Knowledge Spillovers in different Dimensions of Proximity

Knowledge Spillovers in different Dimensions of Proximity 

Wiebke Lang 

University of Bremen, Institute Labour and Economy 

Paper presented at the Regional Studies Association International Conference 

“Regional Growth Agendas”, 28 th May to 31 st May 2005 in Aalborg 

Gateway 5 “Meaning and Role of Proximity” 

Contact: 

Dipl. Ing 

Wiebke Lang 

University of Bremen | IAW (Institute Labour and Economy) 

Parkallee 39 

28209 Bremen 

Germany 

phone: +49 (0)471 218 7273 

fax: +49 (0)471 218 2680 

email: wlang@iaw.uni-bremen.de 

url: www.iaw.uni-bremen.de

Knowledge Spillovers in different Dimensions of Proximity Wiebke Lang 

Knowledge Spillovers in different Dimensions of Proximity 

At a first glance proximity seems to be a very meaningful concept, as it has found its way into 

many policy concepts for regional development. Most regional, national and supranational 

development programs for regional growth elaborate factors such as the proximity of university 

and high-tech firms, the proximity of researchers or the proximity of similar sectors of 

economic activity. 

Taking a closer look, proximity looses meaning. Theoretical and empirical approaches use the 

concept in many dimensions: organisational, technological, industrial, cultural, geographical, 

cognitive, institutional proximity. Without being exact about the dimension used, proximity is 

what Ann Markusen (1999) would call a fuzzy concept. 

Nevertheless, in all these dimensions proximity apparently plays a significant role for the innovativeness 

of economic actors, because it promotes and facilitates knowledge spillovers. 

“Proximity in geographical, industrial, and technical space matters here in that it provides 

reluctant and sceptic, risk-adverse adopters the opportunity to assess the actual profitability 

of the new technology and hence to adopt it.” (Antonelli 2003: 9-10) A central question is 

therefore the relationship between geographical proximity and other dimensions of proximity. 

Do they serve as substitutes or as complements to geographical proximity (Boschma 2005) 

and how does this relationship influence knowledge spillovers and regional growth. 

Undertaking research on knowledge spillovers faces the problem that no concluding theory of 

the innovation process exists that could explain the causes, impacts and distribution mechanisms 

of knowledge spillovers in macroeconomic terms. Research on the allocation and distribution 

of the classic factors of production land, capital and labour have a long tradition. 

Knowledge as an essential production factor found only sporadic attention for example by 

Marshall 1890 or Hayek 1945. Inasmuch as the western industrial countries found themselves 

loosing ground competing in the classic factors of production, the ‘new’ production factor 

knowledge as their competitive advantage was discovered. Accordingly, research on the role 

of knowledge extensively took up. 

Since the mid 90ies an astonishing thing can be observed. Research results are often greedily 

taken up by policy measures although concluding evidence is still missing. And research uncritically 

takes up poorly conceived ideas, legitimising the policy concepts ex post. “The lack 

of precise understanding is in stark contrast to the many policies and policy oriented concepts 

that attempt to utilize the positive impulses of knowledge spillovers.” (Maier & Sedlacek 

2005: 1) 

Especially the thesis that spatial proximity facilitates the distribution and accumulation of the 

alleged only competitive advantage knowledge, finely fits into policy concepts, that demand 

more responsibility of regions and cities for their own economic welfare. This on the one hand 

Regional Growth Agendas 28th to 31st May 2005, Aalborg 2


allows central institutions to offload responsibility and redistribution requirements. On the 

other hand it is a tribute to the decrease of steering capacity in the face of growing complexity. 

In effect regional competition is furthered thereby accepting increasing divergence between 

regions. 

So the precise understanding of the meaning of spatial proximity for knowledge spillovers and 

the way these insights are fed into policy concepts are crucial. The accurate definition of 

mechanisms and proximity dimensions facilitating knowledge spillovers is necessary to identify 

the endogenous potential of regions to facilitate knowledge driven economic processes. 

Additionally remaining demands for redistribution and central governing can be specified to 

enable an overall cohesive development process. 

Taking a closer look at the original theories I will firstly work out what contribution the three 

central theories actually make to the meaning of proximity for knowledge spillovers. This will 

be followed by an definition of four dimensions of proximity that provide essential explanation 

of the mechanisms responsible for knowledge spillovers. The analysis of their relationship 

will show what role spatial proximity really plays for knowledge spillovers. 

