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Does external R&D matter for family firm innovation? Evidence from the Italian manufacturing industry

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Abstract

This article focuses on the relationship between external R&D and firm innovation output. Using a sample of Italian manufacturing firms over the period 2007–2009, we estimate the effect of R&D collaboration with the aim to detect differences between family and non-family firms. The study shows that the R&D acquired from external sources has a positive impact on innovative sales, especially for family firms. This result holds when using either the extensive or the intensive margins of R&D collaboration, thereby suggesting that family companies have a greater capacity to translate external R&D into tangible economic benefits. We also find that family firms benefit from the diversity of R&D collaboration.

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Notes

  1. Along this line of reasoning, Haeussler et al. (2012) point out that new high tech companies could join alliances under unfavourable conditions that could increase the risk of expropriation of the firm’s own knowledge, undermining the new firms’ competitive position.

  2. The importance of internal social capital for absorptive capacity has been highlighted by several authors. For instance, Gkypali et al. (2018) find that the absorptive capacity plays an important role in fostering the effect of external R&D of Greek firms. It has also been proved that the relationships between organizational members can reduce transaction costs, facilitate information flows, knowledge creation and accumulation (Burt 2000; Lin, 2001; Nahapiet and Ghoshal 1998). Arregle et al. (2007) and Patel and Fiet (2011) argue that personal relationships, trust and intra-firm cooperation are important characteristics in FFs also to combine better than non-family firms the existing tacit knowledge with the external knowledge. This can constitute a valuable source of competitive advantage compared to non-family firms (Pearson et al. 2008; Hoffman et al. 2006). However, some factors—such as rivalries and family conflicts—can make FFs less capable of transforming external knowledge into internal benefits (Chirico and Salvato 2008).

  3. With respect to the external social capital, it is well-known that it involves significant market knowledge and stronger relationships with clients, thereby contributing to increases alliance success (Ireland et al. 2002; Koka and Prescott 2002). These elements allow firms to quickly detect market niches and adapt new technologies to the needs of clients (Uhlaner et al. 2013). This ensures that innovative collaboration is aimed at obtaining products that adapt to specific customer requirements, making collaborative innovation a commercial success. Furthermore, external collaboration may supply the firm with resources that are not available internally, thereby overcoming resource constraints shaped by their governance structures and size (e.g. Carney 2005a). Also, external collaboration mitigates the low propensity to use investment capital to fund innovation projects (Block et al. 2013), thus avoiding the loss of control (e.g. Gómez-Mejía et al. 2007).

  4. In more detail, Muñoz-Bullón et al. (2019) find that when performance is below the aspiration levels that compromise firm survival, FFs show a higher propensity to give priorities to financial goals over family-centred noneconomic objectives, with positive consequences on innovation performance from combined R&D. The negative effect of combined R&D on family firm performance found by Diéguez-Soto et al. (2019) is due to the presence of unskilled human capital, usually linked to family-managed firms, which is unable to appropriately integrate external and internal R&D. It is also explained by the intrinsic uncertainty and loss of control often attached to R&D investments that do contribute to disjoin economic and non-economic goals (Duran et al. 2016).

  5. The firms included in the dataset were selected using a sampling design that stratifies companies by industries (11-NACE classification), regions (NUTS-1 level of aggregation) and size class (10–19; 20–49; 50–250; more than 250 employees). The dataset comprises a significant amount of quantitative and qualitative information, covering the firm’s proprietary structure, workforce, investment, innovation, internationalisation, finance, market and pricing. See Altomonte and Aquilante (2012) for an in-depth description of the dataset.

  6. Besides the regressors included in Equation (1), in the first step of Woldridge’s (2002) procedure, we have estimated a probit and a two-limit tobit models by including the following variables: a dummy equal to one if the firms benefitted from tax allowances and financial incentives for R&D activities; a dummy for human capital, i.e. equal to one if the firm has a higher share of graduate employees with respect to the national average share of graduates; short term bank debt (%); medium- to long-term bank debt (%); and regional fixed effects. Wooldridge’s (1995) robust scores tests obtained when all firms and the two subsamples of family and non-family enterprises are considered are 2.793, 2.783 and 5.097, respectively. This evidence suggests that the exogeneity of the two variables cannot be rejected at 5% level.

