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Erschienen in: Small Business Economics 3/2015

01.03.2015

The determinants of R&D persistence in SMEs

verfasst von: Juan A. Máñez, María E. Rochina-Barrachina, Amparo Sanchis-Llopis, Juan A. Sanchis-Llopis

Erschienen in: Small Business Economics | Ausgabe 3/2015

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Abstract

This paper analyses the sources of persistence in conducting R&D activities by SMEs. The data used are a panel of Spanish manufacturing firms drawn from the Survey of Business Strategies, for the period 1990–2011. We estimate discrete time proportional hazard models accounting for firm observed and unobserved heterogeneity. Our results are consistent with a process of learning associated with the accumulation of R&D capital and with a self-sustained effect of engagement in R&D activities. In addition, we obtain that persistence in R&D in SMEs is also related to the success-breeds-success, sunk costs and demand-pull hypotheses. Finally, our findings also uncover some interesting differences in the underlying drivers of R&D persistence of SMEs as compared to their larger counterparts.

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Fußnoten
1
One of these European initiatives was a workshop organized by the Joint Research Center of the European Commission that gave rise to the publication of the Special Issue on the “Drivers and Impacts of Corporate R&D in SMEs” in the Small Business Economics. See Ortega-Argilés et al. (2009) for a summary of the studies in this special issue and for a survey on the literature dealing with the strengths and weaknesses of SMEs in conducting R&D, and for a broad discussion on related policy implications.
 
2
See, among others, Geroski et al. (1997), Crépon and Duguet (1997), Malerba and Orsenigo (1999), Cefis and Orsenigo (2001), Cabagnols (2006), Raymond et al. (2010) or Roper and Hewitt-Dundas (2008).
 
3
See Máñez-Castillejo et al. (2009), Artés (2009), Arqué-Castells (2013) and García-Quevedo et al. (2014) for Spanish manufacturing, Peters (2009), for German firms, and Piva and Vivarelli (2007, 2009) for Italian firms.
 
4
Since the sampling criteria for both groups are different, it would result rather complicated to include those firms with workforce between 200 and 250 workers in the SMEs group to follow the EU definition of SMEs. See Sect. 4 for further details.
 
5
Using Spanish data for the manufacturing sector, Máñez-Castillejo et al. (2009) focus on exploring the role of sunk costs in generating a dynamic behaviour in firms’ R&D decisions, but they do not analyse innovation input persistence per se. Artés (2009) analyses the link between R&D and market concentration, Arqué-Castells (2013) test the ability of R&D subsidies to induce sustained R&D performance, and García-Quevedo et al. (2014) analyse whether R&D drivers are different for young and mature firms. Using Italian manufacturing firms data, Piva and Vivarelli (2007) test the demand-pull hypothesis for innovation and Piva and Vivarelli (2009) investigate the possible role of current skills in determining corporate R&D.
 
6
See the characteristics of our database in Sect. 4.
 
7
See Kiefer (1988) for a survey on the application of these methods to economic studies.
 
8
In the mid-1980s, David (1985), based on the work of Arthur (1983), presented his historical study on the typewriter keyboard, explaining why an inefficient (from today’s perspective) typewriter keyboard was introduced and why it persisted, providing plausibility to the path dependence approach. This paper has reached the status of “founding myth” of the path dependence literature (Ruttan 1997).
 
9
In addition, Dosi (1988) introduced the concept of “technological trajectory” according to which R&D investments are characterized by high degrees of cumulativeness and irreversibility and, as a result, should exhibit a high level of persistence. In particular, when describing the nature of the innovation process, Dosi (1988) stresses that it involves the use of information drawn from previous experience and knowledge, so that innovative activities are strongly cumulative in the acquisition of problem-solving capabilities.
 
10
A measure of firms’ cash flow may also be used to capture market conditions, since the firms’ sales usually increase during economic upturns, providing the firm with higher volumes of cash flow. Thus, this variable could also be used to test for the demand-pull hypothesis, as explained later.
 
11
The traditional debate in the innovation literature between the demand-pull and the technology-push approaches has recently settled on a more balanced view that considers both as complementary factors determining innovation, as already suggested by Dosi (1988, 1997). In fact, most recent empirical studies combine these two approaches into a unified framework (Piva and Vivarelli 2007; Dosi and Nelson 2013; García-Quevedo et al. 2014).
 
13
Our working samples require non-missing values in the relevant variables in the analysis and firms’ observations with positive R&D investments.
 
14
Current R&D expenditure has been deflated using industrial prices for the manufacturing sector.
 
15
In survival models, the baseline hazard function accounts for the risk of spell termination that may be exclusively attributed to the passage of survival time and that is common to all the spells, after controlling for the covariates and unobserved heterogeneity.
 
