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Determinants of innovativeness in SMEs: disentangling core innovation and technology adoption capabilities

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Abstract

This paper studies innovativeness in SMEs from a set of innovation indicators at the firm level, capturing various types of innovation (product, process, organisational, and marketing innovations) and the level of innovativeness in these firm’s developments. The article identifies two separate dimensions in the innovativeness of Spanish SMEs, using factor analysis techniques. One dimension is associated with the capabilities for core/internal innovation and the other with the capabilities for the adoption of technology. The paper shows that significant differences exist in the personal and organisational factors that favour these two dimensions. The entrepreneur’s motivation, business planning, and cooperation in R&D activities constitute significant factors when considering the core dimension of a firechnology adoption. However, the use of external consultancy services seems to have no significant effect on the core dimension of the innovativeness of an SME, whereas it is a relevant factor for its technology adoption. Furthermore, it is shown that the entrepreneur’s education plays a more significant role in the core dimension of a firm’s innovativeness than in its capabilities for technology adoption. Depending on the policy objectives, these differences should lead to the application of specific policy approaches when an attempt to stimulate innovation in SMEs is made.

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Notes

  1. Other types of motivation were also considered in the survey, but are omitted from the analysis since they produced no significant results.

  2. The survey also included questions regarding the role of competitors and suppliers as sources for innovation, in addition to the collaboration with clients. The possible influence of these variables was tested, but the coefficients turned out to be non-significant. Hence, these variables were removed from the final results presented herein.

  3. The value of the Kaiser–Meyer–Olkin statistic is 0.782 and the Bartlett’s sphericity test shows a significant value for the Chi square, confirming that the correlation matrix is non-random.

  4. The condition indices are lower than 20, so there is no serious problem of multicollinearity in the analysis.

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Acknowledgments

This article is part of the “Excellence” Research Project entitled “Analysing the qualitative aspects shaping the quality of entrepreneurs and SMEs: Implications for the economic development of the Spanish Regions” (P09-SEJ-4857), funded by the Regional Government of Andalusia (Spain) with the support of the European Regional Development Fund (ERDF). The article has also benefited from the Project entitled “Tourism SMEs, Global Value Chains and Innovation” (ECO2013-42889-P) funded by the Spanish Ministry of Economy and Competitiveness (National Plan for Scientific and Technical Research and Innovation).

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  1. Department of Applied Economics, Faculty of Economics and Business Sciences, University of Seville, Av. Ramón y Cajal, 1, 41018, Seville, Spain

    Juan A. Martínez-Román & Isidoro Romero

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  1. Juan A. Martínez-Román
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Correspondence to Juan A. Martínez-Román.

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Table 6 Correlation matrix for the innovation indicators
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Martínez-Román, J.A., Romero, I. Determinants of innovativeness in SMEs: disentangling core innovation and technology adoption capabilities. Rev Manag Sci 11, 543–569 (2017). https://doi.org/10.1007/s11846-016-0196-x

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