|
on Knowledge Management and Knowledge Economy |
|
Issue of 2026–03–02
eight papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Katharina Brennig (first name last name) (Paderborn University); Christian Bartelheimer (first name last name) (Georg-August-Universität Göttingen); Bernd Löhr (first name last name) (Paderborn University); Daniel Beverungen (first name last name) (Paderborn University); Oliver Müller (first name last name) (Paderborn University) |
| Abstract: | Knowledge-intensive processes (KIPs) are strategic core processes that drive organizational value creation and competitive advantage. Despite their strategic importance, KIPs are predominantly managed manually, as existing classes of IT systems either lack process awareness or struggle with the complexity and unpredictability of KIPs. We present findings from a 39-month Action Design Research (ADR) project to conceptualize a new class of IT artifacts that enables process mining of KIPs. This class of IT artifacts integrates richer process-related information, facilitating knowledge transfer by allowing process participants to learn from similar process instances and engage in socialization at run-time. Our research bridges critical gaps between business process management (BPM) and knowledge management, offering theoretical and managerial insights. We propose five theory-ingrained design principles that guide the development of process mining systems for KIPs and examine their role in fostering knowledge creation within organizations, ultimately upgrading strategic decision-making and organizational performance. (abstract of the paper) |
| Keywords: | Business Process Management, Process Mining, Knowledge-Intensive Processes, Organizational Knowledge Creation, Action Design Research (keywords) |
| URL: | https://d.repec.org/n?u=RePEc:pdn:dispap:166 |
| By: | Ernest Miguelez; Michele Pezzoni; Fabiana Visentin; Catalina Martínez; Reinhilde Veugelers; Julio Raffo |
| Abstract: | This paper examines the evolving geography of international technological knowledge diffusion over the last four decades using multiple patent-based indicators. We first review the main mechanisms through which knowledge diffuses across borders—including trade and global value chains, foreign direct investment, skilled migration, global science, and markets for technology—highlighting their complementarities and the role of domestic capabilities. We then provide new empirical evidence based on cross-border patent citations, technological trajectories defined by IPC recombinations, patent-to-science linkages, and international patent families. The results reveal persistent asymmetries, with a small group of advanced economies remaining central knowledge hubs, alongside the rising role of emerging countries, especially China. Science-based technologies diffuse farther and faster, while capability constraints continue to limit integration for many regions. |
| Keywords: | Technological knowledge diffusion, Geography, Patents, Citations, Technological trajectories, Science, Patent families |
| JEL: | O34 O33 F14 F23 R12 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:wip:wpaper:92 |
| By: | Andrea L. Eisfeldt; Barney Hartman-Glaser; Edward T. Kim; Ki Beom Lee |
| Abstract: | We develop a text-based measure of intangible investment intensity derived from firms’ 10-K filings, and offer a general methodology for semantic theme scoring (STS). Our approach further classifies disclosure text into knowledge, customer, and organization capital. Firms with high intangible intensity are smaller, younger, and invest heavily in R&D and human capital. The three subcomponents map cleanly to distinct economic firm types: knowledge-intensive firms are R&D-driven with high valuations and skilled labor; customer-intensive firms are mature, profitable, and commercially oriented; and organization-intensive firms are large, asset-heavy incumbents. Managerial expenditure descriptions thus provide informative signals about intangible investment, complementing financial statements in capturing corporate capital stocks. |
| JEL: | A0 C0 E0 E01 G0 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34882 |
| By: | Fabiano Compagnucci (Gran Sasso Science Institute); Daria Denti (Gran Sasso Science Institute); Alessandra Faggian (Gran Sasso Science Institute); Arsène Perrot (Gran Sasso Science Institute) |
| Abstract: | The green transition unfolds against a backdrop of widening territorial inequalities driven by the spatial concentration of the knowledge economy. While knowledge-intensive regions with educated, affluent populations might be expected to champion environmental causes, this paper reveals a counter-intuitive pattern. Using novel measures of pro- and anti-environmental activism across Italian provinces (2012-2022) and a Bartik-like instrumental variable, we find that knowledge economy concentration reduces pro-environmental activism nearly twice as much as anti-environmental activism. This asymmetry creates a compositional shift where knowledge-intensive areas exhibit relatively more anti-environmental sentiment in their remaining activism. The findings challenge simplified assumptions about education, affluence, and environmental support, revealing that territorial economic structures fundamentally alter engagement patterns. Green transition policies must account for how different economic contexts generate distinct mobilization patterns, addressing both the reduced collective action in knowledge hubs and resistance in vulnerable territories. |
| Keywords: | green transition, climate crisis, local resentment, knowledge economy, activism, polarisation, local vulnerability |
| JEL: | R11 R12 Q54 Q58 D74 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:ahy:wpaper:wp75 |
| By: | Ville Korpela (Turku School of Economics, University of Turku, Finland); Eero Mäkynen (Turku School of Economics, University of Turku, Finland) |
