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Small Business Economics

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09.08.2019

Innovation persistence in times of crisis: an analysis of Italian firms

verfasst von: Davide Antonioli, Sandro Montresor

Erschienen in: Small Business Economics | Ausgabe 4/2021

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Abstract

We investigate the extent to which firms’ innovation persists in “times of crisis.” Following an eclectic theoretical background, we expect that innovation persistence limitedly emerges in these times and that SMEs persist to a different extent than large firms. We argue that innovation persistence is affected by the kind of public support firms receive and by the type of business strategy they follow. Merging three waves of the MET survey on Italian firms over the period 2005–2013, we find that the persistence of those having survived the crisis is limited to process innovations, and to radical ones in particular, being lower for SMEs. The detected persistence is reinforced by the public support firms receive for their ICT, but it is attenuated by the support directed to their employment. In terms of business strategies, intensifying research and innovation efforts attenuates innovation persistence, while diversification appears a conditional strategy for its unfolding.

Vorheriger Artikel Firms’ growth, green gazelles and eco-innovation: evidence from a sample of European firms

Nächster Artikel Entrepreneurship and personal income tax: evidence from Canadian provinces

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Tavassoli and Karlsson (2015) identify additional mechanisms at the basis of innovation persistence, but mainly related to a non-technological kind of innovations.

As we will say in the following, such a focus is also due to the temporal horizon of the dataset we use, which prevents us from making comparisons between before and after the burst of a crisis.

Of course, this is not the only structural firm feature that deserves attention with respect to innovation, R&D and their persistence. An additional one is for sure represented by the age of firms, also and above all given the high frequency of young and small-medium enterprises. On this issue, which we do not focus on because of scope constraints see, Archibugi et al. (2013a) and García-Quevedo et al. (2014).

An interesting exception has been recently documented by Ganter and Hecker (2013), who found that, after a certain level, innovation persistence diminishes in size showing an inverted U-shape relationship.

On the one hand, a public support makes funded firms less financially constrained and less in need to reinvest previous innovation returns into new ones. On the other hand, a public intervention provides firms with additional resources for continuing their pre-existing innovation.

Furthermore, persistence has emerged reinforced by the combination of different kinds of innovation strategies, for example, exploitative and explorative (Archibugi et al. 2013b).

The choice of excluding non-manufacturing industries (i.e., agriculture and services), whose innovative behaviors substantially differ from manufacturing ones, does not prevent us from inspecting the persistence of the core of the Italian system of innovation. Conversely, the exclusion of micro-firms, representing the largest share of the Italian firm population, might appear problematic. On the other hand, the idiosyncratic nature of these firms (e.g., rare events of formal innovation, nearly absent patent and/or R&D activities) would make their retention as much problematic in front of the complexity of the innovation process on which we focus in the paper.

In econometric terms, an “inflation” of dummies could possibly generate problems in reaching convergence of the estimates and/or in calculating the relevant covariance matrix. However, as we will see in the following, none of these problems emerged in our own application.

We have also tried to identify SMEs in a finer way, by combining their employees with their total turnover. However, as this would have implied a loss of around 600 observations out of 3300 because of missing values, we have finally decided to rely on the employees criterion only, noticing that its mean and standard deviation are nearly identical to those in terms of turnover.

Results are not reported here, but they are available from the authors upon request.

This procedure is similar to that applied by Triguero and Córcoles (2013) and Ganter and Hecker (2013) in the context of a dynamic non-linear random effect model. In the case of our dynamic random effect probit model, the use of a balanced panel, in which each firm is observed over three periods, ensures us that we are avoiding the risk of having a collapse of initial conditions and lagged dependent variables over the same period.

The interested reader is referred to this paper for a full analytic account of the estimation procedure, also in a context of selection.

Referring to the largest set of covariates, including also the time averaged ones (Wooldridge correction), the mean VIF value of the fully fitted models in Table 3 (see, Section 4) is 3.25.

A “weak” (strong) persistence would emerge when, with respect to the probability transition matrices of Table 2, the sum of the probabilities of the two states (1,1) and (0,0) is higher than 100%, and one (both) of the two probabilities is (are) less (higher) than 50%.

Because of space constrains, in the same table, we have omitted to report the results about the other controls than our focal independent variables. Full results are available from the authors upon request.

This interpretation is not free from caveats. One of them concerns the short period of time we are able to look at. Inferring a process of path dependence and cumulativeness of innovation over a period of around 10 years is a potential limitation of the present work, which will be overcome in the future through the utilization of data that span a longer period.

Moderation effects will be considered only with respect to these innovation typologies hereafter. Let us notice that, when SMEs is plugged in the estimates, the significance of L a g I n n o R a d P r o d increases.

The negative role that a small size has on the persistence of innovation in Italy would possibly be exacerbated should micro-entrepreises (less than 10 employees) included in the analysis: something that we have postponed to our future research.

The negative effect that we have found is different from the adverse impact that innovation subsidies can have, for example, in terms of productivity, for which see Catozzella and Vivarelli (2016).

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Titel: Innovation persistence in times of crisis: an analysis of Italian firms
verfasst von: Davide Antonioli
Sandro Montresor
Publikationsdatum: 09.08.2019
Verlag: Springer US
Erschienen in: Small Business Economics / Ausgabe 4/2021
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-019-00231-z

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