retrieval cues important for forgetting. Subsequently, we transfer the empirical evidence that the elimination of retrieval cues leads to faster forgetting to the forgetting of organizational routines, as routines are part of organizational memory. We then propose a classification of cues (context, sensory, business process-related cues) that are relevant in the forgetting of routines, and discuss a meta-cue called the "situational strength" cue, which is relevant if cues of an old and a new routine are present simultaneously. Based on the classification as business process-related cues (information, team, task, object cues), we propose mechanisms to accelerate forgetting by eliminating specific cues based on the empirical and theoretical state of the art. We conclude that in intentional organizational change processes, the elimination of cues to accelerate forgetting should be used in change management practices. KW - change management KW - multi-actor routines KW - business processes KW - knowledge management KW - organizational memory KW - situational strength Y1 - 2018 U6 - https://doi.org/10.3389/fpsyg.2018.00051 SN - 1664-1078 VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - GEN A1 - Kluge, Annette A1 - Gronau, Norbert T1 - Intentional forgetting in organizations BT - the importance of eliminating retrieval cues for implementing new routines T2 - Postprints der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - To cope with the already large, and ever increasing, amount of information stored in organizational memory, "forgetting," as an important human memory process, might be transferred to the organizational context. Especially in intentionally planned change processes (e.g., change management), forgetting is an important precondition to impede the recall of obsolete routines and adapt to new strategic objectives accompanied by new organizational routines. We first comprehensively review the literature on the need for organizational forgetting and particularly on accidental vs. intentional forgetting. We discuss the current state of the art of theory and empirical evidence on forgetting from cognitive psychology in order to infer mechanisms applicable to the organizational context. In this respect, we emphasize retrieval theories and the relevance of retrieval cues important for forgetting. Subsequently, we transfer the empirical evidence that the elimination of retrieval cues leads to faster forgetting to the forgetting of organizational routines, as routines are part of organizational memory. We then propose a classification of cues (context, sensory, business process-related cues) that are relevant in the forgetting of routines, and discuss a meta-cue called the "situational strength" cue, which is relevant if cues of an old and a new routine are present simultaneously. Based on the classification as business process-related cues (information, team, task, object cues), we propose mechanisms to accelerate forgetting by eliminating specific cues based on the empirical and theoretical state of the art. We conclude that in intentional organizational change processes, the elimination of cues to accelerate forgetting should be used in change management practices. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 127 KW - change management KW - multi-actor routines KW - business processes KW - knowledge management KW - organizational memory KW - situational strength Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-446022 SN - 1867-5808 IS - 127 ER - TY - CHAP A1 - Vladova, Gergana A1 - Ullrich, André A1 - Sultanow, Eldar A1 - Tobolla, Marinho A1 - Sebrak, Sebastian A1 - Czarnecki, Christian A1 - Brockmann, Carsten ED - Klein, Maike ED - Krupka, Daniel ED - Winter, Cornelia ED - Wohlgemuth, Volker T1 - Visual analytics for knowledge management BT - advantages for organizations and interorganizational teams T2 - Informatik 2023 N2 - 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. KW - knowledge management KW - visual analytics KW - knowledge transfer KW - teamwork KW - knowledge management system KW - tacit knowledge KW - explicit knowledge Y1 - 2023 SN - 978-3-88579-731-9 U6 - https://doi.org/10.18420/inf2023_187 SN - 1617-5468 SP - 1851 EP - 1870 PB - Gesellschaft für Informatik e.V. (GI) CY - Bonn ER - TY - THES A1 - von Kaphengst, Dragana T1 - Project’s management quality in development cooperation T1 - Managementqualität von Projekten in der Entwicklungszusammenarbeit N2 - 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. KW - development cooperation KW - project management quality KW - evaluation KW - GIZ KW - knowledge management KW - Entwicklungszusammenarbeit KW - Qualität des Projektmanagements KW - Evaluierung KW - GIZ KW - Wissensmanagement Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-430992 ER -