nep-ino New Economics Papers
on Innovation
Issue of 2015‒05‒16
seven papers chosen by
Steffen Lippert
University of Auckland

  1. R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis By Ugur, Mehmet; Solomon, Edna; Guidi, Francesco; Trushin, Eshref
  2. International Technology Diffusion of Joint and Cross-border Patents By Chia-Lin Chang; Michael McAleer; Ju-Ting Tang
  3. The Innovation Union Scoreboard is Flawed: The case of Sweden – not being the innovation leader of the EU By Edquist , Charles; Zabala-Iturriagagoitia , Jon Mikel
  4. Innovation and Member Commitment in Agricultural Cooperatives By Bareille, Francois; Beaugrand, Florence; Duvaleix-Treguer, Sabine
  5. A Study on R&D Tax Incentives - Final report By The Consortium consisting of CPB, CAPP, CASE, CEPII, ETLA, IFO, IFS, IHS
  6. KNOWLEDGE SPILLOVERS WITHIN THE ALGARVE TOURISM REGION. EVIDENCE TO IDENTIFY A REGIONAL INNOVATION SYSTEM By Maldonado, Mauricio; Noronha Vaz, Teresa
  7. Measures of innovation activities in tourism according to CIS survey By Emira Becic; Kristina Crnjar; Mauro Licul