Proximity in the New Growth Theory 

The New Growth Theory shows, that the input of knowledge in the production process provokes 

increasing returns. These do not occur to the advantage of a single firm or human being, 

but to an industry or to an economic system altogether. Taking localisation and urbanisation 

economies into account, it is postulated, that not every actor benefits from these increasing 

returns, but those who are in proximity to the knowledge producer. Being near the 

knowledge producer is an advantage because there are greater possibilities to watch, learn 

and judge the new ideas. The higher the proximity between actors is, the lower are transaction 

and communication costs. By having the possibility to learn and anticipate new ideas 

quicker than competitors in greater distance, proximity turns out to be a competitive advantage. 

This is empirically tested with the knowledge production function. Most research results are 

supportive of this thesis, as they find a statistical inter-correlation between the density or 

amount of knowledge input (researchers, universities…) and innovation output (patent, new 

products…). But the statistical interrelationship does not prove an interdependence of spatial 

proximity of knowledge input and innovation output. 

The authors of the New Growth Theory find, that there are two components of knowledge: a 

codified form and a technological form. The term technological knowledge indicates, that this 

kind of knowledge exhibits technological external economies of scale. In effect “for an individual 

firm, average costs per unit of output decrease with growing output at the industrywide 

level.” (van Stel & Nieuwenhuijsen 2004: 405, note 2) In order to benefit from knowl- 



edge spillovers as technological externalities ‘industrial proximity’ is necessary. This means 

the production processes of two economic actors must comply to some degree with each other 

so that the appropriation of knowledge spillovers is possible. 

The technological component of knowledge in the New Growth Theory is generally identified 

as tacit knowledge. Tacit knowledge is known to be transferred face-to-face. This gives the 

explanation for the statistical inter-correlation of innovation input and innovation output 

accounted for by using the knowledge production function. A theoretical explanation for the 

statistical interrelationship is found, so that interdependence can be postulated. 

But tacit knowledge and technological knowledge are not the same things. It is central to the 

New Growth Theory that technological knowledge features the properties of externalities. Only 

if the knowledge spillovers are externalities they can contribute to a knowledge stock from 

which a whole industry or a regional economic system can benefit. Externalities are non rival 

and non-excludable in consumption, and they are not transferred intentionally nor mediated 

by the price mechanism. This means they are accessible for anyone at any time and any place. 

Without this assumption knowledge in the production process could not generate increasing 

returns. 

Table 1: Knowledge as Externalitiy and Tacit Knowledge 

Knowledge as Externality 

non-rival 

non-excludable 

un-intentional dissemination 

no price mechanism 

Tacit Knowledge 

partly rival 

partly excludable 

intentional dissemination 

no price mechanism 

In contrast tacit knowledge does not necessarily show these attributes. Tacit knowledge is 

embedded in human capital or in other production factors. Therefore it must at least partly 

take on their properties. But the human capital of labourers or the expertise incorporated in 

machines are ordinary private goods. Hence rivalry will characterise at least to some extent 

the transference of tacit knowledge and maybe interested economic actors will be excluded. A 

person who carries tacit knowledge cannot convey it independently of his or her location nor 

will the person convey it to anyone regardless of the relationship between him and the person 

interested in acquiring the tacit knowledge. 

Nevertheless the appropriation of technological knowledge and of tacit knowledge is costly. 

The transactions costs the recipient must raise can be reduced by spatial proximity. In the 

logic of tacit knowledge the cost reduction by generating spatial proximity is possible because 



it can only be transferred face-to-face. Spatial proximity is then a prerequisite for the distribution 

of knowledge. 

In the logic of technological knowledge the higher probability of meeting and communicating 

leads to reduced transaction costs in spatial proximity. So being located in a density of economic 

actors can be a competitive advantage. But as far as the New Growth Theory is concerned 

only industrial proximity is a prerequisite for the distribution of knowledge spillovers. 

The mutual understanding and consistency of production specifications are necessary to benefit 

from knowledge spillovers. 

Proximity in the Evolutionary Theory 

The Evolutionary Theory also assumes that increasing economies of scale are generated by 

dynamic, technological externalities of scale, which show their impact only in an industry as a 

whole. Unlike static externalities, knowledge spillovers as dynamic externalities continuously 

have influence on production costs and conditions of other economic actors. Knowledge exhibits 

dynamic externalities, because of its cumulative character. The fact that new knowledge 

builds upon knowledge acquired previously and by others, means that the production function 

of different firms in the economic system are dependent on each other. Returns on investments 

in knowledge can only be appropriated by the industry as a whole not by a single actor. 

So also the Evolutionary Theory postulates what I have coined earlier industrial proximity as 

an important feature enabling knowledge spillovers. 

An industry which features not only industrial proximity but also spatial proximity, in other 

words an industry agglomeration, can form a local monopoly by internalising the dynamic 

technological externalities. The proximity between the economic actors is then so high, that 

their combined knowledge forms a local knowledge stock. 

