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on Knowledge Management and Knowledge Economy |
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Issue of 2018‒02‒19
six papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Asongu, Simplice; Tchamyou, Vanessa; Acha-Anyi, Paul |
| Abstract: | This study assesses the knowledge economy (KE) performance of lagging African countries vis-à-vis their frontier counterparts with regard to the four dimensions of the World Bank’s knowledge economy index (KEI). The empirical exercise is for the period 1996-2010. It consists of first establishing leading nations before suggesting policy initiatives that can be implemented by sampled countries depending on identified gaps that are provided with the sigma convergence estimation approach. The following are established frontier knowledge economy countries. (i) For the most part, North African countries are dominant in education. Tunisia is overwhelmingly dominant in 11 of the 15 years, followed by Libya which is a frontier country in two years while Cape Verde and Egypt lead in a single year each. (ii) With the exception of Morocco that is leading in the year 2009, Seychelles is overwhelmingly dominant in ICT. (iii) South Africa also indomitably leads in terms of innovation. (iv) While Botswana and Mauritius share dominance in institutional regime, economic incentives in terms of private domestic credit are most apparent in Angola (8 years), the Democratic Republic of Congo (3 years) and Tanzania, Sierra Leone and Malawi (each leading in one year). |
| Keywords: | Knowledge economy; Benchmarks; Policy syndromes; Catch-up; Africa |
| JEL: | O10 O30 O38 O55 O57 |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:84043&r=knm |
| By: | Kul B. Luintel; Mosahid Khan |
| Abstract: | Research and development (R&D) activities of emerging countries (EMEs) have increased considerably in recent years. How important are knowledge transfers from developed countries and other emerging countries? This wide-ranging but rigorous macro-level study of 31 EMEs provides some much-needed evidence. |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:35&r=knm |
| By: | Jason Dedrick; Kenneth L. Kraemer |
| Abstract: | This report uses data on individual smart phones as well as industry data to identify which smartphone firms capture the most value. It finds that Apple captures most of the industry profits, thanks to its high prices, large profit margins and the volume of iPhone sales worldwide. Apple’s success is explained as a result of its ability to develop its own intellectual property (IP) and take advantage of IP created by suppliers through a strategy of selling only a few models at high prices compared to competitors. |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:wip:wpaper:41&r=knm |
| By: | Koen Jonkers (European Commission - JRC); Robert Tijssen; Athina Karvounaraki (European Commission - JRC); Xabier Goenaga Beldarrain (European Commission - JRC) |
| Abstract: | This report provides a framework to assess the impact of universities on their regional innovation ecosystem. The policy context for this work is provided by: a) the Renewed EU agenda for higher education which argued that universities do not attain their full potential; and b) the report by the High Level Group chaired by Pascal Lamy which called for an additional funding stream to support universities to modernise and increase their innovation impact. This report explores what the assessment framework underpinning such an innovation performance based funding instrument could look like. However, it acknowledges that the final form of such a framework would heavily depend on the regional, national or EU level instrument through which it is implemented. The report proposes a system in which universities draft a case study supported by indicators, through which they present evidence of their contribution to regional innovation. It identifies four impact categories and identifies a list of associated indicators. In this "narrative with numbers the universities can both explain how they reach this impact and contextualise their performance with reference to the development level of their region. |
| Keywords: | universities, higher education, innovation, performance based funding, knowledge transfer |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc109020&r=knm |
| By: | Shuige Liu |
| Abstract: | We provide an epistemic foundation for the core of a cooperative game by proof theory. Given a cooperative game, we first transform each payoff vector into a decision problem (accept or reject) for each player. Then we use a modified KD-system in epistemic logic to describe a player's belief/knowledge, decision-making criterion, and reasoning process. Especially, we define C-acceptability to capture the criterion for a core payoff vector. Within this syntactical framework, we characterize the core of a cooperative game in terms of each player's knowledge. Based on this result, we discuss epistemic inconsistency behind Debreu-Scarf Theorem. |
| Date: | 2018–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1802.04595&r=knm |
| By: | John Edwards (European Commission - JRC); Elisabetta Marinelli (European Commission - JRC); Eskarne Arregui Pabollet (European Commission - JRC); Louise Kempton |
| Abstract: | The Policy Brief analyses three elements: - S3 Platform survey data on institutions and smart specialisation - ESF programming data - HESS pilot case studies |
| Keywords: | Higher Education Institutions, Smart Specialisation, Innovation |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc109780&r=knm |