Mechanisms of Knowledge Sharing within the Industry Cluster

Literature Review

Introduction of the Two Levels Model of Knowledge Sharing

Geographical proximity only predisposes companies to the possibility of sharing information with others in a shared industry, whereby, on its own, geographical proximity is not a predictor of knowledge sharing among companies regardless of other industry and market factors they may be sharing. The factors that determine the extent of knowledge sharing in industry clusters are grossly understudied, which means that the mechanisms of the processes that encourage or discourage knowledge sharing are poorly understood(Ibrahim and Fallah 2005; Malmberg and Power 2005). In this regard, it is necessary to identify the other factors that promote knowledge sharing, which Mitchell, Burgess and Waterhouse (2010) identify in their research on knowledge sharing among clustered firms in a shared industry. However, spatial distance is not the only factor that determined the extent to which companies share the knowledge in their possession for purposes of mutual benefits, and Mitchell, Burgess and Waterhouse (2010) identify relational proximity as the other aspect of firm closeness that can determine knowledge sharing, especially in an emerging new industry cluster that is the focus of this study. Based on their findings, a model of study for this research has been formulated, the two level model, in which each aspect of proximity is treated as a knowledge sharing level on its own. One the level is the one determined by distance proximity, hereby referred to as the distance proximity level, and the other level is the one determined by relational proximity, hereby known as the relational proximity level. Secondary sources will be used to discuss the roles played by the two in determining the extent of knowledge sharing, discuss the mechanisms through which these levels operate, determine the relationship between the mechanisms of these levels, and identify the similarities and differences between the two levels.

Distance Proximity Level

Boschma R. A. (2005) Proximity and innovation: a critical assessment, Regional Studies39, 61-74. A key issue in economic geography is to determine the impact of geographical proximity on interactive learning and innovation. We argue that the importance of geographical proximity cannot be assessed in isolation, but should always be examined in relation to other dimensions of proximity that may provide alternative solutions to the problem of coordination. We claim that geographical proximity per se is neither a necessary nor a sufficient condition for learning to take place. Nevertheless, it facilitates interactive learning, most likely by strengthening the other dimensions of proximity. However, proximity may also have negative impacts on innovation due to the problem of lock-in. Accordingly, not only too little, but also too much proximity may be detrimental to interactive learning and innovation. This may be the case for all five dimensions of proximity discussed in the paper, i.e. cognitive, organizational, social, institutional and geographical proximity. Finally, the paper presents a number of mechanisms that offer, by their own, or in combination, solutions to the problems of coordination and lock-in. That is, they enhance effective coordination and control (solving the problem of too little proximity), while they prevent actors to become locked-in through ensuring openness and flexibility (solving the problem of too much proximity) (Boschma 2005).

Much literature suggests that knowledge-production activities are still heavily dependent upon geographically proximate sources of information, in spite of rapid development in telecommunications technology. Some analysts believe that the importance of proximity in knowledge production will eventually disappear with the continued development of telecommunications. The authors analyse patent citations and find that, after controlling for the existing distribution of knowledge-production activities, the proportion of local citations has increased over time. This finding reinforces the notion that in contemporary knowledge production and innovation the role for geographical proximity is increasing (Sonn and Storper 2008).

This paper analyzes the results of an empirical study involving 10 firms located in the Campos Basin oil & gas industrial agglomeration in Brazil. Within the last 20 years, this region has emerged from limited oil & gas competencies to a leading center for deep and ultra-deep offshore exploration and production capabilities, resulting in Brazilian energy self-sufficiency. Firms operate under intense technological dynamism, providing technologically complex goods and services to major oilfield operators in that region. Firms analyzed included wellhead equipment suppliers (‘wet christmas trees’), well service suppliers (well technology) and the highly influential national oil company, Petrobras. The analysis uses elements from the clusters and innovation systems approaches. The aim of this work is to determine the formation process and the actual characterization of the agglomeration and understand, from the perspective of the knowledge system and firms’ technological approaches, how technological changes are implemented in the Campos Basin agglomeration and the origins of such changes. As a secondary objective, this study attempts to verify whether geographical proximity is a factor that favors innovation by the firms within the agglomeration. Results indicate the existence of a group of firms in which geographical proximity has a positive influence on innovative activities (Silvestre and Dalcol 2009).