| Abstract: | Business dynamism has been slowing globally over the last several decades. In a recent study, Akcigit and Ates (2023) examine the relative importance of different channels behind this development and highlight weakened knowledge diffusion from the technology frontier to followers as a dominant force.1 Their study also suggests that diffusion may weaken endogenously as the technology gap widens and market power accumulates, raising the question of how innovation policy can strengthen diffusion without reducing welfare. In this paper we study leader-to-follower licensing as a policy-relevant diffusion margin, and evaluate licensing subsidies relative to direct R&D subsidies. We develop an endogenous-growth general equilibrium model in which firms compete in prices and invest in R&D; the technology leader endogenously chooses whether to license to the follower, trading off higher static profits against faster follower catch-up through knowledge diffusion. We calibrate the model to Finnish data from 2014–2019. Our first exercise evaluates whether allowing licensing is desirable by shutting down the licensing channel in the calibrated economy. In the Finnish benchmark, shutting down licensing lowers growth but increases consumption-equivalent welfare, because the level effects of reduced concentration dominate the diffusion benefits of licensing. We then vary the diffusion rate through licensing and product substitutability to characterize when licensing becomes welfare-improving. In that region, solving the policymaker’s problem shows a non-trivial interaction: higher R&D subsidies can reduce equilibrium licensing by moving leaders more quickly into the monopoly-pricing states where licensing is privately unattractive, so the optimal policy mix augments R&D support with a non-negligible licensing subsidy to sustain diffusion. |
| Keywords: | Antitrust Policy, Business Dynamism, Endogenous Growth, Innovation Policy, Licensing, Technology Diffusion |
| JEL: | E22 L10 L41 O33 O34 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:tkk:dpaper:dp174 |
| By: | Andrea Guccione; Pau Roldan-Blanco |
| Abstract: | Firms' innovation outcomes depend on their ability to attract and retain talented inventors. What market frictions prevent the sorting between firms with high innovation potential and high-productivity inventors? How does this sorting impact aggregate innovation, growth and welfare? We address these questions both empirically and theoretically. Empirically, we show that firms facing strong competition in the product market employ more productive inventors, while less productive inventors tend to be allocated in concentrated industries. Theoretically, we embed a frictional labor market for inventors into an endogenous-growth model of strategic innovation. In line with the data, the model predicts that high-productivity inventors are disproportionately employed in firms that operate in competitive industries. We then use the model to quantify the growth and welfare implications of this inventor sorting. Our results show that matching frictions in the market for inventors impede the allocation of high- productivity inventors to firms with high implementation intensity, and are responsible for a 32% loss in economic growth. Industrial policies that subsidize R&D spending relax these frictions by boosting inventor productivity, helping high-quality inventors reallocate to firms with high implementation incentives. Under optimal subsidies, growth increases as much as 74 basis points, closing most of the gap in missing growth caused by frictions in the market for inventors. |
| Keywords: | innovation, inventors, R&D productivity, search |
| JEL: | L16 J6 O3 O4 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1562 |
| By: | Alice Guittard (ICRE8); Isabelle La Jeunesse; Ebun Akinsete (ICRE8); Maria Tziva; Ana Lorena Barrueto Munoz; Alicia Blanchi-Sic; Alexandra Spyropoulou; Phoebe Koundouri |
| Abstract: | Climate change impacts in Europe are accelerating, creating urgent adaptation needs across diverse local contexts. This paper presents the implementation of a Systems Innovation Approach (SIA) through living labs to co-design climate resilience strategies in nine European case studies. SIA provides a structured, participatory framework for systemic change through a stepwise approach enabling the development of tailor-made sustainability strategies by co-designing a portfolio of short, mid, and long-term innovative solutions. Living labs can successfully support open innovation ecosystems by enabling knowledge exchange, trust-building, and co-creation of tailored innovation pathways for adaptation. Results demonstrate that through the SIA, living lab can enhance stakeholder networks and capacity building, co-create knowledge and mutual understanding across a diversity of stakeholders while fostering actionable strategies. However, challenges remain regarding sustaining living labs beyond project funding, maintaining engagement, and bridging planning-to-implementation gaps. The paper concludes with recommendations for institutionalizing living labs within governance frameworks to accelerate Europe's transition toward climate resilience. |
| Keywords: | Living Lab, System Innovation Approach, Climate Change Adaptation, Stakeholder Engagement, System Thinking |
| Date: | 2026–02–19 |
| URL: | https://d.repec.org/n?u=RePEc:aue:wpaper:2605 |
| By: | Yanlong Wang; Jian Xu; Hongkang Zhang; Shao-Lun Huang; Danny Dongning Sun; Xiao-Ping Zhang |
| Abstract: | Formulaic alpha factor mining is a critical yet challenging task in quantitative investment, characterized by a vast search space and the need for domain-informed, interpretable signals. However, finding novel signals becomes increasingly difficult as the library grows due to high redundancy. We propose FactorMiner, a lightweight and flexible self-evolving agent framework designed to navigate this complex landscape through continuous knowledge accumulation. FactorMiner combines a Modular Skill Architecture that encapsulates systematic financial evaluation into executable tools with a structured Experience Memory that distills historical mining trials into actionable insights (successful patterns and failure constraints). By instantiating the Ralph Loop paradigm -- retrieve, generate, evaluate, and distill -- FactorMiner iteratively uses memory priors to guide exploration, reducing redundant search while focusing on promising directions. Experiments on multiple datasets across different assets and Markets show that FactorMiner constructs a diverse library of high-quality factors with competitive performance, while maintaining low redundancy among factors as the library scales. Overall, FactorMiner provides a practical approach to scalable discovery of interpretable formulaic alpha factors under the "Correlation Red Sea" constraint. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.14670 |