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on Knowledge Management and Knowledge Economy |
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Issue of 2026–05–25
eight papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Bartelsman, Eric J.; Dobbelaere, Sabien; Zona Mattioli, Alessandro |
| Abstract: | This paper develops a micro-founded framework linking price-cost and wage markups to intangible assets. Intangible assets, once created, are a source of firm rents. Owing to limits to enforceable ownership and the non-rival nature of knowledge, these rents can be both retained by the origin firm and transferred to a competitor through poaching of workers. Search and matching frictions affect labor mobility and result in bargaining over rents between the firm and the worker. This environment generates hold-up in intangible asset creation and motivates rent sharing. Under non-compete agreements, poached workers face start delays that weaken outside options. Using microdata from the Netherlands, we document higher price-cost and wage markups in more intangible-intensive firms and lower wages for workers with non-compete agreements, consistent with the model. |
| Keywords: | intangibles, non-compete agreements, price-cost markups, rent sharing, wage markups |
| JEL: | J41 L10 O30 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iwhdps:341089 |
| By: | Julien Baillet (CEA/DAM - CEA/DAM [Arpajon] - DAM - Direction des Applications Militaires - CEA - Commissariat à l'énergie atomique et aux énergies alternatives); Benoît Le Blanc (COGNITIQUE - IMS - Laboratoire de l'intégration, du matériau au système - UB - Université de Bordeaux - Institut Polytechnique de Bordeaux - CNRS - Centre National de la Recherche Scientifique, ENSC - Ecole Nationale Supérieure de Cognitique - Institut Polytechnique de Bordeaux); Olivier Musseau (CEA/DAM - CEA/DAM [Arpajon] - DAM - Direction des Applications Militaires - CEA - Commissariat à l'énergie atomique et aux énergies alternatives); Alban Peleszko (IOGA - IOGA) |
| Abstract: | Intelligence artificielle pour la gestion des connaissances : quels risques et opportunités pour les organisations ? Résumé Comme beaucoup d'autres domaines professionnels, la gestion des connaissances au sein des organisations est aujourd'hui bousculée par le développement rapide de l'intelligence artificielle et notamment des IA génératives qui enflamment l'actualité. Après avoir positionné d'une part les différents types de connaissance qu'un knowledge manager est amené à gérer dans une grande entreprise, et avoir exposé d'autre part les grands principes de l'IA générative, nous proposons deux cas d'usage. Le premier tire profit de l'IA pour une chaîne de traitement visant à exploiter la base de connaissances de l'entreprise. Le second met à contribution l'IA pour la capitalisation des savoirs d'un expert. A travers le détail de ces deux réalisations nous montrons comment l'IA vient ouvrir de nouvelles perspectives pour les méthodes de gestion des connaissances. |
| Keywords: | Intelligence artificielle, Knowledge management KM |
| Date: | 2024–05–29 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05612778 |
| By: | DiMaria, charles-henri |
| Abstract: | This document examines how three structural megatrends—the expansion of services, the diffusion of ICT, and deepening globalization - have reshaped the production structure and, by extension, the measurement of productivity in advanced economies. It argues that classical growth‑accounting approaches, rooted in Solow (1957), under‑state performance in knowledge‑based systems because they insufficiently capture the contribution of intangible assets. Using experimental macroeconomic estimates of intangibles from EUKLEMS–INTANProd applied to Luxembourg and a set of comparator economies (US and EU peers), the analysis shows that including intangibles raises the level of value added per hour and modestly alters growth rankings, with Luxembourg’s post‑2007 decline turning into a slight positive trend—yet still falling short of its pre‑2007 trajectory. While measurement constraints and data comparability issues remain, the results align more closely with a knowledge‑based economy narrative and provide a practical foundation for improving productivity metrics going forward. |
| Keywords: | intangible assets; productivity measurement; EUKLEMS–INTANProd; knowledge‑based economy. |
| JEL: | O4 O40 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129021 |
| By: | Sunil Kanwar (Department of Economics, Delhi School of Economics, University of Delhi) |
| Abstract: | Estimating a varying coefficients specification using an unbalanced panel of countries spanning the period 1997-2023, we find unambiguous support for the contention that educational attainment has a positive influence on innovation. The estimation results reveal that a one-year increase in mean years of education increases aggregate patent applications of a sample country by 1107, at the 50th percentile of the knowledge capital stock, or about 3.8% of the sample mean patent applications. Second, the innovation response to changes in education becomes stronger in the presence of larger stocks of knowledge capital. Thus, at the 95th percentile of the knowledge capital stock, we find that a one-year increase in the education level raises aggregate patent applications by 1264, or about 4.4% of the sample mean patent applications. This response to a unit-increase in the treatment variable is about 14.2% larger than what we found at the 50th percentile of the stock of knowledge capital, exemplifying the strengthening response at higher levels of the knowledge capital stock. Third, we find that the overall innovation-education response does not hinge upon any individual sector, but rather obtains across all the technology-intensive industry groups, namely, Chemicals, Electricals and Electronics, Machinery (non-electrical), Pharmaceuticals, and Professional and Scientific Equipment. Our results are robust to a number of sensitivity checks. |
