nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2021‒02‒22
five papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Identification Of Business Knowledge Management Strategy: Using The Research Skills Development Framework Concept By Sangadji, Suwandi S.; , Ismaulina; Manullang, Sardjana Orba; Tahirs, Jemi Pabisangan; , Mardhiah
  2. Endogenous life expectancy and R&D-based economic growth By Tscheuschner, Paul
  3. Corporate govermance for sustainability By Andrew Johnston; Jeroen Veldman; Robert G. Eccles; Simon Deakin; Jerry Davis; Marie-Laure Salles-Djelic; Blanche Segrestin; Cynthia Williams; David Millon; Paddy Ireland; Beate Sjafjell; Christopher Bruner; Lorraine Talbot; Hugh Willmott; Charlotte Villiers; Carol Liao; Bertrand Valiorgue
  4. Artificial Intelligence, Robotics, Work and Productivity: The Role of Firm Heterogeneity By Heyman, Fredrik; Norbäck, Pehr-Johan; Persson, Lars
  5. Education, Skill Training, and Lifelong Learning in the Era of Technological Revolution By Kim , Jinyoung; Park , Cyn-Young

  1. By: Sangadji, Suwandi S. (Universitas Nuku); , Ismaulina; Manullang, Sardjana Orba; Tahirs, Jemi Pabisangan; , Mardhiah
    Abstract: The qualitative study discusses and guides the business people with the strategic management of business knowledge using research skills development framework. The success of the development of business strategy management is closely related to the framework of developing specific field expertise. One of them is through the research skills development framework (RSD). For that purpose, we have taken a strategic step, namely collecting data and information from various literature sources that seek and examine several scientific publications related to the framework and concepts of developing research expertise. After the data is collected, we next analyze with a phenomenological approach to ensure that our findings are valid and reliable in answering research formation questions. The analysis process involved coding the data, in-depth interpretation, and conclusions so that the findings could line up with the problems of the research. Finally, we could conclude the results that the RSD framework can be a conceptual framework in developing a business management strategy with analysis of approaches and communication assisted by rubrics and autonomy for researchers. Thus, these findings are to become part of a formal reference for starting a business that is useful and effective.
    Date: 2020–12–02
  2. By: Tscheuschner, Paul
    Abstract: We propose an overlapping generations framework in which life expectancyis determined endogenously by governmental health investments. As a novelty, we are able to examine the feedback effects between life expectancy and R&D-driven economic growth for the transitional dynamics. We find that i) higher survival induces economic growth through higher savings and higherlabor force participation; ii) longevity-induced reductions in fertility hampereconomic development; iii) the positive life expectancy effects of larger savingsand higher labor force participation outweigh the negative effect of a reductionin fertility, and iv) there exists a growth-maximizing size of the health caresector that might lie beyond what is observed in most countries. Altogether, the results support a rather optimistic view on the relationship between lifeexpectancy and economic growth and contribute to the debate surroundingrising health shares and economic development.
    Keywords: long-run growth,horizontal innovation,increasing life expectancy,welfare effects of changing longevity,size of health-care sectors
    JEL: I15 J11 J13 J17 O41
    Date: 2021
  3. By: Andrew Johnston (University of Sheffield [Sheffield]); Jeroen Veldman (Nyenrode Business Universiteit); Robert G. Eccles (Saïd Business School - University of Oxford [Oxford]); Simon Deakin (CAM - University of Cambridge [UK]); Jerry Davis; Marie-Laure Salles-Djelic (Sciences Po - Sciences Po); Blanche Segrestin (MINES ParisTech - École nationale supérieure des mines de Paris - PSL - Université Paris sciences et lettres); Cynthia Williams (University of York [York, UK]); David Millon (WLU - Washington and Lee University); Paddy Ireland (University of Bristol [Bristol]); Beate Sjafjell (UiO - University of Oslo); Christopher Bruner (University of Georgia [USA]); Lorraine Talbot (University of Birmingham [Birmingham]); Hugh Willmott (CASS Business School - London, UK); Charlotte Villiers (University of Bristol [Bristol]); Carol Liao (UBC - University of British Columbia); Bertrand Valiorgue (CleRMa - Clermont Recherche Management - Clermont Auvergne - ESC Clermont-Ferrand - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne)
    Date: 2019–12
  4. By: Heyman, Fredrik (Research Institute of Industrial Economics (IFN)); Norbäck, Pehr-Johan (Research Institute of Industrial Economics (IFN)); Persson, Lars (Research Institute of Industrial Economics (IFN))
    Abstract: We propose a model with asymmetric firms where new technologies displace workers. We show that both leading (low-cost) firms and laggard (high-cost) firms increase productivity when automating but that only laggard firms hire more automation-susceptible workers. The reason for this asymmetry is that in laggard firms, the lower incentive to invest in new technologies implies a weaker displacement effect and thus that the output-expansion effect on labor demand dominates. Using novel firm-level automation workforce probabilities, which reveal the extent to which a firms’ workforce can be replaced by new AI and robotic technology and a new shiftshare instrument to address endogeneity, we find strong empirical evidence for these predictions in Swedish matched employer-employee data.
    Keywords: AI&R Technology; Automation; Job displacement; Firm Heterogeneity; Matched employer-employee data
    JEL: J70 L20 M50
    Date: 2021–02–09
  5. By: Kim , Jinyoung (Korea University); Park , Cyn-Young (Asian Development Bank)
    Abstract: Rapid technological development makes skills depreciate faster than in the past while new technologies generate gaps in workers’ skills and call for the acquisition of proper skills and lifelong learning. Proper skill mixes for future jobs include strong cognitive skills, basic information and communication technology, and analytical skills, as well as a range of noncognitive skills such as creativity, problem-solving, critical thinking, and communication. Retraining and reskilling workers is also crucial. All these changes lead to a major rethinking of education and skill training throughout a person’s life. This paper reviews the recent studies on human capital and skill formation in the era of rapid technological progress. Findings from these studies particularly in labor economics can shed light on new directions for lifelong education policies.
    Keywords: education policy; lifelong learning; population aging; technology
    JEL: I25 I28 J00 J24 O15 O33
    Date: 2020–01–23

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