16
We use twenty industries according to the two-digit NACE-2009 classification (reported in Table 2) to calculate this variable (see, e.g. Beneito 2000).
 
17
Exporter firms may need to innovate to face a higher competitive pressure in international markets (Kleinschmidt and Cooper 1990; Kotable 1990). In addition, according to Cohen and Levinthal (1989), foreign markets may facilitate the transfer of technology and so stimulate firms’ R&D activities.
 
18
We present the estimates of the coefficients instead of the hazard ratios since in the presence of unobserved individual heterogeneity their interpretation becomes cumbersome in survival models (see Gutiérrez 2002, p. 32).
 
19
We have experimented with three mass points, but we did not obtain statistically significant results for the final mass point.
 
20
It is important to note that 34.18 % (34.03 %) of the sample of R&D spells for SMEs (large firms) are left-censored and, thus, the lack of control for this fact is probably captured by the estimated duration dependence parameter in specification 1.
 
21
For instance, according to specification 3, receiving an R&D subsidy decreases the hazard of ending the R&D spell for SMEs, when this could be indicating that firms receiving R&D subsidies have less probability of failure. Other example is that under specification 3, the size dummies for SMEs with respect to the reference category (firms from 10 to 19 employees) hold stronger coefficients (as compared to specification 4) in reducing the likelihood of R&D spell termination, when in fact this could be indicating that larger firms (among SMEs) have lower chances of failure.
 
22
The patterns of duration dependence obtained by Geroski et al. (1997) and Le Bas et al. (2003) are inconsistent with the hypothesis of negative duration dependence, so that they provide only weak evidence on dynamic economies of scale in the production of patents or major innovations. However, as pointed out by the authors, their results could be due to their lack of information on potentially important determinants of spell duration.
 
23
However, it is important to note that besides sunk costs, there might be other reasons behind this size effect. For instance, size may be correlated with the number of distinct units/business lines within the firm, and R&D programmes in these units may not be perfectly correlated. Then, there could be some overlapped R&D programmes in larger firms, what would also lead to higher persistence in R&D with or without sunk costs. Unfortunately, we do not have information related to this issue in our dataset.
 
24
The combination of internal and external R&D may imply higher total R&D investment (already controlled by the inclusion of R&D capital), being probably also a requirement for undertaking more complex (or ambitious) R&D programmes.
 
25
For a comprehensive survey on the empirical literature of the effects of competition on innovation, see, e.g. Gilbert (2006). For a theoretical paper that acknowledges the complexity of the relationship between competition and innovation at the firm level, distinguishing between product and process innovation incentives and also among different sources of competition changes in a firm’s market, see Vives (2008). For an empirical study testing the main predictions of Vives (2008), see Beneito et al. (2014).
 
26
As many firms in the data set do not receive any subsidy for R&D activities, the inclusion in estimation of a continuous variable measuring the amount of firm’s subsidies over sales did not add any relevant effect as regards the dummy variable finally included in estimation.
 
27
Notice that when comparing a statistically significant coefficient with a non-significant one, the t statistic on the difference may fail to reject that they are equal. In these cases, we disregard the t test in column 6 and discuss the difference between SMEs and large firms considering only the variable that is statistically significant for one of these two size groups.
 
28
Añón-Higón et al. (2011), using the ESEE for the period 1990–2005, focus on decomposing the extensive and intensive margins of R&D investments into three components (starting new R&D activities, R&D activities that survive or persist, and deepening existing R&D efforts) to explain aggregated R&D growth in Spanish manufacturing, but they do not explore the drivers of firms’ R&D spell lengths.
 
29
In exploratory work, we also used a variable measuring the firm’ exports-to-sales ratio, but since it was not statistically significant, we finally decided to use the dummy variable.
 
30
To define the difficulty of an exporting market, Máñez-Castillejo et al. (2010) characterize foreign markets according to a vector of variables including, among others, the degree of competition (tougher markets incentivise firms’ innovation), and information on export market destinations to analyse the level of geographic diversification. They obtain that the level of diversification is substantially higher for large firms than for SMEs.
 
31
A Stata program elaborated by S. Jenkins that implements the cloglog model with nonparametric unobserved heterogeneity is available by typing ssc install hshaz inside Stata.
 
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Metadaten
Titel
The determinants of R&D persistence in SMEs
verfasst von
Juan A. Máñez
María E. Rochina-Barrachina
Amparo Sanchis-Llopis
Juan A. Sanchis-Llopis
Publikationsdatum
01.03.2015
Verlag
Springer US
Erschienen in
Small Business Economics / Ausgabe 3/2015
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI
https://doi.org/10.1007/s11187-014-9611-3

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