| Keywords: | Innovation, Education, Heterogeneity, Technology groups JEL codes: O34, O38, O43 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cde:cdewps:362 |
| By: | Kox, Henk L.M. |
| Abstract: | Gravity models of foreign direct investment (FDI) have until now been based on the attraction power each country's market size. This paper presents and test a new structural gravity model that explains international FDI patterns from two separate attractors, market size and national knowledge characteristics. The model allows to separate and measure the gravity push and pull forces per country pair. The model is tested using a data panel with 150 indicators for firm-based and public knowledge activities, and bilateral FDI for about 200 jurisdictions over the full period 2001-2022. We find that knowledge-based comparative advantages have a separate impact on bilateral FDI, alongside the impact of market size. The impacts differ between partner countries, quantitatively and qualitatively (type of national knowledge assets). Knowledge factors often have a stronger impact than a country's gross domestic product. We have subjected these results that are new to the literature to severe robustness tests, but the results remain standing. The FDI Knowledge-Enriched Gravity (FKEG) model can become a powerful new tool for international economics. |
| Keywords: | knowledge-enriched structural gravity model; foreign direct investment; proprietary knowledge; gravity push and pull factors; Multilateral resistance terms; empirical test. |
| JEL: | C33 F21 F23 H41 O3 O34 |
| Date: | 2026–04–30 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129069 |
| By: | Kyu Yub Lee (KOREA INSTITUTE FOR INTERNATIONAL ECONOMIC POLICY (KIEP)) |
| Abstract: | This paper introduces a newly developed model that examines the interplay between trade, growth, and digital data, emphasizing data’s dual role as both a driver of growth and a source of privacy concerns. Departing from existing trade and growth models that have largely overlooked digital data’s unique characteristics, this paper provides the first comprehensive analysis of how data influences growth through data flows and knowledge diffusion, while simultaneously introducing associated privacy trade-offs.<p> A key novelty of this model lies in its clear distinction between digital data and traditional “ideas.” Both concepts share the characteristics of non-rivalry and stocklike accumulation, meaning they are cumulative and can be used by multiple entities with negligible additional cost. However, ideas are generally understood to produce only positive externalities, whereas digital data uniquely generates both positive and negative externalities simultaneously, including privacy and cybersecurity concerns for consumers.<p> The model is built within a dynamic general equilibrium framework that incorporates international trade and endogenous technological change, extending the work of Rivera-Batiz and Romer (1991) by integrating the evolution of digital data. Consumption activities, both domestic and a portion of foreign consumption, actively contribute to a country’s evolving data stock. This generated data then acts as a negative externality in the utility function of privacy-conscious consumers, reducing their welfare, even as it serves as a primary input for the R&D sector, fueling the growth engine.<p> Key findings from this new model highlight significant impacts: First, (economic growth) the model shows that unrestricted cross-border data flows are a significant stimulant for economic growth. This positive effect is further magnified by stronger knowledge spillovers and an increased number of trading partners. Conversely, stricter restrictions on data flows directly impede economic growth. The paper notes that trade liberalization alone, without the diffusion of ideas or data flows, only generates a level effect and does not affect long-term economic growth.<p> Second, (trade-off with individual welfare) another central finding is the inherent trade-off between economic growth and individual welfare. While open data flows promote economic expansion, they simultaneously intensify privacy concerns, leading to a reduction in individual welfare. This conflict is particularly pronounced in scenarios with limited or inefficient knowledge diffusion. Conversely, the model indicates that stricter data regulations, while hindering growth, can enhance individual welfare by mitigating these privacy risks. To navigate the identified trade-off between growth and privacy, the paper advocates against data localization and strongly supports the implementation of deep digital trade agreements. These agreements are proposed as crucial mechanisms to facilitate freer data flows and knowledge sharing, thereby mitigating the inherent conflict and unlocking the full potential of the digital economy. |
