nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2020‒03‒30
five papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Emotional intelligence and tacit knowledge management in hospitality By Spyros Avdimiotis
  2. There is Not One But Many AI: A Network Perspective on Regional Demand in AI Skills By Stephany, Fabian
  3. Transferred Tax Knowledge to Improve Taxpayer Compliance By Kusumaningrum, Nurcahyaning Dwi; Hidayat, Rachmat; Wicaksono, Galih; Puspita, Yeni; Asmandani, Venantya; Pamungkas, Tree Setiawan; Susilo, Djoko
  4. Patterns of innovation, advanced technology use and business practices in Canadian firms By Fernando Galindo-Rueda; Fabien Verger; Sylvain Ouellet
  5. Capabilities, Economic Development, Sustainability By Jan Fagerberg; Martin Srholec

  1. By: Spyros Avdimiotis (International Hellenic University)
    Abstract: Several researchers stressed out the importance of tacit knowledge underlying the fact that it is a type of knowledge, almost impossible to articulate, codify and thus to transfer. Based on the argument of Avdimiotis (2016) that tacit knowledge could be acknowledged, acquired and transferred through employees' behavioral patterns, the present paper seeks to associate emotions-as determinant factor of behavior-with tacit knowledge management in hospitality establishments. To prove the association a quantitative research was held on a stratified sample of 128 hotel employees in Northern Greece. The research model was based on Nonaka and Takeuchi (1995) SECI knowledge transfer model and Salovey and Mayer Emotional Intelligence model. Findings indicate that both Emotional Intelligence and Tacit knowledge are strongly associated, leading to the inference that E.I. is a structural element of tacit knowledge.
    Keywords: Tacit Knowledge,Emotional Intelligence,Hotel and Human Resources Management
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02441027&r=all
  2. By: Stephany, Fabian
    Abstract: This work proposes a network perspective in order to empirically identify the relevant ICT skills related to AI, to what extent they are systemically related, and how their composition varies across regions. With the example of 5,227 job openings from Germany advertised as postings in Artificial Intelligence, relevant skills are identified and connected in a network fashion. Two skills are connected, if they are jointly required by the same job advertisement. Similarly, regional skill networks can be constructed: Job postings are screened by city location and skill networks are constructed for this set of regional postings exclusively. The resulting networks depict the regional city ecosystem of AI skills currently in demand.
    Date: 2020–03–02
    URL: http://d.repec.org/n?u=RePEc:osf:osfxxx:32qws&r=all
  3. By: Kusumaningrum, Nurcahyaning Dwi; Hidayat, Rachmat; Wicaksono, Galih (Universitas Jember); Puspita, Yeni; Asmandani, Venantya; Pamungkas, Tree Setiawan; Susilo, Djoko
    Abstract: The purpose of research to know the influence of the taxpayer science level on the compliance of paying taxes by taxpayers, among others: knowledge of tax law, system knowledge and taxation functions, and the knowledge of sanctions Taxation both partially and simultaneously. Data analysis methods use SPSS software with a linear regression analysis, which is used to test the hypothesized influence of the taxpayer's level of science to pay tax compliance by both partial and simultaneous taxpayers and See the magnitude of the coefficient. Based on the results the study concluded that in partial and simultaneous levels of taxpayer enforcement science has a significant effect on the compliance of paying taxes by taxpayers.
    Date: 2020–02–12
    URL: http://d.repec.org/n?u=RePEc:osf:inarxi:4kcxp&r=all
  4. By: Fernando Galindo-Rueda (OECD); Fabien Verger (OECD); Sylvain Ouellet (Statistics Canada)
    Abstract: This paper uses a distributed microdata analysis approach to map patterns of technology adoption in Canadian firms, exploring the relationship between technology adoption, business practices and innovation. Prepared by the OECD NESTI secretariat in collaboration with Statistics Canada, the paper leverages a unique enterprise database combining information on innovation, technology adoption and the use of selected business practices. This work suggests a number of possible pathways for selecting and defining priority technology and business practices for data collection and reporting, implementing recommendations in the 2018 Oslo Manual on enablers and objectives of business innovation, and identifying potential synergies between business innovation, management and ICT, and other surveys focused on various aspects of technology adoption.
    Date: 2020–03–19
    URL: http://d.repec.org/n?u=RePEc:oec:stiaaa:2020/02-en&r=all
  5. By: Jan Fagerberg (IKE, Department of Business and Management, Aalborg University; Center for Technology, Innovation and Culture (TIK), University of Oslo; Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE), Lund University); Martin Srholec (Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE), Lund University; CERGE-EI, Economics Institute, Academy of Sciences of the Czech Republic)
    Abstract: The capability concept is commonly used in analyses of firms, however, as this paper shows, it may also be used at the level of nations. Factor analysis is used on a broad set of relevant indicators to derive composite measures of national technological and social capabilities. The data covers 114 countries worldwide on different levels of development for the period 1995-2013. The paper then analyzes the relationships between these capability measures and economic development, defined in various ways, and controlling for other relevant factors. The results suggest that improving national technological and social capability is a must for achieving (sustainable) economic development and improving living conditions.
    Date: 2020–03
    URL: http://d.repec.org/n?u=RePEc:tik:wparch:2020001&r=all

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