The regional economy is able to appropriate monopoly rents because of the mechanisms of 

cumulative causation which come to effect in agglomerations. Here the industrial effects of 

cumulative causation described by Myrdal and Perroux work together with the cumulative 

character of knowledge. Knowledge spillovers appear in the Evolutionary Theory as a specific 

type of agglomeration effect. This means they can occur in agglomerations but spatial proximity 

is no sufficient condition for knowledge spillovers. 



Figure 1: Knowledge Spillovers in the Systematic of Agglomeration Effects 

Agglomeration Effects 

Agglomeration Economies 

Agglomeration Diseconomies 

static 

(Pooling; Market size) 

dynamic 

(Knowledge Spillover) 

Congestion Pollution High Rents 

Internal Effects 

(in the firm) 

External Effects 

(between firms) 

Localisation 

Economies 

Urbanisation 

Economies 

Marshall-Arrow- 

Romer Externalities 

(same industry) (different Industries) (between firms of 

the same industry) 

Jacobs Externalities 

(between firms of 

different industries) 

Location and Division of Labour 

Growth and Productivity 

The cumulative character of knowledge makes cognitive proximity of the firms and the individual 

human capital of their employees a prerequisite for knowledge distribution. Without 

having a similar knowledge level I will not be able to understand new knowledge being presented 

to me. In terms of firms appropriating knowledge spillovers, cognitive proximity also 

means complying with a certain composition of production factors. Otherwise the appropriation 

of the new ideas is not possible or too costly. I will coin this compliance of production 

factor composition technological proximity 1 . If human capital relies on cognitive proximity, 

firms rely on technological proximity. 

As prerequisite for knowledge spillovers the Evolutionary Theory points out industrial proximity 

and cognitive or technological proximity depending on who is communicating firms or 

individuals. Spatial proximity alone does not have any effects. But coinciding with the other 

two proximity effects it may generate monopoly rents for a regional industry agglomeration. 

Network Theory 

In the Network Theory knowledge is distributed in systems of relationships. Their construction 

is facilitated by spatial proximity and in spatial proximity special modes of relationships are 

shaped. Especially the exchange of tacit knowledge requires direct face–to–face relationships. 

Spatial proximity allows frequent encounters which produce common identity, reputation and 

1 

Giovanni Dosi asserts that firms potentially adopting knowledge do not, because they simply lack the technological 

and organisational capabilities to do so. These factors influencing the diffusion of innovation relate to 

technological asymmetries between firms. (Dosi 2000(1991): 123) 



trust. In relationships characterised by mutual trust the knowledge distributed and saved in 

them is a public good — a regional knowledge stock. On the regional level different forms of 

relationships can be shaped because the reputation of economic actors is known and opportunistic 

behaviour is impeded. 

In the concept of innovative milieu, it is differentiated between two sets of effects operating 

simultaneously: proximity effects, such as reductions in costs because of quicker circulation of 

information, face-to-face contacts, and lower costs of collecting information; and socialization 

effects, related to collective learning, cooperation, and socialization of risks. (Malecki & Oinas 

1999: 7) 

Although it is emphasised, that these effects are collective rather than explicitly cooperative, 

bilateral relationships are the fundament which make it possible for the milieu effect such as 

knowledge spillovers to spread beyond any single bilateral inter-firm linkage. Knowledge 

Spillovers as externality are bound to a specific composition of economic actors. The knowledge 

stock presents itself as a system of connected elements. 

“The space or territory of a milieu embodies the actors, their interactions and relationships a 

multifaceted system that the metric of distance alone is unable to capture." (Malecki & Oinas 

1999: 7) 

So it is very important to keep in mind, that the regional knowledge stock is bound to relationships 

and is in this respect no real public good. It is not accessible to anyone in a region, 

but only to those economic actors involved in certain (regional) networks. Economic actors in 

spatial proximity are excluded from the knowledge stock by lacking cognitive proximity. Not 

the spatial proximity, but the direct connection between actors incorporating relevant knowledge 

provides for the dissemination and production of new knowledge. Nevertheless the Network 

Theory assumes that in spatial proximity more and better linkages between economic 

actors exist, which form the competitive advantage of spatial proximity for knowledge intensive 

processes. 

But the emphasis on relationships introduces another proximity dimension I will term behavioural 

proximity. Behavioural proximity is a set of rules and routines — explicit or implicit — 

which allow individuals to be co-ordinated without having to define beforehand how they 

must do it. Behavioural proximity comprises the non-market content of relationships. In that 

way it describes the variety of concepts such as untraded interdependencies (Storper 1995), 

relational capital (Storper 1997), social capital (Putnam 1993), institutional thickness (Amin 

& Thrift 1994) etc. 

