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on Knowledge Management and Knowledge Economy |
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Issue of 2025–09–01
four papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Philipp Hohn; Torben Klarl |
| Abstract: | This paper suggests a micro-founded growth theory of human capital that incorporates three important ingredients: i) learning in a knowledge network, ii) possible skill-down-grading due to knowledge obsolescence, and, iii) fear of technological unemployment due to automation. Heterogeneous agents (optimally) split their time between learning-by-exchanging knowledge or working in the final goods sector. On the aggregate level, our benchmark model shows that learning and the degree of connectivity within the knowledge network directly impact the growth rate of the economy. Moreover, we show the existence of a poverty trap in which society stagnates due to an insufficient level of human capital that is in particular governed by the degree of knowledge obsolescence. In an extension, we control for the fact that learning is a cognitively demanding task associated with learning errors due to cognitive constraints. Therefore, two groups of agents are distinguished: Cognitively constrained and rational optimizers, where both can switch endogenously between a low and high-skilled state. We use this extension to numerically quantify the effects of cognitive constraints on human capital inequality. Inter alia, we show that a knowledge obsolescence shock has transitional as well as long-run negative effects on human capital inequality, where in relative terms, cognitively constrained agents are more affected than their rational counterparts. |
| Keywords: | Human capital, innovation, inequality, automation, knowledge network |
| JEL: | O11 O33 O40 E23 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:atv:wpaper:2503 |
| By: | Serguey Braguinsky; Joonkyu Choi; Yuheng Ding; Karam Jo; Seula Kim |
| Abstract: | We provide evidence that mega firms have played an increasingly important role in shaping new technological trajectories in recent years. While the share of novel patents---defined as patents introducing new combinations of technological components---produced by mega firms declined until around 2000, it has rebounded sharply since then. Furthermore, we find that the technological impact and knowledge diffusion of novel patents by mega firms have grown relative to those by non-mega firms after 2001. We also explore potential drivers of this trend, presenting evidence that the rise in novel patenting by mega firms is tied to their disproportionate increase in cash holdings and the expansion of their technological scope. Our findings highlight an overlooked positive role of mega firms in the economywide innovation process. |
| Keywords: | Mega Firms; Innovation; Novel Patents; Knowledge Diffusion |
| JEL: | O31 O33 O34 L11 L25 |
| Date: | 2025–08–06 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-60 |
| By: | Jackson, Emerson Abraham |
| Abstract: | Artificial Intelligence (AI) is transforming the way individuals engage with information, especially in educational environments where there is an increasing need for tailored, scalable, and effective learning models. This study offers a thorough evaluation of the changing impact of AI on knowledge acquisition, emphasising learners’ adaptability, engagement, and performance. This paper employs a mixed-methods approach with a carefully selected sample size of 150 participants from various academic institutions and learning environments to assess the effectiveness, challenges, and equity dimensions of AI-enabled educational tools. The findings indicate significant enhancements in understanding and memory retention among users of AI platforms, while also highlighting inequalities in access and the necessity for responsible implementation. The research provides practical policy recommendations to facilitate the sustainable integration of AI in knowledge delivery systems. |
| Keywords: | Artificial Intelligence, Knowledge Acquisition, Digital Pedagogy, Personalised Learning, Cognitive Enhancement |
| JEL: | C38 D83 I21 O33 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125529 |
| By: | Reynolds, Robert Wallace |
| Abstract: | This paper proposes the Dual-Track Universal Framework (DTUF), a two-path architecture designed to address both existential economic security and entrepreneurial opportunity in the age of AI displacement and innovation asymmetry. DTUF consists of a dignity-linked base income tied to community service and a participation-linked innovation currency that democratizes access to professional services and startup resources. Unlike traditional Universal Basic Income proposals, DTUF preserves human agency through meaningful contribution while creating systematic pathways for innovation regardless of initial wealth. The framework leverages existing institutional structures, from Small Business Administration categorizations to professional licensing requirements, to create a parallel economy that coexists with current systems rather than replacing them wholesale. Through theoretical modeling and comparative analysis, I demonstrate how DTUF addresses key limitations of existing UBI proposals while mitigating the innovation access gaps that perpetuate wealth concentration in knowledge economies. |
| Date: | 2025–07–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:jdwqn_v1 |