ABSTRACT
We propose and test a deliberate innovation management model for small and medium enterprises (SMEs) reconciling the “cognition-action” logic underlying the knowledge management and innovation literature and the “intention-action” logic underlying Mintzberg and Waters’s deliberate strategy perspective. Consistent with a proposed “cognition-intention-action” logic, the empirical results from a sample of 633 Dutch SMEs support our predictions. SMEs that deliberately scan external information (via external knowledge acquisition practices) and distribute, interpret, and create internal knowledge (via internal knowledge-sharing practices) are more likely to enhance their innovation orientation and in turn, their innovation performance. Our study advances current understanding of innovation management, including the role of both external and internal knowledge management (KM) practices and also the value of considering innovation orientation in the overall innovation process. Our findings also offer some practical implications for SMEs to enhance their innovation ability.
Notes
1 To avoid diluting the focus, we intentionally exclude other innovation performance classifications, such as process innovation, organizational innovation, management innovation, and commercial/marketing innovation (Trott, Citation1998). In accordance with Johannessen et al. (Citation2001, p. 26), the critical dimension of innovation (for SMEs) is the variation in newness or novelty, and thus the distinction between types of innovation is less important.
2 As a further precaution for internal consistency, we checked the mean and frequency of the interitem correlations, which all ranged between .2 and .4, and can also be used to check for internal consistency (Briggs & Cheek, Citation1986; Vaske et al., Citation2016).
3 We also examined a four-factor model in which both external knowledge acquisition and internal knowledge sharing are combined into one factor. This four-factor model showed a poor fit with the data with an χ2 of 399.34 (df = 223), p < .01, RMSEA = .03, SRMR = .04, CFI = .93, and TLI = .92. Relatedly, we also examined a four-factor model in which both innovation orientation and innovation performance are combined into one factor. This four-factor model also showed a poor fit with the data with an χ2 of 398.44 (df = 223), p < .01, RMSEA = .03, SRMR = .04, CFI = .93, and TLI = .92. The hypothesized measurement model therefore demonstrates superior fit to comparison models. (Results of the other nested models are available upon request).