Technological Collaboration: Bridging The Innovation Gap Between Small And Large Firms

Universidad Carlos III, Departamento de Econom�a de la Empresa, Business Economics Working Papers 01/2006;
Source: RePEc


The economics of recombinant knowledge is a promising field of investigation. New technological systems emerge when strong cores of complementary knowledge consolidate and feed an array of coherent applications and implementations. However, diminishing returns to recombination eventually emerge, and the rates of growth of technological systems gradually decline. Empirical evidence based on analysis of the co-occurrence of technological classes within two or more patent applications, allows the identification and measurement of the dynamics of knowledge recombination. Our analysis focus on patent applications to the European Patent Office, in the period 1981-2003, and provides empirical evidence on the emergence of the new technological system based upon information and communication technologies (ICTs) and their wide scope of applications as the result of a process of knowledge recombination. The empirical investigation confirms that the recombination process has been more effective in countries characterized by higher levels of coherence and specialization of their knowledge space. Countries better able to master the recombinant generation of new technological knowledge have experienced higher rates of increase of national multifactor productivity growth.

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Available from: Lluís Santamaría, May 13, 2014
    • "The literature has shown that there is a positive relationship between the existence of a network of different types of external partners around a firm and its innovation performance (Becker and Dietz 2004; Gronum, Verreynne, and Kastelle 2012; Nieto and Santamaria 2010; Parida, Westerberg, and Frishammar 2012). Faems, Van Looy, and Debackere (2005) has proven that when the variety of partners of a company increases its innovation performance (of developing new products) also increases. "
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    ABSTRACT: Open innovation (OI) denotes a company's ability to draw on a range of external sources to meet their needs for innovation. Very few empirical analyses have been conducted on the extent to which this new paradigm is embedded in small and medium-sized enterprises (SMEs). Thus, the present study's objective is to identify and characterize different profiles of OI in SMEs, considering the openness of the innovation process phases, variety and breadth of collaborations, determinants, barriers, and motivations. A survey was carried out among Italian SME manufacturing firms, and a database of 105 companies was obtained. With regard to data elaboration, a factorial and cluster analysis was conducted, and three different OI profiles emerged: selective low open, unselective open upstream, and mid-partners integrated open. The different behaviors of the three clusters in terms of determinants, performance, contextual factors, barriers, and motivations were analyzed and discussed.
    Journal of Small Business Management 09/2015; 53(4):1052–1075. DOI:10.1111/jsbm.12091 · 1.39 Impact Factor
    • "Small and medium-sized enterprises (SMEs) are frequently viewed as an engine of economic growth, job creation, and greater prosperity (Wennekers and Thurik, 1999; Reynolds et al., 2004). The innovative capability of SMEs is viewed as a crucial driver of sustainable competitive advantage (Nieto and Santamaria, 2010). Though much of the evidence for this is drawn from the industrialised economies of North America and Europe, it is thought to hold for developing as well as developed economies. "
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    ABSTRACT: Purpose – The purpose of this paper is to utilise a sample of 384 small and medium-sized enterprises (SMEs) who applied for external finance in the Beijing area of China to investigate the characteristics of firms against: the amount of external finance sought, the amount received, and the proportion of external finance which was received from the sought finance. Design/methodology/approach – The authors use a survey of SMEs in Beijing, China, undertaken between July and December 2007 where a response rate of 37.67 per cent was obtained. The survey was translated from English to Chinese, and then back translated from Chinese to English by academics with input from businesses. The sample of 384 firms is robust. Findings – Overall, there is little evidence in the sample of Chinese SMEs that innovative firms face discrimination from providers of credit. However, where innovation is measured by inputs (specifically R&D), providers of credit appear less comfortable. Three other factors were more important and were statistically significant at the 5 per cent level. For example, exporters were less likely to receive a greater proportion of their sought finance; and manufacturing firms were more likely than service sector firms, and limited liability companies were more likely than extended sole proprietorship firms to obtain a greater proportion of the external finance which they sought. Research limitations/implications – The sample for the research is from Beijing. Researchers may extent and role out the research to other parts of China. Practical implications – Practically, the authors explore variations in firm-level characteristics by: the amount of external finance sought, the amount of external finance received, and the ratio of “sought” to “received” external finance. In this way, the research questions are concerned with understanding which “types” of firms seek most bank finance, and which are most successful. This information is of benefit to SMEs, policy makers and those who work in the finance industry. Social implications – Access to finance is a cause of stress and anxiety to many SMEs. A greater understanding of the accessing of finance in Beijing China will allow entrepreneurs to be better placed to reflect upon their businesses and their suitability to pursue finance. This can help the economic and social well-being of entrepreneurs and their employees. Originality/value – There are comparatively few large scale surveys which have been undertaken of access to finance by SMEs in China, and within this field there is very little research which has been undertaken to look at innovators and non-innovators. The results allow us to have a better understanding of how much finance SMEs in Beijing are seeking, obtaining, and the proportion of finance received from that sought, and the extent to which innovation and other business and owner-manager characteristics are influential.
    Journal of Small Business and Enterprise Development 08/2015; 22(3):397-416. DOI:10.1108/JSBED-01-2014-0008
    • "First is when the carmaker wishes to explore some new technological areas (like life-on-board entertainment). A closed relationship with a small (and dependant ) specialist is a good way to capture exclusive ideas and innovations (Nieto and Santamaria 2010). Second is when the carmaker wishes to preserve its market power (against mega suppliers): SMEs remain a good way to cut the procurement cost on certain generic components (Chanaron 2013). "
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    ABSTRACT: The paper questions the widely accepted vision of an automotive supply chain with a very pyramidal structure that works to mega suppliers' benefit. Mobilizing an original survey of 750 French SMEs, we show that SMEs can still operate at the very top of the pyramid and that the different tiers remain porous. The first section explains why the modularization of the automotive industry has led to a pyramidalization of supply chains, enabling the emergence of mega suppliers. The second section shows how some SMEs are still able to rise to the top tier of the supply chain, a process explained in the third section. Using the notion of interstices initially formulated by Penrose, an explanation is provided as to why mega suppliers leave certain market spaces unoccupied, with SMEs subsequently filling in the gaps. The ensuing analytical grid then leads to a conclusion that will highlight two main managerial and political implications.
    Journal of Small Business Management 07/2015; DOI:10.1111/jsbm.12182 · 1.39 Impact Factor
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