In the Network Theory spatial proximity is effective only if it coincides with the existence of 

relationships. “Whereas at the opposite extreme, one can imagine individuals developing informal 

interactions without being physically close.” (Rallet & Torre 1999: 375) 



Dimensions of proximity 

The analysis of the three relevant theories concerning knowledge production and diffusion has 

brought up four proximity dimensions that are relevant for knowledge spillovers: Spatial proximity, 

technological or industrial proximity, cognitive proximity and behavioural proximity. 

Other authors present various other definitions of proximity. In order to outline the scope of 

the different definitions I will hold the four here presented definitions against two different 

classifications presented recently in a special issue of Regional Studies. 

Concerning spatial or geographical proximity no contradictions arise, as there is wide agreement, 

that it “expresses the kilometric distance between two units” (Torre & Rallet 2005: 49). 

Nevertheless being near or far is no objective kilometric measure. It is weighted by the cost 

and time of transport as well as by individual perceptions of distance. In spatial proximity the 

probability of interaction is higher. Although the spatial proximity dimension reduces space 

on its physical content, it is not the same as the container space often used in economics. So 

it also cannot simply be compared to a region delimited by political, administrative or functional 

frontiers. The geographical proximity of two metropoles may be similar to the spatial 

proximity of the inner city to its suburb depending on transport infrastructure. The advantage 

of being located in an agglomeration with a transport hub is the possibility of temporal spatial 

proximity to a relevant person carrying knowledge. 

Cognitive proximity is also mentioned by many other authors, although Torre and Rallet subsume 

this proximity dimension under the category of organisational proximity. Similarity of 

the knowledge base of two actors is necessary for mutual understanding. If the cognitive distance 

is too big, individuals will not be able to understand each other or the costs to overcome 

knowledge gaps will be too high. On the other hand when two actors are too near no 

progress in producing new knowledge will be achieved. All authors agree that cognitive proximity 

is a prerequisite for knowledge dissemination and production. Cowan, David & Foray 

(2000) emphasis here the role of epistemological communities. Referring to the technical 

jargon of professionals they find that knowledge is transferred in specific codebooks, which 

are only known to experts of a scientific field. They can communicate with each other over 

great distance by means of articles and conferences, while actors without knowledge of the 

codebook are excluded. Firms can form epistemological communities with their suppliers and 

customers, oriented narrowly towards a certain common project. Spatial proximity can then 

occur as result of the formation of epistemological communities. In research projects and 

visits, conferences, business meetings etc. spatial proximity is established temporarily. Empirical 

studies by Maryann Feldman and Lichtenberg underline these mechanisms. They analyse 

research projects with the actors involved located at different places in the EU. Centralisation 

of the members at one location occurs according to the amount of tacit knowledge that is 

generated. So cognitive proximity leads to spatial proximity and may be ended when the 

knowledge level is adjusted. Freel (2003) shows that with the means of (temporal) spatial 



proximity knowledge gaps, that actually prevent two actors from understanding each other, 

can be closed. 

The term cognitive proximity refers only to individuals. So it is necessary to add the perspective 

of the firm. The terms industrial and technological proximity refer to the firm. For a firm 

not only the cognitive skills of their employees are of importance but also their composition 

of production factors and their operational area. Just as the individuals have a specific and 

limited knowledge base to their disposal, firms have a significant portion of superfixed production 

factors. “Superfixed production factors are long-lasting, tangible and intangible assets 

which once installed can be replaced only with huge costs and a long time span.” (Antonelli 

2000: 397) Not every new knowledge can be appropriated by a firm, because the superfixed 

production factors place significant constraints on their ability to adjust to changing 

environments. Just as the knowledge base of an individual places constraints on the range of 

new knowledge he is able to appropriate. Technological and industrial proximity outlines the 

ability of firms to learn from each other. 

The many empirical studies that find that vertical relationships along the value chain and 

especially customers are the most important innovation partners underline the meaning of 

industrial proximity (Tödtling und Kaufmann 1999; Freel 2003; Koschatzky und Zenker 2001; 

Sternberg 1998; Dei Ottati 1998; Markusen 2000; Cornford, Naylor & Driver 2000). New knowledge 

is produced in concrete production contexts, where both partners fulfil the necessary 

preconditions to appropriate the new knowledge. These important relationships to highly demanding 

customers are independent of the physical distance between the business partners. 

