Connecting Knowledge Systems:
Exploring the Role of Global Business Services

 

By
Dr Jeremy Howells* and Dr Joanne Roberts**
16th September 1999
Paper submitted to EIBA 25th Annual Conference
International Business and the Global Services Economy
12th-14th December 1999

*Director,
Policy Research in Engineering,
Science & Technology (PREST) and ESRC Centre for Research on Innovation & Competition (CRIC),
Manchester Federal School of Business and Management,
University of Manchester and UMIST
Please contact via:
PREST, University of Manchester,
Oxford Road,
Manchester M13 9PL.
UK. Tel: +44 (0) 161 275 7374
Fax: +44 (0) 161 275 7631

Email: jhowells@oakrits.u-net.com
or
Jeremy.Howells@man.ac.uk


**Senior Lecturer,
Division of Economics,
School of Social, Political and Economic Sciences,
University of Northumbria at Newcastle,
Northumberland Building,
Newcastle upon Tyne. NE1 8ST.

UK. Tel: +44 (0)191 2273931
Fax: +44 (0)191 2274654

Email: joanne.roberts@unn.ac.uk




Connecting Knowledge Systems:
Exploring the Role of Global Business Services

Abstract

This paper seeks to contribute to the understanding of systems of knowledge creation and dissemination. Drawing on the literature concerning systems of innovation this paper identifies and evaluates the characteristics of knowledge systems. Much effort has been directed towards national and sectoral systems of knowledge creation. However, in an increasingly global economic environment it is evident that some knowledge-creating enterprises function simultaneously in a number of national and sectoral systems. The aim of this paper is therefore, to examine the extent to which knowledge systems interact at an international level. Globally provided business services, especially Knowledge Intensive Business Services (KIBS), are identified as having a particularly important role facilitating the transfer of knowledge between national and regional knowledge systems. Specific attention is therefore given to the role of KIBS as connectors assisting the transfer of knowledge between knowledge systems. The analysis presented here concludes by suggesting a framework in which to conceptualise the interactions of knowledge systems at an international level.

The paper begins with an exploration of knowledge. This is followed by the presentation of a definition of knowledge systems drawing on existing literature concerning systems of innovation. A brief review of the systems of innovation literature is then presented, before a fuller exploration of knowledge systems is provided in which they are compared and contrasted with systems of innovation. It is at this point that a conceptual analysis of knowledge systems is provided. Attention then turns to international knowledge systems and the importance of KIBS is highlighted. Following on from this, a framework, which incorporate the role of KIBS as connectors linking knowledge systems, is forwarded as a conceptual tools with which to analyse the interactions of knowledge systems in an international context. Finally, conclusions are drawn and directions outlined for further research.

 

Connecting Knowledge Systems:
Exploring the Role of Global Business Services

 

 

 

Dr J Howells�

Chapter 14

Knowledge Systems in an International Context

 

J. Howells and J. Roberts c. 8,200 00 words (incl. refs.)

 

INTRODUCTION

The significance of knowledge and innovation in economic activity has received much attention in recent years (OECD 1996). ECD 1996b3) Consequently, there has been a desire to provide a better understanding of the role of knowledge in relation to the innovation process and more generally in terms of economic growth and performance. This paper seeks to contribute to this understanding by examining systems of knowledge creation and dissemination. Drawing on the literature concerning systems of innovation this paper identifies and evaluates the characteristics of knowledge systems. Much effort has been directed towards national and sectoral systems of knowledge creation. However, in an increasingly global economic environment it is evident that some knowledge-creating enterprises function simultaneously in a number of national and sectoral systems. The aim of this paper is therefore, to examine the extent to which knowledge systems interact at an international level. Globally provided business services, especially Knowledge Intensive Business Services (KIBS), are identified as having a particularly important role facilitating the transfer of knowledge between national and regional knowledge systems. Specific attention is therefore given to the role of KIBS as connectors assisting the transfer of knowledge between knowledge systems at various spatial scales. The analysis presented here concludes by suggesting a framework in which to conceptualise the interactions of knowledge systems at an international level.

Knowledge and innovation are central to economic success in the advanced industrialised countries (Drucker 1993). Service activities concerned with the supply and management of knowledge and intangible assets, whether within the boundaries of firms or in the market, are becoming increasingly significant in facilitating knowledge creation and distribution in regional, national and international environments. In the emerging knowledge-based economy (OECD 1996) an appreciation of the creation and dissemination of knowledge is vital for policy makers and business managers since they do much to ensure economic prosperity by promote the development of knowledge-based activity (Lundvall and Johnson 1994; Hodgson 1999). Consequently, the analysis of knowledge systems presented in this paper will prove useful to policy makers and business managers alike. It will also contribute to debates among academics studying the role of knowledge in economic activity.

There has been much interest in the ‘systems of innovation’ approach in terms of how it shapes and transforms the innovation process in advanced industrial economies. Equally there has been a desire to provide a better understanding of the role of knowledge in relation to the innovation process and more generally in terms of economic growth and performance. Both sets of interest have also come at a time when the spectre of globalisation of technology has been at least raised, if not wholeheartedly supported, in these modern times by many commentators. The objective of this chapter is to explore this tripartite relationship by seeking to analyse systems of knowledge creation and dissemination in an international context. Drawing on the literature concerning systems of innovation the chapter identifies and evaluates the characteristics of knowledge systems. Much effort has been directed towards national and sectoral systems of knowledge creation. However, in an increasingly globalised economic environment it is evident that some knowledge-creating enterprises function simultaneously in a number of national and sectoral systems. The aim of this chapter is, therefore, to examine the extent to which knowledge systems interact at an international level. It seeks to identify the components that make up an international system, and to investigate how factors at an international level interact with national and sector specific elements of knowledge systems. This analysis concludes by suggesting a number of possible theoretical frameworks in which to conceptualise the interactions of the various knowledge systems.

The paper begins with an exploration of knowledge. This is followed by the presentation of a definition of knowledge systems drawing on existing literature concerning systems of innovation. A brief review of the systems of innovation literature is then presented, before a fuller exploration of knowledge systems is provided in which they are compared and contrasted with systems of innovation. It is at this point that a conceptual analysis of knowledge systems is provided. Attention then turns to international knowledge systems and the importance of KIBS is highlighted. Following on from this, a framework, which incorporate the role of KIBS as connectors linking knowledge systems, is forwarded as a conceptual tools with which to analyse the interactions of knowledge systems in an international context. Finally, conclusions are drawn and directions outlined for further research.

WHAT IS KNOWLEDGE?

In order to understand knowledge systems it is necessary to make clear what knowledge is. Defining and comprehending knowledge is complex and problematic (Sparrow 1998, 24). A simple definition is that knowledge is what we know. However, more centrally knowledge is "a mental state that bears a specific relationship to some feature of the world." (Plotkin 1994, 40). Crucially knowledge has a relational characteristic, as it involves a ‘knowing self’ and something; that ‘something’ being an event or an entity. Knowing is an active process that is mediated, situated, provisional, pragmatic and contested (Blackler 1995). A final element in knowledge is the need for some kind of memory. ‘Memory’ here involves an enduring brain state that must exist in the case of knowing by the mind, and allows the bridging of the time gap between events that have occurred and any claim to know about them. It is important to note here that memory about events in the past in turn undergoes change and therefore memory forms an unconscious, altering the form of knowing (Plotkin 1994, 8).

There is an important distinction to be made here between knowledge and information. Information relates to individual bits of data or data strands, whilst knowledge involves a much wider process that involves cognitive structures which can assimilate information and put it into a wider context, allowing actions to be undertaken from it. Thus knowledge in turn combines the process of learning (Polanyi 1958, 369). The take-up of learned behaviour and procedures is a critical element within knowledge acquisition, both in terms of capturing and moving it between individuals within an organisation (Kim 1993), but also in more widely diffusing such competence throughout an organisation more generally (Urlich and von Glinow 1993), between organisations and indeed within the economy as a whole. It should be stressed that knowledge cannot be said to ‘flow’; although, via information flows and mutual learning experiences which then are assembled or absorbed within a cognitive structure or framework, knowledge can be said to be ‘shared’ or ‘transferred’. As knowledge is transferred through the process of codification, abstraction, diffusion and absorption it acquires a dynamic quality (Boisot 1998, Nonaka and Takeuchi 1995).

