The purpose of this paper is to try to assess the applicability of the SECI model (Nonaka and Takeuchi) to the processes of external knowledge acquisition for firms located on knowledge‐intensive clusters. The paper's intended contribution lies in improving our understanding about the different mechanisms that organizations can use to learn from this kind of environment.
The paper uses survey data obtained from a sample of knowledge‐intensive firms from Boston's Route 128, with custom tailored measurement scales. It applies a quantitative method based on questionnaire answers.
Findings show that external knowledge acquisition takes place through three different processes that raise important differences and similarities with the SECI model.
Conclusions can only be generalized to firms located in knowledge‐intensive clusters. Nevertheless, some implications for management practice can be derived. Tacit knowledge from the environment requires different mechanisms in order to be successfully incorporated into the organization, whereas explicit knowledge acquisition can be managed more smoothly. Managers should pay special attention when designing channels for acquiring external tacit knowledge.
The SECI model reveals itself to be a powerful guide for starting research about external knowledge acquisition. Nevertheless, context specific variables can show industry or country preferred ways for learning in practice, so highly focused empirical research may be required to disentangle the peculiarities of tacit knowledge.
In the field of external knowledge acquisition by organizations, empirical works about testing widely spread theoretical models are very scarce. This paper takes the theoretical processes of the SECI model and extends them for external knowledge acquisition.
López‐Sáez, P., Emilio Navas‐López, J., Martín‐de‐Castro, G. and Cruz‐González, J. (2010), "External knowledge acquisition processes in knowledge‐intensive clusters", Journal of Knowledge Management, Vol. 14 No. 5, pp. 690-707. https://doi.org/10.1108/13673271011074845Download as .RIS
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