What role do various kinds of proximity play in the current and projected development of peripheral areas? In summarizing and drawing conclusions from this special issue on proximity, this paper elaborates on two core notions of proximity, geographical and organizational. It presents a framework in which the relationship between geographical and organizational proximity is conceptualized in a way that is somewhat different from previous contributions, notably by the French School on Proximity. The framework is used to evaluate the outcomes of the various contributions in this issue. The findings endorse the idea that economic performance relies more on localized capacities to build “global” connections, complemented with an adequate local resource base, than on local networking and clustering (Lagendijk and Lorentzen 2007).

The competitiveness of firms and regions is increasingly dependent on their capabilities to organise knowledge processes that unfold between different knowledge providers. In this article it is argued that this knowledge management in networks is a cognitive process that uses different dimensions of proximity. As much of the knowledge required is ‘tacit’ in character, ’embedded’ social interaction becomes crucial. There are, however, conflicts of interest in business networks. The organisation of knowledge processes thus becomes a complex governance task that depends to a large extent on the characteristics of the learning processes of the sectors involved. This paper offers some empirical evidence from the service sector with the case of M&A activities and from the manufacturing sector with the case of automobile design (Schamp, Rentmeister, and Lo 2004).

Relational Proximity Level

The geographical literature on communities of practice suggests that geographical proximity should not be confused with relational proximity, and that the latter is more important in determining how easily specialized knowledge can be jointly produced and shared through distributed innovation processes. However, the existing body of work has not specified the critical determinants of relational proximity, and the conditions under which we should expect it to be achieved effectively at a distance. This chapter reviews recent findings from a number of case studies in which distributed teams participating in joint problem-solving projects have attempted to engage in long-distance learning and knowledge translation, with varying degrees of success. Effective distanciated learning is shown to depend on the degree of social affinity between economic actors, and this affinity is comprised of several different dimensions: linguistic, educational, experiential, occupational, organizational, industrial, and institutional. The frictional effects of distance are also shown to depend on the types of knowledge supporting innovation in each case, with synthetic and symbolic forms of knowledge the least amenable to distanciated learning (Gertler 2008).

The proximity concept is used in many different ways in the literature. These dimensions of proximity are, however, defined and measured in many different (sometimes even contradictory) ways, show large amounts of overlap, and often are under- or over-specified. The goal of this paper is to specify the different dimensions of proximity relevant in inter-organizational collaboration more precisely and to provide definitions of these dimensions. The research presented contributes to reducing the ambiguity of the proximity concept as used in the literature.

Based on the above, the following research question is addressed in this paper: ‘Which dimensions of proximity are relevant in inter-organizational collaboration and how are they defined?’ A systematic literature review is presented in order to disentangle the dimensions of the proximity concept. Based on this literature review, three dimensions of proximity relevant in inter-organizational collaboration are distinguished: geographical proximity, organizational proximity and technological proximity. Examples (case studies) from the literature are used to illustrate the current conceptual ambiguity as well as to clarify how the proposed dimensions of proximity reduce this conceptual ambiguity (Knoben and Oerlemans 2006).

This article addresses the role of proximity for knowledge collaboration between dedicated biotechnology firms (DBFs) and related actors. Innovation projects managed by a selection of eight Swedish DBFs are analysed in detail and classified with regard to their specific knowledge characteristics. Based on this classification, explanations to the relative importance of functional and relational proximity to collaborators are sought.The findings indicate that knowledge collaboration in projects characterized by embodied knowledge are more sensitive to functional proximity than projects characterized by embrained and encoded knowledge. The findings also indicate that even though functional proximity is facilitative, global knowledge collaboration is indispensable for most DBFs. The convenience of local collaboration can never replace the extreme requirements of specialized knowledge, which forces them to seek collaborators on a global arena despite the impediments they face in these situations. Policy resources aimed at promoting bioregions are therefore better used to enhance local resources and to provide conditions for DBFs to link up with global sources of knowledge rather than to boost the formation of `second best’ local networks (Moodysson and Jonsson 2007).

Embeddedness in social networks is increasingly seen as a root cause of human achievement, social stratification, and actor behavior. In this article, we review sociological research that examines the processes through which dyadic ties form, persist, and dissolve. Three sociological mechanisms are overviewed: assortative mechanisms that draw attention to the role of actors’ attributes, relational mechanisms that emphasize the influence of existing relationships and network positions, and proximity mechanisms that focus on the social organization of interaction (Rivera, Soderstrom, and Uzzi 2010).