In terms of technological innovation more specifically, the innovation process involves both using existing knowledge but often also requires generating and acquiring new knowledge, which in turn involves learning. Innovation also involves sharing learned knowledge. The process of innovation by moving from existing knowledge and learning patterns to new ones through invention and discovery can be termed a ‘heuristic’ (defined here as a procedure or strategy for solving a problem or moving towards a solution of a problem; Plotkin 1994, 250). If we accept this definition and description, it suggests that knowledge is fundamentally centred on the individual (Howells 2000). Even though we may share many characteristics in our knowledge frameworks, and intelligence, and in the way we learn and perceive, resulting from common social and educational experiences, knowledge it is still intrinsically an individually centred phenomenon. Such a viewpoint also has important implications when we come to discuss what is meant by a knowledge system.

A great deal has been discussed in relation to the important distinctions between tacit and codified knowledge and this distinction has carried through to much wider discussion at the more macro level of the economy as a whole (see, for example, Boisot 1998). The distinction between tacit and codified knowledge made by Michael Polyanyi (1958; 1966; 1967) is a powerful and useful one, but has all too often been mis-applied. Codified (or explicit) knowledge can be defined here as knowledge that can be written down in the form of a document, manual, blue-print or operating procedure. By contrast tacit knowledge is disembodied know-how that is acquired via the informal take-up of learned behaviour and procedures. It is presented here therefore that this bi-polar dichotomy represents a crude characterisation of knowledge as an activity, or more generally in terms of how it should be conceived operating within a system. It in particular misrepresents Polanyi’s own thinking which stressed that tacit and explicit knowledge were not divided and that explicit or codified knowledge required tacit knowledge for its interpretation. Polanyi (1966: 7) notes "While tacit knowledge can be possessed by itself, explicit knowledge must rely on being tacitly understood and applied. Hence all knowledge is either tacit or rooted in tacit knowledge. A wholly explicit knowledge is unthinkable." Knowledge is therefore much more complex than this dichotomy portrays; particularly as one moves from knowledge being an individual phenomenon through to group, firm or organisation wide process. Knowledge should be better conceived as involving a spectrum of processes ranging from what might be described as ‘tacit’ and ‘explicit’ (although indeed PolyaniPolanyi stressed that articulation would always remain incomplete (Polanyi 1958: 70) and therefore on his basis one would never fully reach the ‘explicit’ knowledge end of the spectrum).

DEFINING KNOWLEDGE SYSTEMS

If the above defines and describes what knowledge is, how can a knowledge system be defined? Dominique Foray (1997, 64-5) defines a knowledge system:

"as a network of actors or entities that assume specific functions for the generation, transformation, transmission, and storing of knowledge...... The critical degree of cohesiveness, necessary to get a knowledge system is simply defined by some parameters describing the frequency of the knowledge interactions."

Foray (1997, 65) continues by noting that:

"A knowledge system includes economic agents (or learning entities) that assume the relevant functions of knowledge generation (by means of cognitive exploration and search) such as the codification and reduction of knowledge to information, the monitoring and perception of information (involving encoding, decoding, translation, filtering, and compression), the communication and transfer of knowledge, and its storage, retrieval, and reconstruction. It also includes the institutions that serve to overcome the market’s deficiencies in the production and distribution of knowledge."

The description and definition that Foray applies to a knowledge system covers the actors and institutions that are involved in the generation, transformation, storage and distribution of knowledge. The knowledge system that Foray has described is one which is highly purposeful and specifically centred around economic agents and is framed on the basis of the knowledge interactions between these agents, and consequent on this the distribution of power. This specificity has indeed been highlighted by Smith (1995, 82) who notes that the ‘David-Foray’ concept of the knowledge system is as narrow though complex in its multi-layered approach to scientific and technological knowledge. As Smith (1995) notes the David and Foray (1995) approach emphasises the role of learning systems for knowledge (see below).

Foray’s definition of knowledge system, together with the way he and Paul David have articulated this concept, is regard here as being too narrow and specific. Thus Foray and David (1995, 20) specifically focus on the special characteristics of knowledge as an economic commodity. Although much innovation, and indeed new knowledge, comes from purposeful study, learning and action by economic agents in a market-oriented and mediated context, much important knowledge does not. Serendipity and non-market situations are still highly important; social interaction and embeddedness, past historical actions, geographical proximity, trust and chance all play a significant role in knowledge processes. Above all care should be taken in not taking a too ex post view of a knowledge system and its impact on innovation and the wider economy. Ex ante the knowledge system still remains a fragmented, highly complex and sometimes confusing world.

However, if we accept this narrow definition as a starting point, in what way does a knowledge system differ from an innovation system? A brief outline of the development of the systems of innovation approach is provided below before a more detailed comparison between the two types of system in undertaken.

SYSTEMS OF INNOVATION

The ‘systems of innovation’ approach has developed and evolved from the original set of ‘national systems of innovation’ (NSI) studies presented by Freeman (1987; 1988), Lundvall (1988; 1992a) and Nelson (1992). Freeman (1987; 1988) has identified a number of vital and distinctive elements in its national system of innovation, such as its model of competition, which could be attributed to its success in terms of innovation and economic growth. It has subsequently been applied at a variety of scales and levels, many of which have been outside the original focus of a national setting. Thus, although the national focus remains strong, and rightly so, it has been accompanied by studies seeking to analyse the notion of systems of innovation at an international, sub-national (regional or local) and sectoral or technology level. In this latter context, Carlsson (1995) developed the ‘technological systems’ approach, which indicates that systems can be specific to particular technology fields or sectors. Sectors and technological systems within a nation have a powerful shaping influence on the structure and dynamic of a national innovation system, whilst national contexts have important influences on sectoral performance and conditioning. Thus, prior institutional endowments of a national system may help or hinder innovative activity and performance within particular sectors of a national economy (Howells and Neary 1995).

Chris Freeman (1987, 1) was the first to attempt to define the concept as "the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies." Lundvall (1992a, 12) makes a distinction between a narrow and broad definition of a system of innovation. In his narrow definition of a system of innovation this would include "organisations and institutions involved in searching and exploring - such as R&D departments, technological institutes and universities." In his broader definition, a system of innovation would include "all parts and aspects of the economic structure and the institutional set-up affecting learning as well as searching and exploring - the production system, the marketing system and the system of finance present themselves as sub-systems in which learning takes place." In respect of the ‘national’ element, Lundvall (1992a, 2-3) stresses that this is not as clear-cut as is often assumed and that nation states which the concept of ‘national systems of innovation’ presumes, has two dimensions: the national-cultural and the étatist-political. The ideal, abstract nation state where these two dimension coincide controlled by one central state authority, though, is, as Lundvall adds, difficult, if not impossible, to find in the real world. Moreover, this nationally-bounded view, at least in geographical terms, has been loosened over time. The globalisation of economic activity is bringing into question the role and relevance of NSI (Nelson and Rosenberg 1993).

There is then growing recognition of the significance of supranational and international systems of innovation, and indeed some discussion of international knowledge systems (Caravcostas and Soete 1997; Noisi and Bellon 1994). As Carlsson and Stankiewicz (1995) note, the boundaries of a system depend on the particular circumstances. The systems of innovation approach has now been widened and developed to more specifically include systems of innovation that are sectoral in dimension and those that are at a different geographical scale, both above in terms of what Freeman (1995) coined ‘upper’ regions (‘triad’ and continental regions), and below in relation to regional and local systems.

