Firms’ growth: Does the innovation system matter?
Introduction
A wide body of literature has focused on the determinants of the evolutionary process behind firm growth. In particular a growing interest has been devoted to the understanding of the determinants of firms’ differential rate of growth.
Empirical works have concentrated mainly on the traditional determinants of firm growth, principally firm-specific characteristics such as age, size, legal form and innovation, and have demonstrated that small, young and independent businesses grow at fastest rate (Mansfield, 1962, Storey, 1994, Audretsch, 1995, Sutton, 1997, Caves, 1998, Almus and Nerlinger, 1999). Besides, a growing interest in the literature has been devoted to an additional variable, i.e. location as critical factor shaping firm performance. Storey (1994) argues that some regions are more conducive to firm growth being characterised by high resources and wide market opportunities. The work by Davidsson (1989) suggests that location is an important factor for industry clustering while Davidsson et al. (2002) highlight how change in geographical location seems to exert a positive effect on business rate of growth.
In spite of the interest on the link between location and firm growth, the literature has paid less attention to the identification of the region-specific characteristics that may play a relevant role in determining the growth of firms. More recently, a few contributions emphasize how university-based knowledge spillovers influence firm performances (Audretsch and Lehmann, 2005b, Colombo et al., 2006).
In our work we extend the literature on this topic, investigating the connection between external sources of research, in particular universities, and individual firm growth by focusing on UK public companies listed on the London Stock Exchange (LSE) on both the Official List (OL) and the Alternative Investment Market (AIM). By comparing companies listed on the two markets, in our work we try to highlight the impact of knowledge produced by universities on the post-issue rate of growth of such a firms. In this paper, we further mean to emphasise the role of social sciences with respect to natural sciences in fostering growth. Previous works focusing on knowledge spillovers put much emphasis on natural sciences as if social sciences were not able to generate knowledge functional to the business sector. In the same vein, much attention has been paid to high tech sectors in empirical analysis investigating knowledge spillovers phenomena. The logic behind this preferred line of research lies in the fact that innovation mechanisms are quite easily referred to high technology. In this paper we assume that social sciences play an important role in the spillovers of knowledge since they largely draw on tacit knowledge. For this reason, we expect they became especially important for the growth of firms, both in the high- and not-high-tech sectors.
In our analysis, we compare two samples of companies for a specific reason. While companies on the Official List cover all the life cycle phases and all the industry sectors, the AIM is the secondary market dedicated to young and growing companies formed around new business ideas. These firms are in the entrepreneurial phase, characterized by high innovativeness and entrepreneurial creativity, and also by a high level of uncertainty. The literature highlights that small and young enterprises are subject to ‘credit rationing’ and thus have major difficulty in developing internal research. For this reason, these companies rely mainly on external sources of R&D in order to sustain their innovation activities. We thus expect a greater impact of university research spending and knowledge spillovers on the growth rates of AIM's companies in comparison with companies listed on the Official List.
The remainder of our paper proceeds as follows. In Section 2 we discuss the theoretical framework on the role of external sources of knowledge and highlight the expected impact on firms’ rate of growth. The sample, measure and the econometric model are presented in the methodological section. Section 4 describes the results of our analyses. Finally, in the concluding section we discuss our findings, also highlighting suggestions for further researches.
Section snippets
Universities and economic growth
The main idea behind our study is that the proactive role local institutions may influence businesses performance. In the research area of regional science, concepts like Regional Innovation Systems (RIS) (Cooke et al., 1997, Braczyk et al., 1998) and Triple Helix (TH) (Etzkowitz and Leydesdorff, 1997, Etzkowitz and Leydesdorff, 2000) emphasize the active role of territorial actors within regional development dynamics and give relevance to the institutional foundations of regions’ competitive
Dataset and sample
To verify whether the access to knowledge from universities may influence firm growth, we focus on a particular sample of firms, companies listed on the London Stock Exchange, comparing the Alternative Investment Market and the Official List.
Our main source of data is the EurIPO,3
Results
Table 4 presents the correlation matrix while the results of the econometric estimations are shown in Table 5, Table 6. The correlation matrix reveals that some rather high correlations should be taken into account in the analysis. Particularly, Research funding and Students turn out to be significantly correlated in both the AIM and OL samples. Such high correlations are probably related to one specific reason. The two variables are both measures of size, the former referring to the knowledge
Discussion
In accordance with the knowledge spillovers literature, this paper explores the relationship between universities and new businesses growth, with a particular focus on the role of knowledge spillovers and social sciences. The results of our analysis suggest that both universities knowledge input and output in a specific region positively impact the rate of growth of entrepreneurial companies in the early stages of the life cycle. Thus, it appears that such a firms absorb more knowledge from the
Acknowledgments
The authors wish to thank Cristiano Antonelli, Giovanni Dosi, Joana Mendonça, Pier Paolo Patrucco, Nick Von Tunzelmann and two anonymous referees for useful suggestions. The paper has also benefited from the comments of the participants at the EMAEE 2007 Conference, the 47th Congress of ERSA and the XXI RENT Conference. A. Colombelli wishes to thank Marie Curie Training Site (grant ref.: MEST-CT-2004-504299) for financial support.
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