  7. In foreign markets firms get access to the diversified knowledge, gain cross-country income and acquire patents, which increase the likelihood of innovativeness of exporters (Bratti and Felice 2012). Moreover, exporting firms broadens the international customer base, specifically when foreign markets are more competitive and innovative than the domestic ones (Lu and Beamish 2006; Castellani 2002). However, the related literature provides mixed results on the causality between exports and innovation. In this regards, an unifying framework for studying the complex relationship between firms’ innovation and exporting activity is developed by Gkypali et al. (2015); Gkypali et al. (2018).

  8. A number of checks have been performed in order to verify the robustness of results. For instance, we have investigated the role of the degree of family participation in the supervisory and management board, as they are important factors of heterogeneity in FFs (Chua et al. 2012; Matzler et al. 2015; Miller et al. 2014). Additionally, we replace R&D intensity with a dummy equal to one if the firm carried out internal R&D over the last 3 years, and zero otherwise. Results are available upon request.

  9. Similarly to other studies (García-Quevedo et al. 2014;Pellegrino and Piva 2020; Segarra-Blasco and Teruel 2016), here, our purpose is to identify any difference that might exist between groups (FFs vs non-family firms) in terms of the impact of explanatory variables on outcome. We have tested if there is a difference between the marginal effects of External R&DINT of FF vs non-family firms using the pwcompare STATA command. The test shows that there is no difference between the two average marginal effects of External R&DINT displayed in columns 4 and 6 of Table 4.

  10. See footnotes 2 and 3.

  11. Here and below, it is useful to remember that the results of non-family enterprises must be interpreted with caution since the non-family firms that carry out research with external partners are few, that is 93 (less than 12% of the sample) and only 19 firms have R&D collaborations jointly with universities and other firms.

  12. The openness of firms’ external search processes may be measured through two concepts (Laursen and Salter 2006). The first concept refers to external search breadth and is the one we use in our analysis. The second concept refers to external search depth and it is defined in terms of the extent to which firms draw deeply from the different external sources to increase performance (Chen et al. 2011; D’Ambrosio et al. 2017; Ferreras-Méndez et al. 2015; Kobarg et al. 2019). Unfortunately, we cannot insert in the analysis an indicator of the intensity of R&D collaboration because of data limitation. This issue is left for next research.

  13. Breadth refers to the different types of partners with which innovating firms associate to sustain and increase performance (Chen et al. 2011). Previous studies included a lot of types of potential external partners (D’Ambrosio et al. 2017; Ferreras-Méndez et al. 2015; Kobarg et al. 2019; Laursen and Salter 2006) such as other organisations within the business group; competitors and other enterprises from the same industry; suppliers of equipment, materials, components or software; clients or customers; consultants; laboratories or R&D companies; universities or other higher education institutes and government or private non-profit research institutes. Our database considers only the R&D partnership with Universities/research centres and with other firms.

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Authors and Affiliations

  1. Department of Economics, Statistics and Finance “Giovanni Anania”, University of Calabria, Arcavacata di Rende, (Cosenza), Italy

    Francesco Aiello, Paola Cardamone, Lidia Mannarino & Valeria Pupo

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  1. Francesco Aiello
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  2. Paola Cardamone
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  3. Lidia Mannarino
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  4. Valeria Pupo
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Correspondence to Francesco Aiello.

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Aiello, F., Cardamone, P., Mannarino, L. et al. Does external R&D matter for family firm innovation? Evidence from the Italian manufacturing industry. Small Bus Econ 57, 1915–1930 (2021). https://doi.org/10.1007/s11187-020-00379-z

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  • DOI: https://doi.org/10.1007/s11187-020-00379-z

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