Is there a linear relationship between R&D intensity and growth? Empirical evidence of non-high-tech vs. high-tech SMEs

Abstract

To investigate whether there is a similar relationship between R&D intensity and growth in high-tech and non-high-tech small and medium-sized enterprises (SMEs), we examine two samples of SMEs in manufacturing industries, applying the two-step estimation method. Our findings are that R&D intensity restricts the growth of high-tech SMEs at lower levels of R&D intensity and stimulates their growth at higher levels. However, R&D intensity restricts the growth of non-high-tech SMEs regardless of the level of R&D. The relationships obtained between other determinants considered in the literature and the growth of high-tech and non-high-tech SMEs allow us to conclude that (i) smaller, younger, non-high-tech SMEs grow more quickly than larger, older, non-high-tech SMEs, which does not occur in the case of high-tech SMEs; and (ii) financing restrictions are especially important in financing the growth of high-tech SMEs, compared with non-high-tech SMEs.

Introduction

High-tech small and medium-sized enterprises (SMEs) are considered to be principal drivers of economic and employment growth in developed countries. In European countries, high-tech SME activity is considered to be crucial to achieving the desired structural transformation of economies (European Commission, 2008). Henrekson and Johansson (2010) conclude that government policies on entrepreneurship (incentives for entry, survival, and growth of high-tech SMEs) are fundamental for stimulating economic and employment growth in European economies.

Among the activities of high-tech SMEs, R&D investment is particularly important (Stam and Wennberg, 2009, Lee, 2010). This is the case because, aside from the ability to create new products and develop more efficient productive processes, R&D investment encourages strategic cooperation among firms (Gilsing et al., 2008, De Jong and Freel, 2010). Together, these factors promote a greater spread of knowledge spillovers (Coad and Rao, 2008) and help to increase absorptive capacity (Cohen and Levinthal, 1989).

While admitting that R&D investment is fundamental to the success of high-tech SME activities and, consequently, to increased gains in countries’ macroeconomic and microeconomic productivity (Ortega-Argilés et al., 2010), European countries still trail far behind the United States (for example) with respect to investment in high-tech sectors (European Commission, 2008). Ortega-Argilés et al. (2010) conclude that the low productivity of high-tech sectors in Europe compared to the United States is not explained by lower levels of R&D investment but is instead a consequence of the inability to transform R&D investment into productivity gains, which would thereby make firms more competitive. One possible explanation for that inability resides in firms’ failure to use assets efficiently. Teece (1986) argues that taking advantage of asset complementarity may be particularly important for improving firm performance. Nevertheless, that same author concludes that SMEs have difficulty benefiting from innovation insofar as their complementary assets are more limited compared to large firms.

The growth of SMEs is crucial to ensure survival and subsequent consolidation in their operating markets (Lotti et al., 2009). In addition, SMEs are considered to be the main driving force behind economic and employment growth in European countries and, therefore, should be given a special status in major government policies, especially those related to high-tech SMEs (European Commission, 2008).

Considering the importance of high-tech SMEs for economic and employment growth in developed countries in general, and in European countries in particular, studying the relationship between R&D intensity and high-tech SME growth is especially important. Thus, we seek to ascertain if the relationship between R&D intensity and growth is different between high-tech SMEs and non-high-tech SMEs. On the basis of our findings, we also hope to formulate helpful advice for managers/owners of high-tech SMEs and non-high-tech SMEs as well as for policy-makers.

To do so, we consider two samples of Portuguese SMEs in manufacturing industries: (i) 330 non-high-tech SMEs and (ii) 133 high-tech SMEs. We believe Portugal (a small open economy within the single European market (IAPMEI, 2008)) to be a good setting for this investigation because 99.6% of all firms are SMEs. It is clear, therefore, that such firms play a leading role in the performance of the country's economy and employment.

We use the two-step estimation method proposed by Heckman (1979). This method is considered suitable for efficiently solving the problem of result bias associated with the matter of survival. In the first stage, we estimate probit regressions of survival, considering all non-high-tech and high-tech SMEs. In the second stage, after calculating the inverse Mill's ratio and including it in the regressions, we estimate relationships between determinant factors and the growth of non-high-tech vs. high-tech SMEs, considering only surviving non-high-tech and high-tech SMEs.

The empirical findings allow us to make the following contributions and implications regarding the literature on SMEs and R&D management. R&D intensity is a factor that restricts growth in non-high-tech SMEs, regardless of the level of R&D intensity. In the case of high-tech SMEs, R&D intensity is a factor that stimulates growth, but only for higher levels of R&D intensity. At lower levels of R&D intensity, it restricts growth. Smaller, younger, non-high-tech SMEs grow more quickly than larger, older, non-high-tech SMEs, which does not occur in the case of high-tech SMEs, where size and age have no influence on growth. Financial restrictions are more severe in the case of high-tech SME growth than in non-high-tech SME growth. Using the two-step estimation method allows us to make another contribution, which is to confirm that the factors determining survival in high-tech SMEs are different from those for non-high-tech SMEs.

The remainder of the paper is structured as follows: Section 2 presents the literature review and hypotheses for investigation; Section 3 presents the database, variables, and estimation method used; Section 4 presents the results; Section 5 discusses those results; and Section 6 presents conclusions and implications.