Within the context of the term ‘innovation’, this has a wide range of explicit and implicit definitions applied to it. Edquist (1997, 10) here has stressed the ambiguity and wide variation in what may be termed the ambit of the word ‘innovation’. Thus, Nelson and Rosenberg (1993) and Carlsson and Stankiewicz (1991; 1995) have tended to adopt narrower definitions of innovation, mainly (though not wholly) centred on technological innovations, whilst Lundvall (1992a) seeks to include what may be termed dis-embodied innovations, in particular institutional innovations. However, Freeman (1988, 339-41), in his analysis of the Japanese innovation system, also emphasised the role of social and educational innovations, whilst Carlsson and Stankiewicz (1995, 28), in adopting Dosi’s (1988, 222) definition of innovation, would also seem to include the emergence and development of new organisational set-ups in their use of the word ‘innovation’.

KNOWLEDGE SYSTEMS: A CONCEPTUAL ANALYSIS

The above has sought to outline some of the background to the systems of innovation approach, but how might a knowledge system be distinct from an innovation system? A number of points are put forward here, highlighting not only differences between the two types of system but also their inter-relationship. A number of problems associated with using the term ‘knowledge system’ as a conceptual tool are also raised.

Firstly, interpreting a knowledge system in a wider sense than that used by Foray, a knowledge system represents a broader and less well defined system than an innovation system. A knowledge system represents an underlying knowledge and learning framework and pool for the more specific process of innovation and hence systems of innovation. Since an innovation can broadly be seen as application of knowledge, knowledge represents a repository which then becomes taken up and applied to invent things and create new ways of doing things. A knowledge system on this basis is bound to be a vaguer and more nebulous system, it may include many elements which are redundant, forgotten, ignored or quite simply wrong.

This notion of a knowledge system acting as the background to the foreground of an innovation system has parallels with Tassey’s (1991) notion of a ‘technology infrastructure’. Here Tassey envisages knowledge together with institutional frameworks as providing the basic infrastructure that acts as a resource and structuring form for technological innovation.

Secondly, education and learning will obviously be central to any knowledge system. However, Lundvall has noted the clear role that learning played in binding together production and innovation in a national system of innovation (Lundvall 1988, 362; Lundvall 1992a, 9-11) and the foundation that interactive learning provides for the competitive performance of an innovation system (Lundvall 1995, 39; Lundvall and Johnson 1994). Indeed much of what Lundvall lends to the role of learning in an innovation system is pertinent to a knowledge system, although more so.

Thus learning is important in Lundvall’s conception of systems of innovation because, aside from it being viewed by him as being critically important in the innovation process, it is a key element in both the dynamic of the system and as a key agent in binding the whole system together. Here Lundvall (1995, 40) notes "many different sectors and segments of the economy contribute to the overall process of interactive learning and the specificity of the elements, as well as the linkages and modes of interaction between them, are crucial for the rate and direction of technical change." Learning plays therefore a major role in the change and development of both innovation and more directly knowledge systems, whilst forming the key element in its connectivity. In this framework learning takes place at all scales from the individual, through to the firm and organisation, on to the inter-firm and inter-organisational learning; institutional learning (Johnson 1992); cross-institutional learning and on through to the whole system, the ‘learning economy.’

Thirdly, the notion of learning however leads to a more central concern about of how one conceives knowledge as one moves away from the individual to a more aggregate setting such as a system. Obviously in the context of learning and knowledge generation and sharing, the learning process involves a clear interactive and collective dimension. There are also inter-firm and more general institutional routines (Hodgson 1988) that can be set up through this interactive learning process. It is however much harder to ascribe collections of firms, organisations and institutions as having a single, clear cognitive process (involving both a decision-making and memory function) associated with the central foundation of what knowledge is. Knowledge systems can be associated with ‘learning frameworks’ and parts of the system are involved in collective learning processes, but knowledge itself will reside with the individual (Howells 2000). The authors feel that discussions about knowledge commodities and knowledge assets arise from a profound misconception about the notion of knowledge. Knowledge assets can be no more than organisational and social mechanisms for the creation, absorption, diffusion and protection of knowledge. They may, for example, result from a firm’s investment in a team of workers capable of reading the code through which knowledge central to the firm's activity is codified (Cowan and Foray 1997).

Fourthly, it is useful to describe a knowledge system as combining the two elements of tacit and codified knowledge, although, it is argued here that it is inappropriate to describe the separate functioning of these two aspects of knowledge. It is presented here, therefore, that a knowledge system is more complex than a simple bi-polar model of codified and tacit knowledge generation and transfer. As knowledge becomes more codified it becomes more like information, or quasi knowledge, and less like knowledge, however it still depends on a tacit element in its articulation, comprehension and sharing. Knowledge is also firmly rooted in the individual. Thus, as one moves further up the knowledge hierarchy (involving both geographical and socio-economic scales), knowledge radiates outward from the individual through to team/site groupings, to the whole organisation, inter-organisational, local and/sectoral, regional, national and international contexts. In doing so, it becomes more codified, more information-like, more transferable and more global in its reach but still requires interpretation at the individual level (Figure 1 p.24). Moving up the knowledge hierarchy, therefore, certain types of codified knowledge become essentially transmogrified into information which can then be readily transferred, but its interpretation, comprehension and absorption back into a knowledge state remains at the individual level, either as separate individuals or working through specific teams or specific local sites. Knowledge, as defined here, is then, embedded within the individual and the social contexts in which individuals interact with one another.

In terms of defining a knowledge system, a distinction must be clearly drawn between individually centred knowledge and what is referred to here as quasi knowledge. A knowledge system, as defined here, consists of two sub-system. One relates to individually centred knowledge, and can be referred to as the knowledge sub-system. Here knowledge circulates within and between individuals through social interaction. In this sub-system knowledge is shared and created in a social context, consequently the relevant institutional structures are socio-cultural (Table 1 p.25). Generally, this knowledge sub-system is specific to the location of the team or group within the firm. Increasingly, however, it is possible to identify such systems operating at various spatial scales. For example, R&D workers in a multinational firms may participate in a geographically dispersed team through frequent travel, enabling face-to-face contact with colleagues, together with the support of information and communication technology services, such as email and video conferencing. In this instance, the knowledge sub-system is international in scope.

The second sub-system within a knowledge system can be referred to as the quasi knowledge sub-system. Here knowledge is shared in codified form, and the full range of institutional factors are relevant from socio-cultural, legal, political, economic and so on Although, a distinction is being drawn here between knowledge and quasi knowledge sub-systems, they both have socio-cultural dimensions. The codification of knowledge may draw on social or cultural conventions, for example language or traditions. Moreover, as already noted, the assimilation of codified knowledge requires tacit knowledge and new tacit knowledge may arise not only from social interaction and learning, but also from the absorption and assimilation of codified knowledge. Importantly, then the two sub-systems are inter-linked and indeed, interdependent. However, whereas the knowledge sub-system depends on co-location and co-presence for the sharing of tacit knowledge, the quasi knowledge system is not restricted in this way. The sharing of quasi knowledge does not require co-location or co-presence between the transmitter and receiver. Consequently, when examining knowledge systems in an international context we might expect to find that the quasi knowledge sub-system has a dominant role whereas in the local context the knowledge sub-system is more significant.

A knowledge system is then clearly much broader than a system of innovation. The view of knowledge systems outlined here builds on the definition provided by Foray, in doing so, it provides a more detailed reflection of the complex institutional structures that influence the process of knowledge creation and transfer at various spatial scales. Nevertheless, it is recognised that the operationalisation of this framework would present difficulties. The value of this framework lies in its ability to complement the systems of innovation approach, providing an additional dimension for those studying innovation whether in a national or international context.