  1. By: Ugur, Mehmet; Solomon, Edna; Guidi, Francesco; Trushin, Eshref
    Abstract: Effects of R&D investment on frim/industry productivity have been investigated widely thanks to pioneering contributions by Zvi Griliches and others in late 1970s and early 1980s. We aim to establish where the balance of the evidence lies and what factors may explain the variation in the research findings. Using 1,258 estimates from 65 primary studies and hierarchical meta-regression models, we report that the average elasticity and rate-of-return estimates are both positive, but smaller than those reported in prior narrative reviews and meta-analysis studies. We discuss the likely sources of upward bias in prior reviews, investigate the sources of heterogeneity in the evidence base, and discuss the implications for future research. Overall, this study contributes to existing knowledge by placing the elasticity and rate-of-return estimates under a critical spot light and providing empirically-verifiable explanations for the variation in the evidence base.
    Keywords: R&D,knowledge capital,productivity,meta-analysis
    JEL: D24 O30 O32 C49
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:zbw:esprep:109962&r=ino
  2. By: Chia-Lin Chang (National Chung Hsing University, Taiwan); Michael McAleer (National Tsing Hua University, Taiwan; Erasmus University Rotterdam, the Netherlands; Complutense University of Madrid, Spain); Ju-Ting Tang (National Chung Hsing University, Taiwan)
    Abstract: With the advent of globalization, economic and financial interactions among countries have become widespread. Given technological advancements, the factors of production can no longer be considered to be just labor and capital. In the pursuit of economic growth, every country has sensibly invested in international cooperation, learning, innovation, technology diffusion and knowledge. In this paper, we use a panel data set of 40 countries from 1981 to 2008 and a negative binomial model, using a novel set of cross-border patents and joint patents as proxy variables for technology diffusion, in order to investigate such diffusion. The empirical results suggest that, if it is desired to shift from foreign to domestic technology, it is necessary to increase expenditure on R&D for business enterprises and higher education, exports and technology. If the focus is on increasing bilateral technology diffusion, it is necessary to increase expenditure on R&D for higher education and technology.
    Keywords: International Technology Diffusion; Exports; Imports; Joint Patent; Cross-border Patent; R&D; Negative Binomial Panel Data
    JEL: F14 F21 O30 O57
    URL: http://d.repec.org/n?u=RePEc:tin:wpaper:20150053&r=ino
  3. By: Edquist , Charles (CIRCLE, Lund University); Zabala-Iturriagagoitia , Jon Mikel (Deusto Business School, Deusto University)
    Abstract: According to the Innovation Union Scoreboard, published by the European Commission every year, Sweden has been, and still is, an innovation leader within the EU and one of the most innovative countries in Europe. In the Innovation Union Scoreboard 2014 (European Union, 2014: 5), Sweden has the top position (ranked number 1) of all EU28 Member States in what is called “EU Member States’ Innovation Performance”. In the ranking there are 10 countries between Sweden and the EU average. This analysis is based on the ranking provided by one single composite indicator (SII or Summary Innovation Index), based on 25 separate indicators. <p> In this paper we argue that the SII provided by the Innovation Union Scoreboard is highly misleading. The data (the 25 separate indicators) that constitute this composite innovation indicator need to be analyzed much more in depth in order to reach a correct measure of the performance of an innovation system. We argue that input and output indicators need to be considered separately and measured individually and as two groups of indicators. Thereafter we compare the input and output indicators with one another (as is normally done in productivity and efficiency measurements). The outcome of this is a relevant and better measure of innovation performance. <p> In this paper, the performance of the Swedish national innovation system is analyzed by using exactly the same data as is used by the Innovation Union Scoreboard 2014. We analyze the relative position of Sweden regarding both input and output indicators, concluding that Sweden’s position as an innovation leader within the EU must be reconsidered. A theoretical background and reasons for selecting the indicators used is given and a new position regarding Sweden’s innovation performance compared to the other countries is calculated. <p> Our findings show, that Sweden remains in a high position for the innovation input indicators, ranked number 1. However, with regard to innovation output, Sweden is ranked number 10. In other words, about a third of all European Union 28 Member States have a higher innovation output than Sweden. To estimate the efficiency or productivity of the Swedish innovation system, inputs and outputs must be related to each other. When doing so, we reach the conclusion that Sweden is ranked number 24 of EU28 Member States. This finding is then discussed and we also discuss which countries would be relevant for Sweden to compare (benchmark) its innovation system with. <p> The conclusion is that Sweden, based on our calculations, can certainly not be seen as an innovation leader in Europe. This means that the Innovation Union Scoreboard is flawed and may therefore mislead researchers, policy-makers, politicians as well as the general public – since it is widely reported in the media.
    Keywords: Innovation system; innovation policy; innovation performance; Sweden; indicators; input; output
    JEL: O30 O38 O49 O52
    Date: 2015–04–29
    URL: http://d.repec.org/n?u=RePEc:hhs:lucirc:2015_016&r=ino
  4. By: Bareille, Francois; Beaugrand, Florence; Duvaleix-Treguer, Sabine
    Keywords: Research and Development/Tech Change/Emerging Technologies,
    Date: 2015–04
    URL: http://d.repec.org/n?u=RePEc:ags:aesc15:204217&r=ino
  5. By: The Consortium consisting of CPB, CAPP, CASE, CEPII, ETLA, IFO, IFS, IHS
    Abstract: Investment in research and innovation plays a critical role in kick-starting smart growth and upgrading the competitiveness of European companies. In the post-crisis world, Europe needs innovation more than ever before to keep up with the rapid technology advances and growing global competition. R&D tax incentives are an important innovation policy tool widely used in Europe. In some countries, during the crisis, tax instruments have become increasingly important for stimulating private R&D than direct funding. The recent study conducted jointly by DG TAXUD and DG GROW finds fiscal incentives for R&D expenses to be effective in stimulating investment in R&D. The size of the effect varies across countries which can be linked to country specific features, but, crucially, also to differences in the design and organisational practices of the fiscal schemes. The study identifies what are good designs for R&D tax incentives and which features are to be avoided. To answer this question, the study benchmarks the 80 existing R&D tax incentives in 33 countries (including all EU Member States) based on a number of identified good practices in design and administration.
    Keywords: European Union, taxation, R&D tax incentives
    JEL: H20 H29
    Date: 2015–01
    URL: http://d.repec.org/n?u=RePEc:tax:taxpap:0052&r=ino
  6. By: Maldonado, Mauricio (University of Chile); Noronha Vaz, Teresa (University of Algarve)
    Abstract: Studies of local knowledge spillovers have often focused on empirical evidence for core regions, and been related largely to manufacturing, neglecting behavior in less innovative economic sectors in peripheral regions. Tourism in the Algarve region is the main engine of its regional economy. Although frequently considered as a low-moderate innovative sector, competitive tourism firms are becoming increasingly Knowledge Intensive, which may create positive advantages for regional growth. This may improve conditions for the creation and diffusion of knowledge, with cooperative and collaborative interaction contributing to the consolidation of a regional innovation system (RIS). The goal of this study is to provide preliminary evidence of the main sources and vehicles of regional knowledge spillovers affecting tourism firms in the Algarve, generally considered to be a peripheral region. The main sources of knowledge used by micro and small tourism firms (MSTF) are human resources and formal and informal networks. This study detected specific features of a regional innovation platform which, eventually, may give way to a RIS.
    Keywords: Tourism; Innovation; Knowledge Spillover; Knowledge Intensive Services; Regional Innovation System; Algarve Region
    JEL: P25
    Date: 2015–05–08
    URL: http://d.repec.org/n?u=RePEc:ris:cieodp:2015_004&r=ino
  7. By: Emira Becic (Ministry of Science, Education and Sports, Directorate for Science and Technology, Zagreb, Croatia); Kristina Crnjar (Faculty of Tourism and Hospitality Management, Opatija, University of Rijeka); Mauro Licul
    Abstract: Purpose – This paper addresses a series of key questions regarding the role of innovation in tourism industry, and its relation to economic performance and the competitiveness of Croatia with regard to the tourism sector. For detecting and evaluating the impact of innovation activities on tourism sector performance, this paper takes a look at recent statistics on innovation activities in the tourism sector in Croatia and selected countries. The focus is on innovation activities made by enterprises in Sector I - Accommodation and Food Service Activities. Methodology – The majority of the statistical data will be taken from Eurostat and other data sources (UNWTO). Descriptive analysis and correlation analysis were preformed to analyze the data. Research findings and originality – Using the available data from CIS surveys, the paper analyzes the type of innovations by enterprises, estimates the impact on total turnover and tests the intensity of correlation between type of innovations, total Turnover and Receipts relative to GDP (for Croatia and selected countries). The paper analyzes trends in innovation evaluation and effects on employment in tourism. Therefore, it contributes to the existing literature on the effects of innovation in the tourism industry.
    Keywords: CIS survey, measures of innovation activities, Human capital, Innovation in Accommodation and Food Service Activities sector, Croatia
    JEL: L83
    URL: http://d.repec.org/n?u=RePEc:tho:iscthi:section2-1&r=ino

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