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on Economics of Strategic Management |
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Issue of 2022‒04‒25
seven papers chosen by João José de Matos Ferreira Universidade da Beira Interior |
| By: | LEOGRANDE, ANGELO |
| Abstract: | The European Innovation Scoreboard calculates the value of the impact of innovation on employment through the sum of two sub-indicators, i.e. employment in knowledge-intensive activities and employment in innovative companies. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112517&r= |
| By: | LEOGRANDE, ANGELO |
| Abstract: | The European Innovation Scoreboard-EIS calculates the value of employees in knowledge-intensive activities in Europe. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–24 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112538&r= |
| By: | Kroll, Henning; Frietsch, Rainer |
| Keywords: | China,Global Science,Innovation |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fisidp:73&r= |
| By: | Leogrande, Angelo; Magaletti, Nicola; Cosoli, Gabriele; Massaro, Alessandro |
| Abstract: | The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112242&r= |
| By: | Ferney Osorio (UNAL - Universidad Nacional de Colombia [Bogotà], ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine); Laurent Dupont (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine); Mauricio Camargo (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine); José Ismael Peña (UNAL - Universidad Nacional de Colombia [Bogotà]) |
| Abstract: | This paper examines through a single case study the process in which strategic intent is built within an innovation lab. As collaborative innovation structures, innovation labs are sensitive to collision of visions leading to misalignments that could undermine their purpose. Therefore, this study explores from a managerial point of view the way in which an innovation lab is designed, implemented, and sustained in a university context. Results depict the different manifestations of strategic intent that (1) led to the reorganization of existing capabilities under the original idea that gave life to the lab, (2) drove the experimentation and adaptation stages that shaped our case, and (3) favored the institutionalization of the practices and routines resulting from the lab to its ecosystem. This suggests the potential use of the framework to be applied as a coherence-building tool from which strategic intent could be made recognizable and operational. |
| Keywords: | innovation lab,strategic intent,strategy-making,case study |
| Date: | 2021–07–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03285670&r= |
| By: | Thakur, Gogol M |
| Abstract: | Can expansion of modern-services such as telecommunications, banking & finance and business services boost industrialization in developing countries? We explore this question in a two-sector Kaleckian model where an autonomously growing service sector generates market for a demand-constrained domestic industry but the latter faces competition from technologically-superior imports. We show that it is possible to have a steady state in this model, where domestic industry grows at the same rate as the service sector with positive industrial employment growth. Convergence to this steady state, however, requires domestic industry to increase its rate of technical change in response to increasing import competition. We find that improvements in the conditions for technological progress in the domestic industrial sector, say because of policy interventions that helps in upgrading technology, can increase relative size of domestic industry. On the other hand, an increase in the pace of technological progress abroad or an increase in the elasticity of imports of industrial product with respect to technology gap between the domestic industry and its foreign competitor reduces the same. |
| Keywords: | Modern services and industrialization, imports, technology gap, developing countries, two-sector Kaleckian model |
| JEL: | F63 F68 O14 O19 O41 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112297&r= |
| By: | Jonathan McFadden (University of Oklahoma); Francesca Casalini (OECD); Terry Griffin (Kansas State University); Jesús Antón (OECD) |
| Abstract: | Digitalisation offers the potential to help address the productivity, sustainability and resilience challenges facing agriculture. Evidence on the adoption and impacts of digital agriculture in OECD countries from national surveys and the literature indicates broad use of digital technologies in row crop farms, but less evidence is available on uptake for livestock and speciality crops. Common barriers to adoption include costs (up-front investment and recurring maintenance expenses), relevance and limited use cases, user-friendliness, high operator skill requirements, mistrust of algorithms, and technological risk. National governments have an important role in addressing bottlenecks to adoption, such as by ensuring better information about costs and benefits of various technologies (including intangible benefits such as quality of life improvements); investing in human capital; ensuring appropriate incentives for innovation; serving as knowledge brokers and facilitators of data-sharing to spur inclusive, secure and representative data ecosystems; and promoting competitive markets. |
| Keywords: | Barriers to adoption, Precision agriculture, Productivity, Risk management, Sustainability |
| JEL: | Q15 Q16 L79 Q12 O33 |
| Date: | 2022–04–13 |
| URL: | http://d.repec.org/n?u=RePEc:oec:agraaa:176-en&r= |