Embeddedness remains a central concept in much economic geographical thought for understanding how social factors influence economic activity. Recent commentators have argued for a reconceptualization that entails a relational and processual redefinition of the concept. This paper argues, however, that there remain deep-rooted epistemological problems with embeddedness that are not overcome by this emerging reconceptualization. It argues that the conceptual lexicon of embeddedness conflates economic action and outcomes, insufficiently captures power and agency and produces a limited understanding of the spatialized development of economic activity. It further argues that the language of embeddedness conceals dimensions to transnational business activity that require increasing theoretical attention in order to explain economic success or failure in the context of contemporary globalization. In contrast to those seeking to reconceptualize embeddedness, the paper thus argues for a relational and associational approach centred on tracing the practices that produce economic outcomes in the contemporary global space economy. This alternative approach draws on recent contributions to actor-network theory as well as relational and topological theorizations of the nature of power and knowledge in relation to economic activity. The arguments are grounded with reference to a series of examples drawn from research into the nature of contemporary transnational firms (Jones 2008).

Relationship between the Two Levels

Similarities between the two Levels

Discussion and Conclusion


Boschma, Ron. 2005. “Proximity and Innovation: A Critical Assessment.” Regional Studies 39 (1). Taylor & Francis: 61–74.

Gertler, Meric. 2008. “Buzz without Being There? Communities of Practice in Context.” Community, Economic Creativity, and Organization 1 (9). Oxford University Press Oxford: 203–27.

Ibrahim, Sherwat, and M Hosein Fallah. 2005. “Drivers of Innovation and Influence of Technological Clusters.” Engineering Management Journal 17 (3).

Jones, Andrew. 2008. “Beyond Embeddedness: Economic Practices and the Invisible Dimensions of Transnational Business Activity.” Progress in Human Geography 32 (1). Sage Publications: 71–88.

Knoben, Joris, and Leon A G Oerlemans. 2006. “Proximity and Inter‐organizational Collaboration: A Literature Review.” International Journal of Management Reviews 8 (2). Wiley Online Library: 71–89.

Lagendijk, Arnoud, and Anne Lorentzen. 2007. “Proximity, Knowledge and Innovation in Peripheral Regions. On the Intersection between Geographical and Organizational Proximity.” European Planning Studies 15 (4). Taylor & Francis: 457–66.

Malmberg, Anders, and Dominic Power. 2005. “(How) Do (firms In) Clusters Create Knowledge?” Industry and Innovation 12 (4). Taylor & Francis: 409–31.

Mitchell, Rebecca, John Burgess, and Jennifer Waterhouse. 2010. “Proximity and Knowledge Sharing in Clustered Firms.” International Journal of Globalisation and Small Business 4 (1). Inderscience: 5–24.

Moodysson, Jerker, and Ola Jonsson. 2007. “Knowledge Collaboration and Proximity the Spatial Organization of Biotech Innovation Projects.” European Urban and Regional Studies 14 (2). Sage Publications: 115–31.

Rivera, Mark T, Sara B Soderstrom, and Brian Uzzi. 2010. “Dynamics of Dyads in Social Networks: Assortative, Relational, and Proximity Mechanisms.” Annual Review of Sociology 36. Annual Reviews: 91–115.

Schamp, Eike W, Bernd Rentmeister, and Vivien Lo. 2004. “Dimensions of Proximity in Knowledge-Based Networks: The Cases of Investment Banking and Automobile Design.” European Planning Studies 12 (5). Taylor & Francis: 607–24.

Silvestre, Bruno dos Santos, and Paulo Roberto Tavares Dalcol. 2009. “Geographical Proximity and Innovation: Evidences from the Campos Basin Oil & Gas Industrial agglomeration—Brazil.” Technovation 29 (8). Elsevier: 546–61.

Sonn, Jung Won, and Michael Storper. 2008. “The Increasing Importance of Geographical Proximity in Knowledge Production: An Analysis of US Patent Citations, 1975-1997.” Environment and Planning A 40 (5). PION LTD 207 BRONDESBURY PARK, LONDON NW2 5JN, ENGLAND: 1020.


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