nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2022‒01‒31
three papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Peer Learning in Teams and Work Performance: Evidence from a Randomized Field Experiment By Kamei, Kenju; Ashworth, John
  2. The identification of Smart Specialisation priority domains in Serbia By RADOVANOVIC Nikola; MATUSIAK Monika; KLEIBRINK Alexander
  3. What prevents spillovers from the pool of knowledge? By Lööf, Hans

  1. By: Kamei, Kenju; Ashworth, John
    Abstract: A novel field experiment shows that learning activities in pairs with a greater spread in abilities lead to better individual work performance, relative to those in pairs with similar abilities. The positive effect of the former is not limited to their performance in peer learning material, but it also spills over to their performance in other areas. The underlying improvement comes from the stronger increased performance of those whose achievements were weak prior to peer learning. This implies that exogenously determining learning partners with different abilities helps improve productivity through knowledge sharing and potential peer effects.
    Keywords: peer effects, dilemma, knowledge sharing, field experiment, teamwork
    JEL: C93 I23 J24 M54
    Date: 2021–12–19
  2. By: RADOVANOVIC Nikola (European Commission - JRC); MATUSIAK Monika (European Commission - JRC); KLEIBRINK Alexander
    Abstract: The report documents the findings of the analytical phase of development of the Smart Specialisation Strategy for Serbia, implemented with the methodological and financial support of the Joint Research Centre of European Commission (JRC). The analysis follows the Smart Specialisation Framework for EU Enlargement and Neighbourhood Region (Matusiak and Kleibrink, 2018) and has two complementary parts: the quantitative mapping aims to identify the potential Smart Specialisation priority domains based on the set of indicators showing critical mass, specialisation and growth rates in subsectors of economic activity and specialisation in science, technology and innovation outputs. The results of this analysis are in a second step verified through a qualitative mapping, based on structured interviews, focus groups and case studies. Both analyses provide a sound base for the following entrepreneurial discovery phase of the strategy development. The findings from both analyses represented key inputs for the upcoming stakeholder dialogue under the Entrepreneurial Discovery Process (EDP).Serbia decided to introduce the Smart Specialisation approach into the development of its innovation policy in 2016. Guidance and technical support has been provided by the Joint Research Centre ever since, based on the Smart Specialisation Framework for the EU Enlargement and Neighbourhood Region. Serbia created its National Smart Specialisation team for coordinating the Smart Specialisation process and it has run the process until the strategy was adopted in February 2020. The analytical team of the National Smart Specialisation Team of Serbia played an important role in providing expert support and developing local capacities for both the quantitative mapping, conducted by the Fraunhofer ISI, and the qualitative mapping. Another important contributor was the National Statistical Office of Serbia, which provided necessary disaggregated data sets which made the analysis possible. The quantitative mapping revealed several primary and secondary preliminary priority areas which were further analysed in the qualitative mapping phase. The qualitative analysis set out four final priority domains with sub-areas for Smart Specialisation in Serbia.
    Keywords: mapping, smart specialisation, serbia, innovation
    Date: 2021–12
  3. By: Lööf, Hans (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)
    Abstract: This paper surveys theoretical and empirical literature on non-pecuniary flow of knowledge and the conditions and limitations for firms to benefit from positive externalities. Spillovers from the pool of accumulated knowledge generated by technological and scientific development is considered to be a key factor for economic development in modern growth models. Knowledge spillovers has also been a major topic of empirical research on firms’ innovation and economic performance over the last thirty years or more. By exploiting theoretical and methodological advances, and using more comprehensive, complex and detailed data sources, scholars from various scientific disciplines have improved the identification of factors, mechanisms, and channels that influence flows of knowledge within and across industries, technological regimes and regions. This research has deepened the understanding of the economic importance of knowledge spillovers.
    Keywords: externalities; innovation; knowledge spillovers; productivity; technology
    JEL: L20 M13 O31 O33 O40
    Date: 2022–01–03

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