In order to achieve this objective it is necessary to make clear what knowledge is, and how this relates in turn to a knowledge system. Defining and comprehending knowledge is complex and problematic (Sparrow 1998, 24). A simple definition answer to what knowledge is that knowledge is what we know. However, more centrally knowledge is "a mental state that bears a specific relationship to some feature of the world." (Plotkin 1994, 40). Crucially knowledge has a relational characteristic, as it involves a ‘knowing self’ and something; that ‘something’ being an event or an entity. Knowing is an active process that is mediated, situated, provisional, pragmatic and contested (Blackler 1995). A final element in knowledge is the need for some kind of memory. ‘Memory’ here involves an enduring brain state that must exist in the case of knowing by the mind, and allows the bridging of the time gap between events that have occurred and any claim to know about them. It is important to note here that memory about events in the past in turn undergoes change and therefore memory forms an unconscious, altering the form of knowing (Plotkin 1994, 8).

There is an important distinction to be made here between knowledge and information. Information relates to individual bits of data or data strands, whilst knowledge involves a much wider process that involves cognitive structures which can assimilate information and put it into a wider context, allowing actions to be undertaken from it. Thus knowledge in turn combines the process of learning (Polanyi 1958, 369). The take-up of learned behaviour and procedures is a critical element within knowledge acquisition, both in terms of capturing and moving it between individuals within an organisation (Kim 1993), but also in more widely diffusing such competence throughout an organisation more generally (Urlich and von Glinow 1993), between organisations and indeed within the economy as a whole. It should be stressed that knowledge cannot be said to ‘flow’; although, via information flows and mutual learning experiences which then are assembled or absorbed within a cognitive structure or framework, knowledge can be said to be ‘shared’ or ‘transferred’. As knowledge is transferred through the process of codification, abstraction, diffusion and absorption it acquires a dynamic quality (Boisot 1998).

In terms of technological innovation more specifically, the innovation process involves both using existing knowledge but often also require generating and acquiring new knowledge which in turn involves learning. Innovation also involves sharing learned knowledge. The process of innovation by moving from existing knowledge and learning patterns to new ones through invention and discovery can be termed a ‘heuristic’ (defined here as a procedure or strategy for solving a problem or moving towards a solution of a problem; Plotkin 1994, 250). If we accept this definition and description, it suggests that knowledge is fundamentally centred on the individual (Howells 2000). Even though we may share many characteristics in our knowledge frameworks, and intelligence, and in the way we learn and perceive, resulting from common social and educational experiences, knowledge it is still intrinsically an individually centred phenomenon. Such a viewpoint also has important implications when we come to discuss what is meant by a knowledge system.

 

KNOWLEDGE SYSTEMS

If the above defines and describes what knowledge is, how can a knowledge system be defined? Dominique Foray (1997, 64-5) has provided a definition, describesing a knowledge system:

"as a network of actors or entities that assume specific functions for the generation, transformation, transmission, and storing of knowledge...... The critical degree of cohesiveness, necessary to get a knowledge system is simply defined by some parameters describing the frequency of the knowledge interactions."

Foray (1997, 65) continues by noting that:

"A knowledge system includes economic agents (or learning entities) that assume the relevant functions of knowledge generation (by means of cognitive exploration and search) such as the codification and reduction of knowledge to information, the monitoring and perception of information (involving encoding, decoding, translation, filtering, and compression), the communication and transfer of knowledge, and its storage, retrieval, and reconstruction. It also includes the institutions that serve to overcome the market’s deficiencies in the production and distribution of knowledge."

 

The description and definition that Foray applies to a knowledge system covers the actors and institutions that are involved in the generation, transformation, storage and distribution of knowledge. The knowledge system that Foray has described is one which is highly purposeful and specifically centred around economic agents and is framed on the basis of the knowledge interactions between these agents, and consequent on this the distribution of power. This specificity has been indeed been highlighted by Smith (1995, 82) who notes that the ‘David-Foray’ concept of the knowledge system is as narrow though complex in its multi-layered approach to scientific and technological knowledge. As Smith (1995) notes the David and Foray (1995) approach emphasises the role of learning systems for knowledge (see below).

Although the authors here accept, on one hand, the definition of Foray’s regarding knowledge system and the way he and Paul David have articulated this concept, we, on the other hand, see such a definition as being too narrow and specific. Thus Foray and David (1995, 20) specifically focus on the special characteristics of knowledge as an economic commodity. Although much innovation, and indeed new knowledge, comes from purposeful study, learning and action by economic agents in a market-oriented and mediated context, much important knowledge does not. Serendipity and non-market situations are still highly important; social interaction and embeddedness, past historical actions, geographical proximity, trust and chance all play a significant role in knowledge processes. Above all care should be taken in not taking a too ex post view of a knowledge system and its impact on innovation and the wider economy. Ex ante the knowledge system still remains a fragmented, highly complex and sometimes confusing world.

However, if we accept this narrow definition as a starting point, in what way does a knowledge system differ from an innovation system? A brief outline of the development of the systems of innovation approach is provided below before a more detailed comparison between the two types of system in undertaken.

The ‘systems of innovation’ approach has developed and evolved from the original set of ‘national systems of innovation’ (NSI) studies presented by Freeman (1987; 1988), Lundvall (1988; 1992a) and Nelson (1992). Freeman (1987; 1988) has identified a number of vital and distinctive elements in its national system of innovation, such as its model of competition, which could be attributed to its success in terms of innovation and economic growth. It has subsequently been applied at a variety of scales sales and levels, many of which have been outside the original focus of a national setting. Thus, although the national focus remains strong, and rightly so, it has been accompanied by studies seeking to analyse the notion of systems of innovation at an international, sub-national (regional or local) and sectoral or technology level. In this latter context, Carlsson (1995) developed the ‘technological systems’ approach, which indicates that systems can be specific to particular technology fields or sectors. Sectors and technological systems within a nation have a powerful shaping influence on the structure and dynamic of a national innovation system, whilst national contexts have important influences on sectoral performance and conditioning (Chapter 13). Thus, prior institutional endowments of a national system may help or hinder innovative activity and performance within particular sectors of a national economy (Howells and Neary 1995).

Chris Freeman (1987, 1) was the first to attempt to define the concept as "the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies." Lundvall (1992a, 12) makes a distinction between a narrow and broad definition of a system of innovation. In his narrow definition of a system of innovation this would include "organisations and institutions involved in searching and exploring - such as R&D departments, technological institutes and universities." In his broader definition, a system of innovation would include "all parts and aspects of the economic structure and the institutional set-up affecting learning as well as searching and exploring - the production system, the marketing system and the system of finance present themselves as sub-systems in which learning takes place." In respect of the ‘national’ element, Lundvall (1992a, 2-3) stresses that this is not as clear-cut as is often assumed and that nation states which the concept of ‘national systems of innovation’ presumes, has two dimensions: the national-cultural and the étatist-political. The ideal, abstract nation state where these two dimension coincide controlled by one central state authority, though, is, as Lundvall adds, difficult, if not impossible, to find in the real world. Moreover, this nationally-bounded view, at least in geographical terms, has been loosened over time. The approach has now been widened and developed to more specifically include systems of innovation that are sectoral in dimension and those that are at a different geographical scale, both above in terms of what Freeman (1995) coined ‘upper’ regions (‘triad’ and continental regions), and below in relation to regional and local systems.

Within the context of the term ‘innovation’, this has a wide range of explicit and implicit definitions applied to it. Edquist (1997, 10) here has stressed the ambiguity and wide variation in what may be termed the ambit of the word ‘innovation’. Thus, Nelson and Rosenberg (1993) and Carlsson and Stankiewicz (1991; 1995) have tended to adopt narrower definitions of innovation, mainly (though not wholly) centred on technological innovations, whilst Lundvall (1992a) seeks to include what may be termed dis-embodied innovations, in particular institutional innovations. However, Freeman (1988, 339-41), in his analysis of the Japanese innovation system, also emphasised the role of social and educational innovations, whilst Carlsson and Stankiewicz (1995, 28), in adopting Dosi’s (1988, 222) definition of innovation, would also seem to include the emergence and development of new organisational set-ups in their use of the word ‘innovation’.

