nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2020‒10‒05
five papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Knowledge Networks and Strong Tie Creation: the Role of Relative Network Position By Maria Tsouri; ;
  2. Knowledge Acquisition in Agricultural Finance Courses By Hanson, Erik; Wachenheim, Cheryl J.
  3. Can embedded knowledge of pollution prevention techniques reduce greenhouse gas emissions? By Lee, Sangyoul; Bi, Xiang
  4. Les incidences de l’intelligence artificielle sur la gestion des compétences dans le secteur des services financiers By Sylvie St-Onge; Michel Magnan; Catherine Vincent
  5. Knowledge Intensity and Gender Wage Gaps: Evidence from Linked Employer-Employee Data By Radu Barza; Cristian Jara-Figueroa; César A. Hidalgo; Martina Viarengo

  1. By: Maria Tsouri; ;
    Abstract: The proximity literature usually treats proximity in terms of common attributes shared by agents, disregarding the relative position of an actor inside the network. This paper discusses the importance of such dimension of proximity, labelled as in-network proximity, and proposes an empirical measurement for it, assessing its impact (jointly with other dimensions of proximity) on the creation of strong knowledge network ties in ICT in the region of Trentino. The findings show that actors with higher in-network proximity are more attractive for both other central actors and peripheral ones, which is further strengthening their position within the network.
    Keywords: knowledge networks, in-network proximity, strong ties, proximity dimensions
    Date: 2020–09
  2. By: Hanson, Erik; Wachenheim, Cheryl J.
    Keywords: Teaching/Communication/Extension/Profession, Agricultural Finance, Agribusiness
    Date: 2020–07
  3. By: Lee, Sangyoul; Bi, Xiang
    Keywords: Resource/Energy Economics and Policy
    Date: 2020–07
  4. By: Sylvie St-Onge; Michel Magnan; Catherine Vincent
    Abstract: The rise of artificial intelligence (AI) offers many opportunities to financial services institutions but also presents a number of challenges, both organizational and societal. On the one hand, AI dramatically changes the skills management within these companies. On the other hand, AI has the potential to affect in a major way employment needs and prospects in the financial services sector, and therefore challenges governments and higher education institutions current practices. In this text, we provide an overview of recent writings on these issues, all interspersed with concrete illustrations. The objective is to present a portrait of the situation to date and to identify lines of thought or action for financial services institutions, educational institutions and governments as well as to propose some research avenues. La montée en puissance de l’intelligence artificielle (IA) offre de nombreuses opportunités aux entreprises du secteur financier mais comporte également un certain nombre d’enjeux, tant organisationnels que sociétaux. D’une part, l’IA modifie de manière dramatique la gestion des compétences au sein de ces entreprises. D’autre part, l’IA risque d’avoir un impact potentiel majeur sur les besoins et perspectives d’emploi dans le secteur financier, et interpelle donc les gouvernements et institutions d’enseignement supérieur. Dans ce texte, nous effectuons un survol des écrits récents sur ces questions, le tout intercalé d’illustrations concrètes. L’objectif visé est présenter un portrait de la situation à ce jour et d’identifier des pistes de réflexion ou d’action pour les entreprises du secteur financier, les institutions d’enseignement et les gouvernements ainsi que pour proposer des avenues de recherche.
    Keywords: Artificial Intelligence,Talent Management,Competencies Management,Financial Services,Employment, Intelligence artificielle,Gestion du talent,Gestion des compétences,Services financiers,Emploi
    Date: 2020–09–17
  5. By: Radu Barza; Cristian Jara-Figueroa; César A. Hidalgo; Martina Viarengo
    Abstract: Do knowledge intense jobs exhibit lower gender gaps in wages? Here we use a linked employeremployee dataset of the entire Brazilian formal labor force to study the relationship between gender wage gaps and the knowledge intensity of industries and occupations. We find that employees in high-skilled occupations and industries experience lower gender wage gaps, and that the effect of knowledge intensity is stronger when the demand for skilled labor is high and the supply of skilled labor is low. We also find evidence that the gender wage gap of skilled workers, but not that of unskilled workers, decreases when knowledge intense industries grow. These effects are robust to controlling for individual, occupation, sector, and location characteristics. To address endogeneity concerns, we use a Bartik instrument based on labor demand shocks. Together, these findings suggest that competition for skilled labor in knowledge intense industries contributes to the reduction of gender wage gaps.
    Date: 2020

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