nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2015‒06‒13
six papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Knowledge Diffusion and Industry Growth: The Case of Japanfs Early Cotton Spinning Industry By Serguey Braguinsky
  2. Macro-Economic Models for R&D and Innovation Policies By Francesco Di Comite; d’Artis Kancs
  3. A New Approach to Estimation of the R&D-Innovation-Productivity Relationship By Christopher F Baum; Hans Lööf; Pardis Nabavi; Andreas Stephan
  4. Establishing Relationships with New Suppliers Having Distant Knowledge to Target Discontinuous Innovation By Jouini, Sihem Ben Mahmoud; Charue-Duboc, Florence
  5. Technological learning in MNC subsidiaries operating in regional integration processes: a case study on an automotive company in MERCOSUR By Martín Obaya
  6. National or international public funding? Subsidies or loans? Evaluating the innovation impact of R&D support programmes By Huergo, Elena; Moreno, Lourdes

  1. By: Serguey Braguinsky
    Abstract: The diffusion of technological knowledge is key to industry growth. But not all knowledge is created equal. I use a nanoeconomic approach to examine knowledge-diffusion based growth in the Meiji-era Japanese cotton spinning industry, which enjoyed remarkable success after a decade of initial failure. By tracing sources of technological knowledge to individual engineers, I find that successful technology diffusion required the right kind of human capital embodying and transmitting knowledge, and a competitive environment that rewarded talent while weeding out incompetence.
    Date: 2015–06
    URL: http://d.repec.org/n?u=RePEc:dpr:wpaper:0939&r=knm
  2. By: Francesco Di Comite (European Commission JRC-IPTS); d’Artis Kancs (European Commission JRC-IPTS)
    Abstract: This report compares R&D modelling approaches in four macroeconomic models used by the European Commission for ex-ante policy impact assessment: one Dynamic Stochastic General Equilibrium (DSGE) model – QUEST; one Spatial Computable General Equilibrium (SCGE) model – RHOMOLO; one Computable General Equilibrium (CGE) model – GEM-E3; and one macro-econometric model – NEMESIS. The report critically compares particularly those parts of the four models that are relevant to R&D transmission mechanisms and interfaces for implementing policy shocks. Given that R&D investment decisions are inherently dynamic, QUEST appears to be the most suitable model for assessing the impact of R&D and innovation policies over time, as it is the only model with inter-temporal optimisation of economic agents. In order to address questions related to geographic concentration of innovative activities and spatial knowledge spillovers, RHOMOLO has a comparative advantage, as it is the only one which models regional economies and spatial interactions between them explicitly. Due to its detailed treatment of energy sectors and environmental issues, GEM-E3 appears to be the most suitable model for assessing the impact of innovation in clean energy. For a more detailed modelling of different types of innovation measures, NEMESIS can provide valuable insights thanks to its richness in estimating and accounting for specific channels of innovation. We also identify avenues for future research, which in our view could improve the modelling of R&D and innovation policies both from a conceptual and empirical perspective.
    Keywords: RHOMOLO, QUEST, GEM-E3, NEMESIS, Macro-Economic Models, General Equilibrium, R&D Policies
    JEL: C68 D24 D58 H50 O31 O32
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:ipt:wpaper:201503&r=knm
  3. By: Christopher F Baum (Boston College; DIW Berlin); Hans Lööf (Royal Institute of Technology, Stockholm); Pardis Nabavi (Royal Institute of Technology, Stockholm); Andreas Stephan (Jönkoping International Business School)
    Abstract: We evaluate a Generalized Structural Equation Model (GSEM) approach to the estimation of the relationship between R&D, innovation and productivity that focuses on the potentially crucial heterogeneity across technology and knowledge levels. The model accounts for selectivity and handles the endogeneity of this relationship in a recursive framework. Employing a panel of Swedish firms observed in three consecutive Community Innovation Surveys, our maximum likelihood estimates show that many key channels of inuence among the model's components differ meaningfully in their statistical significance and magnitude across sectors defined by different technology levels.
    Keywords: R&D, Innovation, Productivity, Generalized Structural Equation Model, Community Innovation Survey
    JEL: C23 L6 O32 O52
    Date: 2015–05–29
    URL: http://d.repec.org/n?u=RePEc:boc:bocoec:876&r=knm
  4. By: Jouini, Sihem Ben Mahmoud; Charue-Duboc, Florence
    Abstract: A discrepancy exists in the literature regarding the type of suppliers to consider when targeting discontinuous innovation (DI). Some authors suggest that DI require leveraging knowledge from a selection of familiar and trustful suppliers, whereas others claim that DI requires leveraging distant knowledge from new suppliers. The authors argue that establishing relationships with a new supplier mastering knowledge distant from the firm’s one, requires a specific process. Based on a longitudinal study in a firm that developed such relationships and succeeded in enhancing DI, they underline three characteristics of the approach adopted: (i) proposing an open enough formulation to give the suppliers the opportunity to value their competencies but well documented, (ii) having a structured and transparent process, supporting a mutual progressive commitment and (iii) dedicating a specific entity with access to the top management and technical specialists, with a global vision of the questions to be tackled.
    Keywords: Discontinuous innovation; early supplier involvement; leveraging external knowledge
    Date: 2014–01–05
    URL: http://d.repec.org/n?u=RePEc:ebg:heccah:1087&r=knm
  5. By: Martín Obaya
    Abstract: In the last three decades, multinational corporations (MNC) have undergone a far-reaching reorganisation that resulted, firstly, in a reorganisation of their business activities around regional areas, and secondly, in an increasing decentralisation of their knowledge-creating activities. As a result of this evolution, some subsidiaries in developing countries have benefited from this process and been able to accumulate technological capabilities. Through the examination of an automotive MNC operating in MERCOSUR, this article examines how innovation activities are organised among subsidiaries operating in a regional integration agreement among developing countries, and what are the driving forces shaping this process. Empirical findings show that a highly hierarchical division between the subsidiaries has been established by the parent company and that knowledge-creating activities are geographically concentrated in one single country.
    Keywords: Automotive industry; Product development, MERCOSUR; Innovation management
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:aal:glowps:2015-02&r=knm
  6. By: Huergo, Elena; Moreno, Lourdes
    Abstract: The objective of this study is to compare the effect of different types of public support for R&D projects on firms’ technological capabilities. We distinguish be-tween low-interest loans and subsidies and between national and European sup-port. Using data on 4,407 Spanish firms during the period 2002-2005, we estimate a multivariate probit to analyse the determinants of firms’ participation in public R&D programmes and, later, the impact of this participation on firms’ technologi-cal capabilities using different indicators. The results provide evidence of the ef-fectiveness of all treatments for improving firms’ innovative performance. With respect to innovation outputs, apart from the indirect effect of public support by stimulating R&D intensity, we also find evidence of a direct effect of participation in the CDTI credit system and in the European subsidy programme on the probability of obtaining innovations and applying for patents.
    Keywords: Soft loans, R&D subsidies, impact assessment
    JEL: H81 L2 L52 O3
    Date: 2014–03–07
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:64926&r=knm

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