The above has sought to outline some of the background to the systems of innovation approach, but how might a knowledge system be distinct from an innovation system? A number of points are put forward here, highlighting not only differences between the two types of system but also their inter-relationship. A number of problems associated with using the term ‘knowledge system’ as a conceptual tool are also raised.

1) Firstly, interpreting a knowledge system in a wider sense than that used by Foray, a knowledge system represents a broader and less well defined system than an innovation system. A knowledge system represents an underlying knowledge and learning framework and pool for the more specific process of innovation and hence systems of innovation. Since an innovation can broadly be seen as application of knowledge, knowledge represents a repository which then becomes taken up and applied to invent things and create new ways of doing things. A knowledge system on this basis is bound to be a vaguer and more nebulous system, it may include many elements which are redundant, forgotten, ignored or quite simply wrong.

This notion of a knowledge system acting as the background to the foreground of an innovation system has parallels with Tassey’s (1991) notion of a ‘technology infrastructure’. Here Tassey envisages knowledge together with institutional frameworks as providing the basic infrastructure which acts as a resource and structuring form for technological innovation.

2) Secondly, education and learning will obviously be central to any knowledge system. However, Lundvall has noted the clear role that learning played in binding together production and innovation in a national system of innovation (Lundvall 1988, 362; Lundvall 1992a, 9-11) and the foundation that interactive learning provides for the competitive performance of an innovation system (Lundvall 1995, 39; Lundvall and Johnson 1994). Indeed much of what Lundvall lends to the role of learning in an innovation system is pertinent to a knowledge system, although more so.

Thus learning is important in Lundvall’s conception of systems of innovation because, aside from it being viewed by him as being critically important in the innovation process, it is a key element in both the dynamic of the system and as a key agent in binding the whole system together. Here Lundvall (1995, 40) notes "many different sectors and segments of the economy contribute to the overall process of interactive learning and the specificity of the elements, as well as the linkages and modes of interaction between them, are crucial for the rate and direction of technical change." Learning plays therefore a major role in the change and development of both innovation and more directly knowledge systems, whilst forming the key element in its connectivity. In this framework learning takes place at all scales from the individual, through to the firm and organisation, on to the inter-firm and inter-organisational learning; institutional learning (Johnson 1992); cross-institutional learning and on through to the whole system, the ‘learning economy.’

3) The notion of learning however leads to a more central concern about of how one conceives knowledge as one moves away from the individual to a more aggregate setting such as a system. Obviously in the context of learning and knowledge generation and sharing, the learning process involves a clear interactive and collective dimension. There are also inter-firm and more general institutional routines (Hodgson 1988) that can be set up through this interactive learning process. It is however much harder to ascribe collections of firms, organisations and institutions as having a single, clear cognitive process (involving both a decision-making and memory function) associated with the central foundation of what knowledge is. Knowledge systems can be associated with ‘learning frameworks’ and parts of the system be involved in collective learning processes, but knowledge itself will reside with the individual (Howells 2000). The authors feel that discussions about knowledge commodities and knowledge assets is a profound misconception about the notion of knowledge. Knowledge assets can be no more than organisational and social mechanisms for the creation, absorption, diffusion and protection of knowledge. They may, for example, result from a firm’s investment in a team of workers capable of reading the code through which knowledge central to the firm's activity is codified (Cowan and Foray 1997).

4) A great deal has been discussed in relation to the important distinctions between tacit and codified knowledge and this distinction has carried through to much wider discussion at the more macro level of the economy as a whole (see, for example, Boisot 1998). The distinction between tacit and codified knowledge made by Michael Polyani (1958; 1966; 1967) is a powerful and useful one, but has all too often been mis-applied. Codified (or explicit) knowledge can be defined here as knowledge that can be written down in the form of a document, manual, blue-print or operating procedure. By contrast tacit knowledge is disembodied know-how that is acquired via the informal take-up of learned behaviour and procedures. It is presented here therefore that this bi-polar dichotomy represents a crude characterisation of knowledge as an activity, or more generally in terms of how it should be conceived operating within a system. It in particular misrepresents Polanyi’s own thinking which stressed that tacit and explicit knowledge were not divided and that explicit or codified knowledge required tacit knowledge for its interpretation. Polanyi (1966: 7) notes "While tacit knowledge can be possessed by itself, explicit knowledge must rely on being tacitly understood and applied. Hence all knowledge is either tacit or rooted in tacit knowledge. A wholly explicit knowledge is unthinkable." Knowledge is therefore much more complex than this dichotomy portrays; particularly as one moves from knowledge being an individual phenomenon through to group, firm or organisation wide process. Knowledge should be better conceived as involving a spectrum of processes ranging from what might be described as ‘tacit’ and ‘explicit’ (although indeed Polyani stressed that articulation would always remain incomplete (Polanyi 1958: 70) and therefore on his basis one would never fully reach the ‘explicit’ knowledge end of the spectrum).

Whilst it is therefore useful to describe a knowledge system as combining these two elements of tacit and codified knowledge, it is argued here that it is inappropriate to describe the separate functioning of these two aspects of knowledge. It is presented here, therefore, that a knowledge system is more complex than a simple bi-polar model of codified and tacit knowledge generation and transfer. As knowledge becomes more codified it becomes more like information and less like knowledge (quasi knowledge), however it still depends on a tacit element in its articulation, comprehension and sharing. Knowledge is also firmly rooted in the individual. Thus, as one moves further up the knowledge hierarchy (involving both geographical and socio-economic scales): knowledge radiates outward from the individual through to team/site groupings, to the whole organisation, inter-organisational, local and/sectoral, regional, national and international) it becomes more codified, more information-like, more transferable and more global in its reach but still requires interpretation at the individual level (Figure 14.1). Moving up the knowledge hierarchy, therefore, certain types of codified knowledge become essentially transmogrified into information which can then be readily transferred, but its interpretation, comprehension and absorption back into a knowledge state remains at the individual level, either as separate individuals or working through specific teams or specific local sites. Knowledge is, then, embedded within the individual and the social contexts in which individuals interact with one another.

INTERNATYIONAL KNOWLEDGE SYSTEMS

In today's highly internationalised world the creation of new knowledge and the innovations that transpire from such knowledge are influenced by many factors both within and beyond the boundaries of the nation. Indeed, new knowledge usually arises from the combination of existing knowledge, consequently the bringing together of knowledge from different global locations can prove to be a rich source of innovation. There are, therefore, good reasons for examining international knowledge systems.

As noted above, the literature concerning systems of innovation and knowledge has focused primarily on the national level. However, the globalisation of economic activity, resulting from the increasing cross border flows of capital, commodities, labour and information, is bringing into question the role of the nation state (Ohmae 1990; Reich 1991). Although there is much debate about the extent and impact of globalisation (Hirst and Thompson 1996; Krugman 1996), it is evident that many national based organisations and institutions are faced with challenges, and are undergoing changes, brought about by the increased level of cross border activity. Undoubtedly, the organisations and institutions that constitute NSI are being transformed, however gradually, by the forces of globalisation. Consequently, the role and relevance of NSI must be questioned. As Nelson and Rosenberg note (1993, 17-18):

"... the internationalization of business and technology erodes the extent to which national borders, and the citizenship, define boundaries that are meaningful in analysing technological capabilities and technical advance. And these developments have been both stimulated and been reinforced by the rise of transnational public programs of R&D such as Eureka, and the increasing activity of organizations such as the European Commission. All this raises the following question: "to what extent does it make sense any more to talk about ‘national innovation systems'?"

There is then growing recognition of the significance of supranational and international systems of innovation, and indeed some discussion of international knowledge systems including, for example, Caravcostas and Soete's (1997) examination of the European System of Innovation. However, there is a general consensus that NSI are of primary importance, and consequently, the research on international knowledge systems has been somewhat limited.