The fourth proximity dimension coined here is behavioural proximity. As explained above it 

comprises the non-market content of relationships. It complies to a great extend with what 

Ron Boschma divides into the three proximity dimensions organizational, social and institutional 

proximity. In Boschmas line of argument the three proximity dimensions must be separated 

because they function along different mechanisms. Organisational proximity is dependent 

on the degree of autonomy the network partners have. Social proximity is dependent on 

trust. It is a feature of friendship, family or long-lasting acquaintance. The mechanism of 

institutional proximity are norms and habits, rules and laws. To draw a clear line between the 

three dimensions is extremely difficult. Even Boschma himself asserts: “As such the social, 

organizational and institutional forms of proximity may be strongly interconnected, because 

the ways intra- and interorganizational relations are governed are deeply embedded in institutional 

settings.” (Boschma 2005: 67/68) 


Procedural 

Rationality 


Relationship of different proximity dimensions 

In subsuming the non-market content of relationships in one proximity dimension, it is possible 

to describe the behaviour in actor networks (Amin 1999). The decisive mechanism working 

here are strong and weak ties. Strong ties work in hierarchical organisations and institutions 

or in very tight kinship relationships. Too strong ties lead to lock-in, understatement of opportunistic 

behaviour and the room for innovation and experiments is very small. Weak ties on 

the other hand can not prevent opportunistic behaviour to harm the dissemination of knowledge 

in the actor network. Are relationships too weak the behaviour of partners cannot be 

anticipated so that transaction costs are not reduced. 

The behaviour of an actor network is decisive for what effect the non-market content — the 

relational or social capital will have. On the one hand social capital as glue between relationships 

can enforce conservative behaviour and lead to lock-in. This is indicated by falling 

economies of scale. Based on progressive behaviour on the other hand social capital will facilitate 

the search for new knowledge and lead to increasing returns to scale. 

Figure 2: Effects of Behavioural Proximity 

Institutions 

Laws/ Regulations 

Relationships/ 

Behavioural Proximity 

Administration/ 

Government 

Recursive 

Rationality 

Instrumentalist 

Rationality 

Social Capital 

as Externality 

falling constant increasing 

Returns to Scale 

Actor networks with mainly strong ties show an instrumental behavioural rationality. Well 

tried rules of action are seldomly put to proof or further developed. Relationships do not have 

the function to acquire new knowledge. Instead they function as a safety net. Cognitive proximity 

is too near, so that knowledge that spills is mainly redundant and assuring regarding 

behavioural rules. Instrumental rationality often dominates pure production networks between 



key firms of an industry and their suppliers especially when they are characterised by asymmetric 

power relations. 

Procedural rationality as dominating behaviour in actor networks appears, when too weak or 

too strong ties dominate. Networks with a great variety of actors are mainly characterised by 

weak ties. Here cognitive proximity is not near enough to enable mutual understanding. 

Where strong ties dominate an actor network can generate monopoly rents by forming a cartel. 

Nevertheless the tendency to conservatism will only allow constant economies of scale. 

“They respond heuristically and procedurally in satisfying goals.” (Amin 1999: 367) 

Only recursive rationality can generate increasing returns to scale. Relationships are supported 

and maintained as strategic resource. On the one hand relationships are stable enough to 

build a continuous source to be activated. On the other hand the relationships are highly 

flexible. They can be activated in different contexts and in different ways. The actor network 

gives room to produce new knowledge in the respectively most effective constellations, it 

gives the possibility to find partners in the right cognitive distance which will enable mutual 

understanding without redundancy. “…a recursive rationality is problem-seeking and assumes 

that the environment can be anticipated and to a degree manipulated through such procedures 

as strategic monitoring, experimental games, group learning and so on.” (Amin 1999: 

367) 

Drawing a conclusion under the here discussed effects and relationships of different proximity 

dimensions it must be asserted that spatial proximity is overstated. In order to generate increasing 

returns in the knowledge production process the behavioural proximity of actors to 

each other is of much greater relevance. Spatial proximity and agglomeration is no sufficient 

condition to create regional growth on the bases of knowledge intensive economic processes. 

Only in combination with technological/ industrial proximity the preconditions are set to earn 

monopoly rents furthering regional growth. But still this may not be a long lasting phenomenon, 

if the behavioural proximity between the regional actors does not enable progressive 

relationships. 

Considering the possibility to create temporal spatial proximity, the advantage of being located 

in an agglomeration may not be the proximity to other knowledge producers and benefiting 

from their knowledge spillovers. Instead the agglomeration as transport hub becomes 

relevant giving much greater possibilities to create temporal spatial proximity to potential 

partners independent of their location. 



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Knowledge Spillovers in different Dimensions of Proximity

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