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on Knowledge Management and Knowledge Economy |
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Issue of 2024‒07‒15
three papers chosen by Laura Nicola-Gavrila, Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Robin Cowan; Nicolas Jonard |
| Abstract: | This paper develops a simple model of academic research to analyse knowledge flows within a research system, when demand for multi-disciplinarity varies. Scientists are embedded in departments, linked to all others in the department, as well as to a small number of others outside the department. Pairs of scientists collaborate to produce ‘papers’. They can collaborate successfully with their direct links provided the distances in knowledge space between partners are within specified upper and lower bounds. By creating new knowledge, co-authors converge in their knowledge endowments, and the distance between them can fall below the lower bound. This is mitigated in two ways: extra-departmental links; and an intermittent job market in which scientists can change departments. In a simulation model we find that increasing the extent of extra-departmental links, and increasing job market activity both improve aggregate knowledge production. These two modes of knowledge diffusion are, however, substitutes rather than complements: increasing both does not improve performance over increasing only one. In addition, we find that increasing demands for multi-disciplinarity (essentially increasing the lower bound on knowledge distance for effective collaboration) generally decreases knowledge production. |
| Keywords: | economics of science; multi-disciplinarity; academic labour mobility; knowledge production. |
| JEL: | I23 I28 O39 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-21&r= |
| By: | Robin Cowan; Nicolas Jonard; Ruth Samson |
| Abstract: | Many scholars observed changes in the intellectual property rights systems in the 1980s and 1990s throughout the world. Patent systems in particular seemed to be expanding their scope, and the legal system seemed to be changing its attitudes towards intellectual property rights. At the same time, and probably in response, firms started to change their patenting behaviour — treating patents as tools of competition and bargaining rather than as a means to protect the fruits of intellectual labour. In this paper we present a simulation model that can be used to discuss that shift. Firms search for new technologies and patent what they find. But different firms have different strategies: one is to protect an invention; a second is to protect a technology space; the third is to attack others’ technology spaces. In the literature the latter two have been described as different types of blocking. We examine different IPR regimes, characterized by who is able to infringe whose patent rights. This is an extreme case of who is able to extract rents from a given configuration of patent rights. |
| Keywords: | Innovation, Patents, Knowledge network, Blocking strategies. |
| JEL: | O31 O34 C6 L5 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-20&r= |
| By: | Mr. Jorge A Chan-Lau; Ruofei Hu; Luca Mungo; Ritong Qu; Weining Xin; Cheng Zhong |
| Abstract: | We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to construct a probability of default (PD) function. This function integrates high-frequency, market-based, aggregate distress signals with low-frequency, firm-level financial ratios, and macroeconomic indicators. When provided with private firms' financial ratios, the model, which we name signal-knowledge transfer learning model (SKTL), transfers insights gained from 35 thousand publicly-traded firms to more than 4 million private-held ones and performs well as an ordinal measure of privately-held firms' default risk. |
| Keywords: | Default risk; Corporate sector; Privately-held firm; Gradient boosting; Transfer learning |
| Date: | 2024–06–07 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2024/115&r= |