Although the nation state constitutes a natural boundary for many technological and knowledge systems, it may make sense to talk about a regional or local, international or even global knowledge system. The boundaries of the system depend on the particular circumstances (Carlsson and Stankiewicz 1995). Indeed, Noisi and Bellon (1994) have developed the idea of ‘open national systems of innovation’. They identify three types of innovation systems, regional, national, and international, that coexist and are in competition with each other. Moreover, they argue that internationalization "does not suppress local and national networks; it modifies their functioning, however, since some previously regional or national activities are transferred to international networks" (Noisi and Bellon 1994, 195).

Clearly, as the process of the globalisation continues the relevance of national systems of innovation and knowledge creation are open to debate. Moreover, the need to consider knowledge systems in an international context is underlined. As Nelson (1993, 518-9) notes:

"It is safe to say that differences across firms stamped into them by national policies, histories, and cultures will diminish in importance. Partly that will be because the world is becoming much more unified culturally, .... Partly it will be because firm managers and scholars of management increasingly are paying attention to how firms in other countries are organized and managed. And cross-country interfirm connections are likely to grow in importance. .... Thus, increasingly, the attempts of national governments to define and support a national industry will be frustrated because of internationalization."

Clearly there are good reason for examining innovation and knowledge systems in an international context. In this chapter an understanding is sought of how knowledge system interact in an international context as they compete with, complement or reinforce, both national, regional, and sectoral systems of knowledge generation. Clearly, in today's highly internationalised world the creating of new knowledge and the innovations that transpire from such knowledge are influenced by many factors both within and beyond the boundaries of the nation. Indeed, new knowledge usually arises from the combination of existing knowledge, consequently the bringing together of knowledge from different global locations can prove to be a rich source of new knowledge.

However, before proceeding further, it is necessary to define an international knowledge system. As noted earlier, a knowledge system is broader and less well defined than an innovation system. Moreover, a knowledge system represents an underlying knowledge and learning framework. The essential feature of an international knowledge system is that the entities from which it is formed either interact across national boundaries or in a purely supranational context (e.g. EU research programmes). The various factors that make up a knowledge system at both a national and supranational level are identified in Table 1. For any specific international knowledge system the actual combination of relevant factors will vary depending on the nature of the knowledge being generated, transformed, transmitted or stored. It is important to note that the various elements that constitute the system can have both a positive and a negative impact on the development of knowledge. For example, regulation may stimulate or restrict knowledge creation. Equally, multinational enterprises (MNEs) may promote the development of new knowledge in competitive markets but stifle it in monopolistic markets where they may seek to prolong the economic life of obsolete knowledge.

Of central importance to any knowledge system is the interaction between the various elements, for it is these interactions that give rise to the system. As Foray (1997, 64) notes, it is the frequency of such interaction that determines the cohesiveness of a knowledge system. In the international context, it is possible to identify a number of channels facilitating interaction. Firstly, MNEs clearly have a significant role not only in the creation of new technology in an international environment but also as facilitators of international interactions of knowledge both within the boundaries of the firm and externally through trade in goods and services, and the sale of technology through licensing agreements (Howells 1998; Granstrand et al. 1992). Secondly, international technical alliances give rise to knowledge interactions between firms from different countries, and between MNEs and national based firms. Thirdly, international technology transfer including within the boundaries of the MNE and through the purchase of technology through licensing agreements between both MNEs and national based firms and between national based firms across borders. Fourthly, knowledge interactions through the international trade of capital, intermediate and final goods. Fifthly, international interactions of knowledge are embodied in labour, in particular managerial, and science and technology personnel, and are facilitated through cross border collaboration between researchers. Sixthly, knowledge interactions arise from joint international science projects, for example EU initiatives such as EUREKA. Seventhly, trade and Foreign Direct Investment (FDI) in services, such as technical and management consultancy services, facilitate knowledge interactions such as, technical and management consultancy services, and educational services facilitate knowledge interactions. Finally, knowledge interaction occurs through a wide variety of social and cultural cross-border mechanisms. Given that the social and cultural characteristics of nations have been associated with their economic performance (Landes 1999; Fukuyama 1995), such mechanisms may well have an important role in the development and sustainability of international knowledge systems.

Indicators of international knowledge interactions are well advanced at a general level. They include data on the flows of technology payments, global diffusion of patents, trade in embodied technology and joint R&D consortia. According to the OECD (1997, 29) these indicators are increasing over time for all OECD countries, although at a different level and rate, indicating the growing significance of inputs of international knowledge to national knowledge systems. However, these indicators fail to capture all international knowledge transaction, they clearly are more useful in terms of assessing knowledge interaction of relevance to systems of innovation. International interactions relevant to knowledge systems must include, in addition to the flows listed above, international labour mobility, cultural and social exchanges through the movement of individuals, whether permanent or temporary, and through media and ICT channels. Furthermore, knowledge diffused by international organisations such as the World Bank and the OECD, as well as non-governmental organisations, like Green Peace, should also be included.

Service sector MNEs, particularly those supplying business services, are becoming increasingly important facilitators of knowledge transfer (Grosse 1996). The internationalisation of business service firms is well advanced, and has attracted much attention in recent years (Aharoni, 1993; Roberts 1998; inter alia). Moreover, studies of business services reveal them to be significant factors influencing the dynamics of growth, innovation diffusion, productivity levels, and competitiveness across firms, sectors and regions (Perry 1991; O’Farrell and Moffat 1995; Miles et al. 1995). Consequently, the role of business services as facilitators of knowledge transfer in an international context should be recognised. Estimates of trade and FDI in the business services sector provide some indication of the growing level of international knowledge transfer enabled by these activities. For example, European Union credits arising from other business services, which include advertising, accountancy and management consulting services, increased from a value of US$ 30,281 million in 1987 to US$ 129,535 million in 1996. Whilst for the US, over the same period, credits arising from other business services rose from US$ 10,635 million to US$ 32,360 million (OECD/EUROSTAT, 1999: 76-77).

Knowledge Intensive Business Services have been identified as not only sources of new knowledge and innovation but also important facilitators of the transfer of knowledge both the regional and national contexts (Miles et al. 1995, Antonelli 1999). In particular, as AntonnelliAntonelli (1999) notes, KIBS act as an interface between ‘quasi-generic’ knowledge, extracted by means of repeated interactions with customers and the scientific community; and the tacit knowledge buried in the routines of firms. Multinational providers of KIBS therefore perform an important function enabling the international transfer of knowledge.

Table 2. Knowledge Intensive Business Services

KIBS I: Traditional Professional Services, liable to be intensive users of new technology:
  • Marketing/advertising;
  • Training (other than in new technologies);
  • Design (other than that involving new technologies);
  • Some Financial services (e.g. securities and stock-market-related activities);
  • Office services (other than those involving new office equipment, and excluding "physical" services like cleaning);
  • Building services )e.g. architecture; surveying; construction engineering, but excluding services involving new IT equipment such as Building Energy Management Systems);
  • Management Consultancy (other than that involving new technology);
  • Accounting and bookkeeping;
  • Legal services;
  • Environmental services (not involving new technology, e.g. environmental law; and not based on old technology e.g. elementary waste disposal services).
KIBS II: New Technology-Based KIBS:
  • Computer networks/telematics (e.g. VANs, on-line databases);
  • Some Telecommunications (especially new business services);
  • Software;
  • Other Computer-related services – e.g. Facilities Management;
  • Training in new technologies;
  • Design involving new office equipment;
  • Office services (centrally involving new IT equipment such as Building Energy Management Systems);
  • Management Consultancy involving new technology;
  • Technical engineering;
  • Environmental services involving new technology; e.g. remediation; monitotingmonitoring; Scientific/laboratory services;
  • R&D Consultancy and "high-tech boutiques".

Source: Miles et al. 1995.

