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Innovation in family and non-family SMEs: an exploratory analysis

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Abstract

This study provides an exploratory analysis of differences between family and non-family firms in innovation investment, product and process innovation outcomes, and labor productivity. Using data from the Community Innovation Survey on 2,087 German small- and medium-sized enterprises (SMEs), we observe significant disparities at each stage of the innovation process. Whereas family SMEs have a higher propensity to invest in innovation at all, conditional on investing in innovation, these companies do so less intensively than their non-family counterparts. Family SMEs further tend to outperform non-family SMEs in terms of process innovation outcomes when controlling for innovation investment. Given the level of product and process innovation, however, family SMEs underperform regarding labor productivity in comparison to non-family SMEs. These findings complement previous empirical research by illustrating how the presence of a dominant family relates to innovation inputs and outputs of SMEs in Europe’s largest economy and its innovative SME sector.

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Notes

  1. According to the Stiftung Familienunternehmen (2011), the share of family firms in Germany (based on the definition that a family owns the majority of shares or votes in a firm) varies as follows across different size classes (number of employees): 0–9: 94 %, 10–49: 85 %, 50–249: 58 %, 250–499: 36 %, and >500: 27 %.

  2. See Mairesse and Mohnen (2010) for an overview of recent studies using the CDM model.

  3. In accordance with the CIS, we define innovation expenditures as money spent on internal and external R&D or the acquisition of external resources to realize innovation projects.

  4. To check the robustness of our results, we reran the entire model adopting the definition of SMEs used in the US (10–500 employees). The sample size increases from 2,087 to 2,323 firms but there is no qualitative difference in the results; all family SME effects are confirmed.

  5. Specifically, this encompasses all internal and external R&D expenditures, acquisition of advanced machinery, facilities, software and external knowledge to realize innovation projects, product design, construction, design of services and other preparations for the production/sale and distribution of innovations, internal or external training specifically for innovation projects, and launch of innovations onto the market (marketing campaigns directly linked to product innovations). Organizational innovation is not included.

  6. Without any loss of generality, we assume that the threshold is zero.

  7. Using the same set of regressors in the selection and the outcome equation of the Heckman model requires the selection equation to be non-linear (Cameron and Trivedi 2010). Testing for this we found clear evidence for non-linearity indicating that the identification of our model need not rely on exclusion restrictions.

  8. Even 20 years after reunification, structural economic differences still persist between the formerly separate entities of East and West Germany. Hence, we control for these regional differences within our analysis.

  9. In addition to the variables discussed in the text, we have included dummy variables for several control variables that indicate missing values. In all cases, when the missing values indicator has a value of one, the corresponding variable is coded zero.

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Authors and Affiliations

  1. School of Business and Economics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands

    Nicolas Classen, Martin Carree & Anita Van Gils

  2. Centre for European Economic Research (ZEW), P.O. Box 103443, 68034, Mannheim, Germany

    Bettina Peters

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  1. Nicolas Classen
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Classen, N., Carree, M., Van Gils, A. et al. Innovation in family and non-family SMEs: an exploratory analysis. Small Bus Econ 42, 595–609 (2014). https://doi.org/10.1007/s11187-013-9490-z

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