| Keywords: | digital data; privacy; trade; endogenous growth; welfare |
| JEL: | D33 E00 J23 O41 |
| Date: | 2025–11–07 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kiepwp:022487 |
| By: | Hinh T. Dinh |
| Abstract: | This paper is the second in a series examining services-led development and global value chain (GVC) integration in the Global South. It applies a three-category analytical framework covering knowledge services (ICT and professional business services), enabling services (transport, logistics, and finance), and local services (retail, hospitality, health, and personal services), to OECD Trade in Value Added indicators. The paper thus provides a structural assessment of Morocco's services sector over 2012–2022, benchmarked against the EU15. Morocco emerges as the most structurally advanced of the three North African economies examined in this series. Its computer programming and IT services sub-sector has achieved a degree of international market orientation that is the highest in the regional sample and broadly comparable to EU15 levels. This reflects the Casablanca nearshore ecosystem's deep integration with European client markets. Professional and technical services show the most dynamic trajectory in the regional dataset; forward integration into international markets rose steadily and substantially over the decade. The administrative and support services sector stands out for combining strong domestic supply chain embedding with growing international orientation simultaneously, a dual character that makes it the most structurally versatile knowledge services sub-sector in the study. Enabling services, anchored by the Tanger Med port complex, exhibit authentic GVC integration through deep assembly-and-re-export operations, with import content growing markedly over time. The paper further shows that Morocco's most competitive knowledge services sub-sectors—computer programming, professional services, and administrative services—have reached or exceeded EU15 levels of bilateral GVC embeddedness measured by both input sourcing and upstream positioning, making Morocco the only economy in the North African dataset that has crossed this threshold. The central conclusion is that Morocco's structural challenge is scale rather than quality. Morocco’s leading knowledge services sub-sectors are internationally competitive but collectively too small to generate the spillovers and employment effects that self-reinforcing convergence requires. The big-push logic of this series' Framework Paper applies directly: Morocco possesses the quality foundations of a knowledge economy but has not yet reached the critical mass at which knowledge services spillovers become self-sustaining. The evidence supports a structural policy agenda of deliberate scaling of IT and professional services, combined with containment of a rising public administration share, which risks crowding out productive investment. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:ocp:rpaeco:rp04_26 |
| By: | Tomita, Kengo (Shimizu Corporation) |
| Abstract: | This article operationalizes the concept of a delegation legitimacy boundary — the structural line along which human judgment can and cannot be legitimately delegated to artificial intelligence — and proposes a minimal scoring protocol for locating it within any knowledge-work task. Building on the Mekiki framework (Tomita 2026), which distinguished specification — the task-defining substrate of domain expertise — from externalization cost — the technical barrier that AI selectively removes — the present article derives a further decomposition within specification itself. Drawing on case-study evidence in which recorded specification judgments contain separable factual components (Sein-type: what the data structure affords, how users will perceive a display) and value-laden components (Sollen-type: what information ought to be excluded, which priority ranking is appropriate), the article grounds this distinction in Hume’s is–ought separation and Kant’s Sein/Sollen architecture, and redeploys it as the axis of a cognitive assay — a measurement system in which philosophical categories serve not as normative prescriptions but as diagnostic coordinates. The resulting five-step scoring protocol assigns Sein-type components to AI evaluation and Sollen-type components to domain-expert evaluation; this asymmetry is not a design choice but a structural consequence of the boundary itself, which holds as long as legitimacy over value judgments remains institutionally human-attributed. Most individual judgments are hybrid, carrying both components in varying ratios; the protocol therefore yields ratio profiles rather than binary classifications. As a first application, the article re-describes the four processes of Nonaka and Takeuchi’s Socialization–Externalization–Combination–Internalization (SECI) model through the assay, deriving as an analytic consequence the finding that AI acceleration of Externalization and Combination shifts the effective rate-limiting stage to Socialization and Internalization — both human-limited cognitive and social processes that cannot be accelerated by AI investment alone. |
| Date: | 2026–05–15 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:e9qw5_v1 |