|
on Knowledge Management and Knowledge Economy |
|
Issue of 2025–03–10
four papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Alain Berger (Ardans SAS - Ardans SAS); Patrick Prieur (Ardans SAS - Ardans SAS) |
| Abstract: | In 2024, the B2V Memory Observatory® took up the issue of "corporate memory" and launched concrete actions to bring this subject to the forefront of management. Prof. JeanGabriel Ganascia, a member of the Scientific Advisory Board, invited us to shed light on the subject, based on our industrial vision of current approaches and the contribution of artificial intelligence to KM: "How can we position Knowledge Management in this reflection on Corporate Memory? In the first part of the article, we present the pioneering, singular and exemplary approach of the Commissariat à l'Énergie Atomique et aux Énergies Alternatives. The second part looks at the arrival of the ISO30401 standard and the expected requirements for SKMs or "Knowledge Management Systems". The already significant contribution of Artificial Intelligence and the arrival of major language models are discussed, with the necessary industrial limits of caution. The author's conviction is clear: KM is a strategic key to addressing the the subject of "Corporate Memory |
| Abstract: | En 2024, l'Observatoire B2V des Mémoires ® s'est emparé de la question de la « mémoire de l'entreprise » et a lancé des actions concrètes pour pointer ce sujet dans les sphères managériales. Membre de son Conseil Scientifique, le Pr Jean-Gabriel Ganascia nous a invités à éclairer cette réflexion par notre vision industrielle des démarches en cours et de l'apport de l'Intelligence Artificielle (IA) dans le Management de la Connaissance (KM), la question étant ainsi formulée : « Comment positionner le « Management de la Connaissance » dans cette réflexion à propos de la « Mémoire d'Entreprise »? » L'article présente dans une première partie la démarche considérée comme pionnière, singulière et exemplaire du Commissariat à l'Énergie Atomique et aux Énergies Alternatives. Dans un deuxième temps, l'article présente un regard sur l'arrivée de la norme ISO30401 et les exigences attendues sur les « Systèmes de Management de la Connaissance » (SKM). La contribution de l'IA déjà significative et la venue sur les grands modèles de langage sont abordés avec la prudence industrielle qui s'impose. La conviction des auteurs est claire : le KM est une clé stratégique pour adresser le sujet de la « Mémoire d'Entreprise ». |
| Keywords: | Corporate Memory, Knowledge Management, Knowledge Capitalisation &, amp, Exploitation, Artificial Intelligence, Key knowledge, Crucial knowledge, ISO30401, Knowledge Engineering, Expert Knowledge Transfer, Knowledge Management System, Intelligence Artificielle, Capitalisation et Exploitation des connaissances, PARNASSE, KB_ Scope ®, Observatoire B2V des Mémoires ®, COGNICOACH, Large Language Models, Système de management de la connaissance |
| Date: | 2025–01–28 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04931322 |
| By: | Oliver, James |
| Abstract: | Universities, once citadels of scarce knowledge, now sell status credentials. This paper argues academia clings to relevance by gatekeeping status through degrees—a model rendered obsolete by the printing press, internet, and AI. Historical resistance to disruptive ideas (germ theory, plate tectonics) mirrors modern reluctance to adopt open-access education and skill-based certification. Soaring student debt and peer-reviewed orthodoxy reveal a system prioritizing self-preservation over progress. To survive, academia must decentralize, leveraging AI-driven learning and validating competence via output, not diplomas. Without reform, universities risk obsolescence in an era where knowledge transcends ivory towers. |
| Date: | 2025–02–02 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:wzq2b_v1 |
| By: | Feiter, Tim Johannes |
| Abstract: | In times of digitalization and the democratization of information, individuals face information overload, misinformation, and missing orientation. Considering the corporate word, the question occurs, how individuals can create value through creative behavior considering the information flood. Therefore, this dissertation investigates the processes behind knowledge generation and the role of social interactions in fostering individual creativity, with a specific focus on innovation within organizations. Drawing on a multidisciplinary approach, the research explores three critical perspectives: network structures, the dynamic process of knowledge exchange, and the application of natural language processing (NLP) for identifying creative contributions. The first research question focuses on how knowledge and social network structures jointly enable future learning and innovation. The findings highlight that knowledge network saturation plays a significant role in creative behavior, particularly in determining the balance between explorative and exploitative search activities. This interaction between knowledge and social networks, where both can compensate for each other, offers a nuanced understanding of how organizations can leverage social dynamics and knowledge structures to stimulate creativity. The second research question examines the impact of knowledge exchange on innovative behavior throughout the idea journey. Through an analysis of online communities, this research demonstrates that changes in individual interests over time are critical to fostering creativity. The dissertation identifies key temporal patterns that enhance the likelihood of creative outcomes, emphasizing the importance of managing both knowledge diversity and depth during the ideation process. The third research question explores the potential of advanced NLP techniques to automatically identify creative behavior from textual data. The research proposes a transfer learning methodology that demonstrates superior accuracy compared to traditional methods, offering a scalable solution for organizations seeking to evaluate large volumes of idea descriptions. This novel approach opens new avenues for utilizing artificial intelligence in innovation management. Overall, the dissertation contributes to innovation literature by providing theoretical and practical insights into knowledge generation processes, social networks, and AI-driven creativity assessment. These findings offer actionable strategies for organizations to cultivate environments that support creative individuals, enabling them to navigate the complexities of knowledge recombination and social interaction for successful innovation in times of information overload. |
| Date: | 2025–02–26 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:153302 |
| By: | Rama, Martin G.; Singh, Rucheta; Aslam, Aiza |
| Abstract: | The World Bank’s analytical work has a strong reputation, but its knowledge products are also perceived to be of varying quality and relevance, and the drivers of this heterogeneity are only partially understood. Building on previous evaluations, this paper adopts a production function approach to assess how budget resources, time to completion, technical skills, and institutional responsibilities affect the internal ratings and external visibility of different types of analytical tasks at the World Bank. To this effect, the paper first matches records from three unconnected electronic platforms — for internal documents, budget codes, and external publications — to assemble a comprehensive database of knowledge products and their key characteristics. With analytical documents as its unit of observation, the exercise shows that: (1) devoting more resources to analytical tasks leads to both better ratings and greater visibility; (2) both outcomes are systematically worse when a greater share of resources comes from trust funds; (3) they are also consistently worse for tasks that take longer to complete; (4) more academically oriented team leaders underperform on ratings and overperform on visibility, whereas technically solid but less stellar team leaders overperform on ratings; and (5) everything else equal, performance varies systematically with the nature of the unit in charge. The findings of the paper can be read as a cautionary note against knowledge management that is based on the counting of analytical tasks. Instead, the findings call for much stronger information systems on knowledge products, a better alignment of incentives for the units in charge, and regular evaluations in the spirit of this paper. |
| Date: | 2024–02–14 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:10704 |