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PurposeThe 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.Design/methodology/approachThe 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.FindingsFindings show that external knowledge acquisition takes place through three different processes that raise important differences and similarities with the SECI model.Research limitations/implicationsConclusions 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.Practical implicationsThe 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.Originality/valueIn 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.

PurposeThe present paper seeks to provide a new insight into intellectual capital classification by theoretically and empirically differentiating relations‐based knowledge into social capital and relational capital. Additionally, taking into account the key role played by radical innovation to compete in the context defined by the “knowledge‐based economy”, the aim is to empirically investigate the possible effect of both relations‐based intellectual capital components on the development of this kind of innovation by firms.Design/methodology/approachData were obtained from a questionnaire responded to by 251 Spanish high and medium‐high tech firms. Based on their answers, exploratory factor analysis and regression analysis are carried out.FindingsAs theoretically proposed, relations‐based intellectual capital can be separated into social and relational capital, with social capital as the main component. Both elements have a significantly positive influence on radical innovation developed by firms in the sample, although those relationships maintained with external agents seem to have a higher impact.Originality/valueThe research contributes to the intellectual capital field by integrating the arguments provided by social capital literature and empirically separating relations‐based knowledge into two differentiated components. The paper also contributes to the knowledge management field by highlighting the important role played by knowledge emerging from relationships around the firm (both internal and external) in the development of radical innovation, whose antecedents have received little attention in the literature.

Purpose – The aim of the paper is to identify the different directions of external knowledge search and to investigate their individual effect on performance at the firm level. Design/methodology/approach – The empirical study is based on survey data gathered from two distinct informants of 248 large- and medium-sized high-tech manufacturing Spanish firms. In dealing with concerns on simultaneity and reverse causality, perceived time-lags among dependent and independent variables were introduced. Quantitative methods based on questionnaire answers were used. Findings – Findings reveal six distinct external search patterns and indicate that, while market sources such as customers and competitors are positively associated with performance, knowledge acquired from general information sources, other firms beyond the core business and patents and databases have no significant effect. Moreover, knowledge obtained from science and technology organizations and from suppliers displays an inversed U-shaped effect on firm performance. Research limitations/implications – Conclusions can only be generalized to high-tech manufacturing firms from developed countries and, although well-established methodological procedures were followed, the nature of the study remains cross-sectional. Yet, an important implication emerges from this work: more openness to external knowledge is not always better. It is necessary to carefully evaluate the potential gains and pains of each type of partner and source. Practical implications – This research provides guidance to managers about how to shape their companies’ inter-organizational networks, i.e. the specific external agents on which they should focus, as well as the efforts they should devote to each of these key partners. Originality/value – By considering distinct directions of external knowledge search instead of a single dimension, the paper contributes to shed some more light to the mixed results reported by the scarce empirical studies that have investigated the effect of openness towards external knowledge on performance at the firm level.

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