 

Miles et al. (1995) identify two types of KIBS (Table 2). The first consists of traditional professional services, such as accountancy and legal services, based upon specialised knowledge of administrative systems and social affairs. These services typically help users to negotiate complex social, physical, psychological and biological systems. The second group of KIBS consists of new services connected with technology, and with the production and transfer of knowledge about new technology. Technology-based KIBS (t-KIBS) include for example computer-related services and technical engineering services.

The increasingly complex and rapidly changing technological and economic environment account for the increasing demand for KIBS. Clearly, they play an important and varied role in both the creation and diffusion of knowledge. In the following section a framework is presented which identifies KIBS as important facilitators of knowledge transfer in an international context.

Although it is clear that international knowledge interactions take a variety of forms, evidence and research into these interactions is limited. Much research has, however, been conducted into the role of the MNE in the context of innovation. This research can be usefully reviewed to gain an appreciation of the role of the MNE, which is regarded as a central actor in international knowledge systems (Cantwell 1995). In the late 1980s, for example, MNEs accounted for between 75 and 80 percent of the privately undertaken R&D in the world (Dunning 1993, 290). Although MNEs are active in international markets it is not necessarily the case that their knowledge creating activity occurs in the same dispersed manner. Indeed, it is generally accepted that the globalisation of knowledge creation in the form of R&D activity is far from widespread (Archibugi and Michie 1995; Patel and Pavitt 1991; Pearce 1989). MNEs adopt a variety of strategies regarding the location of their R&D. These can be broadly grouped into either a centralised strategy where much of the R&D occurs in the MNE's home nation, or alternatively a decentralised strategy where R&D activity is dispersed between a number of nations. Literature on the internationalization of industrial research (Pearce and Singh 1991; Granstrand, Hakanson and Sjolander 1992) has suggested that innovation may be geographically dispersed within MNEs.

When MNEs adopt a centralised R&D strategy then clearly the knowledge system in its home nation will be of great significance. An international knowledge system will, however, have an impact on the innovatory activity of MNEs whether their R&D is centralised or not. Indeed, any firm that either supplies international markets, or draws resources from the international environment, may be influenced by institutions that constitute the international knowledge systems. For those MNEs that adopt a decentralised R&D strategy a number of different national knowledge systems may be of relevance and the international knowledge system may have an even more significance influence.

Of central interest to the development and operation of international knowledge systems are those MNEs that undertake R&D in a geographically dispersed manner. In many sectors the knowledge creating process is highly internationalised. R&D teams are drawn form across the globe, perhaps working in one geographical location or alternatively, with the support of ICTs and cross border travel, in a spatially dispersed network (Howells 1990; 1995; Lewis 1998; Boutellier et al. 1998). In such a way, MNEs develop intra-firm networks between established centres of excellence. These are complementary to external inter-firm networks, which facilitate the exchange of knowledge and occasional cooperation in learning through joint ventures. Cantwell (1995, 157) argues that it is in this way that technology leaders are involved in the globalisation of technology.

The MNE clearly has a significant and multi-dimensional role within international knowledge systems. Knowledge is however shared at an international level through a variety of other institutional and organisational arrangements. To gain a full appreciation of international knowledge systems research must reach beyond the MNE to an examination of the role of other facilitators of knowledge creation and dissemination operating at an international level. Having broadly defined international knowledge systems it is now possible to explore the manner in which they interact with national, regional, local and sector specific knowledge systems.

THE INTERACTION OF KNOWLEDGE SYSTEMS: The Role of GLOBAL Business services

The purpose of this section is to formalise the complex web of interaction that arises from the actions of the various elements that make up an international knowledge system. The conceptual analysis of knowledge systems outlined earlier highlights Two approaches for conceptualising these interactions are outlined and compared, firstly the hierarchical structure and secondly the network or heterarchy structure. The hierarchical form of international knowledge system is represented in Figure 14.2a. In this structure international actors can be viewed as determining the international knowledge system, which has an impact upon national actors and the national knowledge systems, which in turn influences regional actors and the regional knowledge systems and so on. The flow of influence is largely unidirectional. For specific knowledge-creating activity, certain elements within the hierarchy may prove to be more influential than others. A high level of interaction may be identified between such elements, this can be referred to as process of ‘nesting’ since a sub-structure is developed within the overall hierarchical structure, in order to nurture a particular knowledge activity. two sub-systems which together constitute the knowledge system: that is the knowledge sub-system and the quasi knowledge sub-system. As noted KIBS are important facilitators of knowledge transfer. As a consequence of their interaction with client firms they engage in knowledge transfer at the level of both sub-systems. In terms of the knowledge sub-system this is achieved through close co-operation with individuals and teams within the client firm. Such interaction takes the form of regular face-to-face contact with individuals, and it is within this social context that a two-way exchange of tacit knowledge can occur through the development of mutual understanding and a process of learning. In this way KIBS firms absorb tacit knowledge from one knowledge system and distribute it to another. Similarly, KIBS absorb and distribute codified knowledge. Furthermore, they play an important role assisting the transfer of tacit knowledge into codified form, whether in the client firm or within the KIBS firm itself. For example, as a result of contact with many clients a KIBS firm may engage in innovative activity that results in the codification of knowledge previously embedded in the teams and routines of a group of client firms. By providing this newly codified knowledge to new and existing clients, KIBS engage in the transfer of knowledge between firms.

 

The hierarchical structure may capture the essential structure of certain knowledge systems. Knowledge creation at a national level may indeed include actors that are international in scope. For example, the establishment of international regulatory bodies, such as the International Telecommunications Union (ITU) and on a pan-national level the European Medicines Evaluation Agency (EMEA), may have a significant role in the knowledge system within the telecommunications and pharmaceuticals, and related sectors at both a national, regional and local level. Furthermore, MNEs with market power at an international level may also influence knowledge creation at a lower scales through the establishment of technical standards. For example, in the computer manufacturing and services sector IBM had such an impact from the 1960s through to the 1980s, and in the 1990s Microsoft has a central role influencing software development. Knowledge intensive business service firms assist the circulation of knowledge concerning regulatory structures both within and between national and regional knowledge systems. For example, the global accountancy firms play an important role disseminating knowledge about international and national accounting regulatory systems to their clients whether these are internationally active or nationally based companies. They may also enable the flow of knowledge from client firms to national and international regulatory bodies through, for instance, lobbying national and international policy making organisations on behalf of their clients.

Similarly, advertising firms play an important role transferring region and nation specific cultural and social knowledge to their clients. They may also, through advertising campaigns, shape cultural and social knowledge on behalf of their clients. Global KIBS firms, in a sense, provided bridges connecting different national and regional knowledge systems. Such firms provided this role for both national and multinational firms. National firms can access a wide international pool of knowledge through their links with global KIBS firms. Similarly, national based KIBS firms enable MNEs to tap into national and regional knowledge systems that are not service by global KIBS firms, perhaps because they are newly emerging or simply not profitable for the attention of large KIBS firms. Indeed, global KIBS firms themselves may employ smaller KIBS firms in order to gain access to locationally specific knowledge.

 

The network or heterarchy structure is illustrated in Figure 14.2b. In this structure various knowledge systems interact in their influence on the knowledge creating, transmitting, transforming and storing process. The links between the various actors depend upon the environment in which the knowledge activity is occurring, that is, whether local, regional, national, or sector specific. The various groups of actors overlap and interact in their influence on the knowledge creating process. In this framework the influence of interactions are multi-directional. Certain groups of actors may dominate for periods, for example, national actors may be of most significance in the initial development of new knowledge, however, under this structure it is recognised that this dominant position is temporary. The influence of certain elements within the system cluster at specific spatial and temporal points. The network structure is highly dynamic. Clearly, KIBS play an important role in the creation and distribution of knowledge in a regional, national and international context. The role of KIBS is summarised in Figure 2 (p.24) which illustrated the flows of knowledge between and within knowledge systems. The role of KIBS is complex, and, as yet, poorly appreciated. Given the increasing importance placed on knowledge and innovation as sources of economic prosperity the significance of KIBS is set to increase. Empirical research is required to develop upon the analysis presented here.

