Abstract
It is known that small firms rely mainly on the CEO’s individual knowledge for developing innovations. Recent work suggests that this approach is inefficient since it underutilizes other employees’ knowledge. We study to which extent using CEOs, managers and non-managerial employees’ ideas enhances small firms’ innovation performance. A Heckman selection model on 305 small firms shows that not only CEO’s and managers’, but also non-managerial employees’ ideas contribute to innovation performance. However, contributions depend heavily on the individuals’ area of expertise and on whether product or process innovation is desired. Our findings enrich the current view on the entrepreneurial team, but also warn against the implementation of one-size-fits-all employee involvement programs in small firms.
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Notes
While a critical portion of knowledge and skills resided with individuals, it must be noted that innovation is a collective achievement (Kogut and Zander 1992; Cohen and Levinthal 1990). Organizations accumulate and store individual knowledge for collective use (Garud and Nayyar 1994) and establish structures and procedures to streamline individual ideas into streams of innovative outcomes (Cooper 2001; Allen 1977; Kogut and Zander 1992, 1993, 1996; Nonaka and Takeuchi 1995; Spender 1996; Conner and Prahalad 1996; Zander and Kogut 1995; Nahapiet and Ghoshal 1998).
Some studies on SMEs also find a positive relationship between employees’ human capital and sophisticated HRM practices on the one hand and firm performance on the other hand (Hayton 2003; Way 2002; Maes et al. 2005; Sels et al. 2006; Rauch et al. 2005). However, they all model financial performance or non-financial outcomes other than innovation. In these studies, the effect of employees’ human capital on firms’ innovative performance is assumed, but not tested.
This response rate is highly comparable with general response rates for surveys of German firms. For example, the Third Community Innovation Survey had a 21 % response rate in Germany (Eurostat 2004).
The survey asks whether ideas were used in the innovation process. This implies that firms who respond affirmative must at least have planned to innovate in some form. Therefore, we want to control for the fact that a firm engages in innovation at all. This is achieved by estimating a Heckman selection model. If one would estimate the performance equation only on firms that actually innovate, one would possibly overestimate the average innovation performance as those companies with no innovation would not be included in the sample (data censoring problem). This problem can be tackled by the application of the sample selection model as the performance equation will contain a variable that controls for the correlation between the likelihood to innovate and the innovation performance.
The FIML procedure estimates the two equations jointly, instead of first estimating the propensity to innovate and then subsequently estimating the innovation performance equations separately.
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Czarnitzki gratefully acknowledges financial support from the Flemish Science Foundation (FWO, Grant G.0282.10). We also thank the ZEW Mannheim for providing the data access and Alfred Spielkamp for helpful comments.
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Andries, P., Czarnitzki, D. Small firm innovation performance and employee involvement. Small Bus Econ 43, 21–38 (2014). https://doi.org/10.1007/s11187-014-9577-1
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DOI: https://doi.org/10.1007/s11187-014-9577-1