nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2017‒05‒21
five papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. What cluster model for the competitiveness of Tunisian companies? By Bouhari, Mohamed; Khabbouchi, Rafika; Mathlouthi, Yamina
  2. The Measurement of Synergy in Innovation Systems: Redundancy Generation in a Triple Helix of University-Industry-Government Relations By Loet Leydesdorff; Henry Etzkowitz; Inga Ivanova; Martin Meyer
  3. Trends and Priority Shifts in Artificial Intelligence Technology Invention: A global patent analysis By FUJII Hidemichi; MANAGI Shunsuke
  4. Does Inter-firm Collaboration Network Improve Quality of Innovation? International comparative analysis from worldwide patent data (Japanese) By IINO Takashi; INOUE Hiroyasu; SAITO Yukiko; TODO Yasuyuki
  5. 7 ways to boost digital innovation and entrepreneurship in Europe. Key messages from the European innovation policies for the digital shift project By Daniel Nepelski; Marc Bogdanowicz; Federico Biagi; Paul Desruelle; Giuditta De Prato; Garry Gabison; Giuseppe Piroli; Annarosa Pesole; Nikolaus Thumm; Vincent Van Roy

  1. By: Bouhari, Mohamed; Khabbouchi, Rafika; Mathlouthi, Yamina
    Abstract: This paper gives purpose to identify the factors of the constitution of "the Tunisian cluster" in an environment open to competition. It is a contribution to the debate on the importance of clusters for competitiveness of small and medium enterprises (SMEs) to make more innovative and competitive regions and to promote strategically important sectors in technology. Approaches based on the knowledge economy grew by better integrating forms of proximity, organizational, institutional and geographical, (Torre and Rallet 2005) and relational (Boshma, 2005). An empirical study was conducted on a sample of Information and Communication Technologies ICTs’companies. The results show that the lack of attractiveness of ICT Tunisian companies to form clusters is not due to a lack of suitable infrastructure but to the absence of relations involved in a partnership approach or localized nature between higher education, research centers, industry training and organization, enabling to carry out scientific and technical projects.
    Keywords: Clusters, technology centers, geographical proximity, organized proximity
    JEL: R11 R12 R13
    Date: 2016–03
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:79110&r=knm
  2. By: Loet Leydesdorff (University of Amsterdam); Henry Etzkowitz (International Triple Helix Institute (ITHI),); Inga Ivanova (Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics (NRU HSE),); Martin Meyer (Kent Business School,)
    Abstract: In university-industry-government relations, one not only exchanges information, but can also share meanings provided from partially overlapping perspectives. Such sharing of meanings invokes different codes of communication and generates redundancies. Redundancy can be measured as the number of options not yet realized in a system of innovations. The generation of new options is probably more important for the quality of knowledge-based innovation systems than prior achievements. Three levels of communication can be distinguished: the communication of information in networks of relations, the sharing of meaning among differently positioned agents in a multi-dimensional vector space, and codes of communication (“horizons of meaning”) which “structurate” meaning processing among reflexive agents. Scientometricians have mainly studied the communication of information; new options, however, are generated and entertained discursively in the knowledge base. The Triple-Helix synergy indicator enables us to measure the generation of redundancy as feedback on historical trajectories. In a number of studies of national systems of innovation (e.g., Sweden, Germany, Spain, China), this measure was used to indicate niches (e.g., regions) in which uncertainty is reduced. Reduction of uncertainty improves the entrepreneurial climate for innovation. The quality of an innovation system can thus be quantified at different geographical scales and in terms of different sectors, such as high- and medium-tech manufacturing or knowledge-intensive services.