To develop further our appreciation of international knowledge systems it is useful to examine a specific example. The computer services sector represents a useful sector to explore, since it is highly international and dynamic in nature. One can therefore expect to see much interaction between elements which constitute the sector’s knowledge system at various spatial levels. The levels of knowledge interaction in this sector are depicted in Figure 14.3. The knowledge system within computer services can be seen as operating at all spatial scales. One can move from individual knowledge processing, where programmers work on, for example, the design and development of new software programs to the more collective process of software project articulation and the subsequent testing and implementation of software programs involving wider groups of software workers working within the software company and the clients’ firm. Knowledge activity therefore involves constant circuits and iterations between the individual and the collective; from knowledge work within the individual to knowledge processing between other single individuals, groups of workers, and other firms and organisations. Moving further up the spatial scale the role of institutions and ‘superstructure’ organisations which act to provide collective goods to their members and helping to facilitate and coordinate the flow of information to ‘substructure’ firms who are at actual core of the innovation process (Lynn et al. 1996). These superstructure organisations include industry associations and standards authorities, such as the UK Computer Services and Software Association or the American National Standards Institute, help provide a framework for the knowledge processing activities, but in turn are also shaped by individual firms and organisations. Individual firms or organisations can create de facto standards such as US Department of Defense (DoD) which helped create the high-order programming language, COBOL, through setting up an industry committee in 1959 (Mowery and Langlois 1996, 960; Steinmueller 1996, 22-3). Similarly DoD coding and programming standards, such as MIL-STD-882, can become more widely adopted throughout the wider computing community. More recently there has been the example of Microsoft with its Windows software creating a global industry software platform. Firm or organisational knowledge frameworks can break out and become industry or international knowledge standards. Equally high-level international standards, associated with organisations, such as the International Electrotechnic Commission (IEC), can create knowledge frameworks which impact down the spatial knowledge scale. All the these knowledge interactions, combinations and their dynamics creates highly complex knowledge systems, which are subject to change and individual and firm-level interpretation.

The characteristics of the system or the way in which it functions will depend on the nature of the knowledge created, the speed of its evolution, and the extent to which it can be internationally communicated and dispersed. In the computer software sector, and other related and high technology sectors, products are developed rapidly and quickly become obsolete. In such sectors, knowledge is highly dynamic and interaction will occur within a network structure. In sectors with slower levels of technological change international knowledge interactions are more likely to occur within hierarchical structures. Indeed, because sectors may include a wide range of activities, some of which are more dynamic than others, it may be possible to identify relevant hierarchical and network structured knowledge systems of relevance to a sector’s knowledge activity.

 

 

 

CONCLUSION

This paper has examined knowledge systems in an international context. Building on literature concerning systems of innovation, knowledge systems have been defined in both a national and international context. It is argued here that knowledge systems are a broader more nebulous concept than systems of innovation. Consequently, in their consideration it is necessary to look beyond those factors usually associated with systems of innovation. Knowledge is highly complex and cannot be separated from the individual, hence knowledge systems must give particular attention to the mechanisms through which knowledge is transferred and especially through the process of learning. More generally, though, a knowledge system includes a variety of organisational and institutional factors. Since it is argued here that knowledge is fundamentally individual centred the social context and relations are of great significance in the creation and dissemination of knowledge. The role of KIBS in tapping into firm specific social contexts and thereby absorbing knowledge that can be diffused to other client firms has been highlighted.

A major research challenge concerns the exploration and analysis of the individual and social relations in an international context. Here interactions are complicated by the diversity in cultural and social norms between countries and regions.

For advanced industrialised countries knowledge is becoming the only resources capable of offering competitive advantage and continued growth and prosperity. Although knowledge has not replaced the traditional factors of production they are becoming secondary (Drucker 1993, 42). In the emerging knowledge-based economy (OECD 1996) an appreciation of the creation, codification, diffusion and absorption of knowledge is vital for policy makers, since government action can do much to promote the successful development of knowledge-based activity and the learning economy (Lundvall and Johnson 1994; Hodgson 1999). Policy makers must though have an understanding of knowledge systems and how these interact, both in the national and international context.

This paper presents an initial attempt to analyse knowledge systems in an international context. The frameworks developed here provide tools that can assist policy makers in their efforts to analyse knowledge systems. The paper has highlighted the role of KIBS in the international transfer of knowledge, however, clearly further research is required to build upon the conceptual framework findings presented here, and empirical research is necessary to verify the analysis. Moreover, efforts to identify, measure and assess a wider range of knowledge interactions, as well as the barriers to such interactions, at a national and international level are required.

 

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Table 1. Knowledge Systems: Institutional Structure.

Institutional Factors NationalExamples: SupranationalExamples:
Socio-cultural Language; religion; levels of trust; degree of openness/insularity/tolerance; behavioural norms Degree of cross cultural harmonisation; international communications through use of common language - English.
Legal Property rights; patent and copyright systems; employment legislation; immigration laws. International law; international patent and copyright regulation; EU wide employment regulations; international agreements GATT, GATS, IPR, TRIPS etc.
Political Ideology; political structures; policy communities. Dominant ideology - liberal democracy; the cross border coordination of policy – OECD; IMF, World Bank, WTO, G7, EU, NAFTA, UN.
Economic environment Level of current and prospective economic growth; business environment and industrial structure; factor endowments; mobility of factors of production. International flows of capital, commodities, labour and information; global business environment - degree of stability and economic growth; sector structures – level of competition in international markets.
Policy measures Competition & industrial policy; science & technology policy; trade and foreign direct investment policy; fiscal incentives: taxes and subsidies relating to innovation; educational policy. Cross country, science and technology policies, and government sponsored international research programmes; harmonisation of sector wide regulation/standards – International Telecommunications; education – harmonisation of syllabus content across countries and international exchange programmes for both academics and students.
Other National trade associations; privately funded national research programmes; communication infrastructure; local, regional, national interest groups; industrial clusters and centres of excellence. Multinational enterprises; international interest groups; joint ventures, international strategic alliances and other forms of collaborations between national and multinational firms; privately sponsored international student exchanges; international secondments within firms and international organisations; privately funded international research programmes; international private sector scientific organisations; international trade association; internationally mobile scientists and knowledge workers.

Figure 2. International Knowledge Systems.

Figure 3. Knowledge Systems: Levels of Knowledge Interaction in the Computer Services Industry



MICRO MESO MACRO

Level/Scale of Interaction

Abstract or Generic Process/Issue

Computer Services

Individual

 

Information scanning/

accessing

Knowledge Assimilation

generation/

enhancement

Absorption

   

-Design and development of new software programs

-Software testing

Business unit/ site/ team

 

Open sources

 

-On-site turnkey software development/maintenance

Firm/organisation

 

Education /training courses

   

-Internal coding/programming practices, e.g. DOD MIL-STD-882

   

IBM User Group-‘GUIDE’

Security/

Encryption standards

-Software training

Inter-Firm

     

-Computer language/operating systems e.g. COBOL, FORTRAN, Java, Windows, Unix

Industry/Sector

Industrial Standards

     

X/open ‘standards’ group for Unix

Inter-Industry

     

‘Industry’ standards, e.g. Open Systems Interconnections (OSI)

 

Local/Regional

         

National

National trade associations e.g. American National Standards Institute (ANSI)

National industrial policies

UK Computer Services and Software Association

US Computer Software Copyright Act

Brazilian National Software Export Program

   

International

International standards organisations

EU Computer Software Directive

International Electrotechnic Commission (IEC)

Supra-National

WTO

TRIPS

     

Note: DOD – US Department of Defense; WTO – World Trade Organisation; TRIPs – Trade-Related Intellectual Property Rights