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on Knowledge Management and Knowledge Economy |
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Issue of 2022‒08‒29
four papers chosen by Laura Nicola-Gavrila Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Francesco Cinnirella; Erik Hornung; Julius Koschnick |
| Abstract: | Economic societies emerged during the late eighteenth-century. We argue that these institutions reduced the costs of accessing useful knowledge by adopting, producing, and diffusing new ideas. Combining location information for the universe of 3,300 members across active economic societies in Germany with those of patent holders and World’s Fair exhibitors, we show that regions with more members were more innovative in the late nineteenth-century. This long-lasting effect of societies arguably arose through agglomeration economies and localized knowledge spillovers. To support this claim, we provide evidence suggesting an immediate increase in manufacturing, an earlier establishment of vocational schools, and a higher density of highly skilled mechanical workers by mid-nineteenth century in regions with more members. We also show that regions with members from the same society had higher similarity in patenting, suggesting that social networks facilitated spatial knowledge diffusion and, to some extent, shaped the geography of innovation. |
| Keywords: | economic societies, useful knowledge, knowledge diffusion, innovation, social networks |
| JEL: | N33 O33 O31 O43 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9836&r= |
| By: | SBARDELLA Angelica; BARBIERI Nicolò; CONSOLI Davide; NAPOLITANO Lorenzo (European Commission - JRC); PERRUCHAS François; PUGLIESE Emanuele (European Commission - JRC) |
| Abstract: | The brief provides an overview of green technological development across European regions employing the Economic Fitness Complexity approach to establish a green technology space. The study explores the associations between comparative advantage in specific technological domains and a region’s capacity to develop green technologies, i.e. its Green Fitness. Furthermore, it addresses the interaction between the green and non-green knowledge bases, with a particular focus on whether regional know-how in the non-green technological realm can be exploited in the green domain and vice versa. To this aim, a metric of regional Green Potential is proposed. The analysis suggests that regions specialised in green domains, irrespective of their complexity, have a higher propensity to develop technologies connected with green technologies. Green technologies are linked mostly to technologies related to the production or transformation of materials; with engines and pumps; and with construction methods. The regions with the highest Green Potential are not necessarily those with the highest Green Fitness. The results suggest that there is a potential for green and non-green technological advances to generate positive spillovers in terms of capabilities to produce innovations across the spectrum of technological complexity. |
| Keywords: | Green Deal, Economic Complexity, Green Capabilities, Regional Green Potential |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc124696&r= |
| By: | Eleni Fotopoulou (National Technical University of Athens); Ioanna Mandilara (National Technical University of Athens); Anastasios Zafeiropoulos (National Technical University of Athens); Chrysi Laspidou (University of Thessaly); Giannis Adamos (University of Thessaly); Phoebe Koundouri; Symeon Papavassiliou (National Technical University of Athens) |
| Abstract: | The development of solutions to manage or mitigate climate change impacts is very challenging, given the complexity and dynamicity of the socio-environmental and socio-ecological systems that have to be modeled and analyzed to include qualitative variables that are not so easily quantifiable. The existence of qualitative, interoperable and well-interlinked data is considered a must to support this objective, since scientists from different disciplines will have no option but to collaborate and co-design solutions, overcoming barriers related to the semantic mis-alignment of the plethora of available data, the existence of multiple data silos that cannot be easily and jointly processed, and the lack of data quality in many of the produced datasets. In the current work, we present SustainGraph, as a Knowledge Graph that is developed to track information related to the evolution of targets defined in the United Nations Sustainable Development Goals (SDGs) at national and regional level. SustainGraph aims to act as a unified source of knowledge around information related to the SDGs, by taking advantage of the power provided by the development of graph databases and the exploitation of Machine Learning (ML) techniques for data population, knowledge production and analysis purposes. The main concepts represented in SustainGraph are detailed, while indicative usage scenarios are provided. A set of opportunities to take advantage of SustainGraph and open research areas are identified and presented. |
| Keywords: | Knowledge Graph, Sustainable Development Goal (SDG), Systems Innovation Approach, Climate Change Impact, Participatory Modeling, Graph Database |
| Date: | 2022–07–25 |
| URL: | http://d.repec.org/n?u=RePEc:aue:wpaper:2220&r= |
| By: | Lamiae Benhayoun-Sadafiyine (LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], TIM - Département Technologies, Information & Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]); Marie-Anne Le Dain (G-SCOP_CC - Conception collaborative - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Carine Dominguez-Péry (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes); Andrew C. Lyons (University of Liverpool) |
| Abstract: | SMEs increasingly participate in collaborative innovation networks (CINs), enabling them to access valuable external knowledge from other actors while maintaining high levels of internal competencies. The SME absorbs this knowledge to achieve reciprocal learning through its contribution to the common CIN goals, and one-way learning to improve its own organization's performance. This knowledge absorption varies according to the SME's context, described with factors such as the turbulence of its external environment, the motivations to contribute to the CIN, or the cognitive distance separating it from the network actors. To better guide this knowledge absorption, this research uses a two-stage mixed method to propose a contextualized operational measure of absorptive capacity (ACAP) for an SME embedded in a CIN. A qualitative phase consisting of semi-structured interviews was implemented first and enabled characterizing the SME's ACAP through a set of practices and dimensions that it could implement. Then a quantitative phase using the partial least squares (PLS) method established a model predicting the absorption dimensions and practices that the SME should master primarily according to its context in the CIN. Hence, this study provides SMEs with an instrument to assess their strengths and weaknesses with regard to ACAP in CINs. |
| Keywords: | SME,Collaborative network,Open innovation,Absorptive capacity,Inter-organizational learning,Partial least squares |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03144459&r= |