    Keywords: Triple Helix; Non-linear Dynamics; University-Industry-Government Relations; Redundancy; Innovation Systems; Knowledge Base
    URL: http://d.repec.org/n?u=RePEc:sru:ssewps:2017-08&r=knm
  3. By: FUJII Hidemichi; MANAGI Shunsuke
    Abstract: Artificial intelligence (AI) technology can play a critical role in economic development, resource conservation, and environmental protection by increasing efficiency. This study is the first to apply a decomposition framework to clarify the determinants of AI technology invention. Exploiting data from the World Intellectual Property Organization, this study clarifies the determining factors that contribute to AI technology patent publications based on technology type. Consisting of 13,567 AI technology patents for the 2000-2016 period, our worldwide dataset includes patent publication data from the United States, Japan, China, Europe, and the Patent Cooperation Treaty (PCT). We find that priority has shifted from biological- and knowledge-based models to specific mathematical models and other AI technologies, particularly in the United States and Japan. Our technology type and country comparison shows that the characteristics of AI technology patent publication differ among companies and countries.
    Date: 2017–05
    URL: http://d.repec.org/n?u=RePEc:eti:dpaper:17066&r=knm
  4. By: IINO Takashi; INOUE Hiroyasu; SAITO Yukiko; TODO Yasuyuki
    Abstract: Using worldwide patent data and considering co-assignment as collaboration between firms, we compare the characteristics of international collaboration. Then, we examine the effect of knowledge propagation through collaboration on the quality of innovation. Introducing indices proposed in network science to capture firms' status in networks is the feature of this paper. We found collaborations of Japanese firms are less internationalized compared to other countries while Japanese firms tend to collaborate more than others, i.e., they intensively collaborate within a country. However, intensive collaboration within the country doesn't necessary improve the quality of innovation. Instead, firms bridging firms in different groups and creating various connections produce high-quality innovation. This is contrary to U.S. firms which benefit from various type of connections, including intensity of networks. This implies that it is difficult to improve innovation quality by knowledge propagation through collaboration for firms in many countries including Japan.
    Date: 2017–04
    URL: http://d.repec.org/n?u=RePEc:eti:rdpsjp:17034&r=knm
  5. By: Daniel Nepelski (European Commission - JRC); Marc Bogdanowicz; Federico Biagi (European Commission - JRC); Paul Desruelle (European Commission - JRC); Giuditta De Prato (European Commission - JRC); Garry Gabison (European Commission - JRC); Giuseppe Piroli; Annarosa Pesole (European Commission - JRC); Nikolaus Thumm (European Commission - JRC); Vincent Van Roy (European Commission - JRC)
    Abstract: This report attempts to summarise findings and conclusions of over 30 studies published within the EURIPIDIS project (European Innovation Policies for the Digital Shift). The objective of EURIPIDIS was to better understand how digital innovation and entrepreneurship work; to assess the EU's digital innovation and entrepreneurship performance; and to suggest how policy makers could make digital innovation and entrepreneurship in the EU work better. Because digital technologies facilitate the modernization of firms and economies, digital innovation and entrepreneurship requires a comprehensive policy response. The current report focuses on 7 issues. (1) Digital innovation and entrepreneurship require skills and capabilities ranging from technical, managerial and financial; entrepreneurial culture; failure acceptance; large funding and innovation-friendly regulatory environment. Capacity building and specific policies are needed in all those fields. (2) Resisting digital disruption and protecting the status quo is likely to be a short-term strategy. Negative social and economic effects need to be mitigated. (3) The ecosystem of digital innovation and entrepreneurship consists of a wide range of different players. Policy responses need to address this heterogeneity. (4) Digital innovation and entrepreneurship takes place through collaborative interactions between various players. To facilitate collaboration, knowledge flow and spillovers need to become a more central focus of public policies. (5) In addition to increasing funding for innovation, closer attention needs to be paid to the availability of funding for scaling-up of digital enterprises. (6) To guarantee technological interoperability and create technology-related network effects, coordination between various players to, for example, set technological standards is needed. (7) Technological complexity combined with the cumulativeness of digital innovation requires a balance between two conflicting goals: the provision of incentives to create new products and the stimulation of knowledge dissemination.
    Keywords: ICT, digital economy, big data, innovation
    Date: 2017–04
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc104899&r=knm

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