Hi all,

I’ve bundled the PowerPoint notes into this document and they now need ‘unpacking’ I’ve tried to group them into some sort of layout but doubt this will be the final one.

Your bullet points have been colour coded as below so it is easy to see which bits are yours to expand into paragraphs etc. Eventually the contributions will all become mingled into an appropriate fashion, but it is impossible to do at the moment without more info regarding each comment.

Andrew/Raphie Diane/Souad Paul Kathryn/Rhodes

I am not sure the best way to proceed on developing a unified literature review; I already have an entire folder of new papers that I need to read. However, I do suggest that we get this paper into order first before adding anything new because of the danger of it becoming unmanageable (I’ve started to expand mine and it is already turning into a huge document!).

If you could please work on your sections, turning them into sentences! (I’ve added the odd comment – makes me feel important!) and then send it back and I’ll put together a draft three for us to look at.

General outline

1. Intro2. Knowledge3. The importance of knowledge4. The movement of knowledge5. Trust and psychological contracts6. Human resource management7. Introducing the concept of knowledge leakage8. Strategy

Bibliography

9. Literature Summary – Draft 2 – 7th Dec 05Rhodes

Developing the Concept of Knowledge Leakage (KL) and providing insights from a range of disciplines into the effect of KL on UK productivity.

1. Introduction

Something about productivity and the productivity gap etc? Link between knowledge and productivity, importance etc – why were looking at the two together.

Small intro to KL

General intro to what’s coming

To do later on

1.1 Context

Boundries – not set yet, literature below kept wide

This will emerge as we continue (I hope!)

SME’s as high risk (evidence? Is this what were focussing on? – Diane I think – was in the Sept ppt on the portal)

1.2 Project drivers (from the Sept PowerPoint)

outsourcing of non-core activities introduction of lean lower tier companies to provide integrated solutions rather than mere

components the movement of low value adding activities to low cost base regions cluster activities and coordinated value chains

Needs writing up into a paragraph or two along with any other info

2. Knowledge

– More needed - Km stuff (Rhodes to look at Paul’s papers), Audits, Rhodes PhD etc

– Rhodes to develop

Intro – understanding types of knowledge in companies….lead to an understanding of knowledge leakage….etc

Diff between knowledge and information (Vohinger, Kuosmanen and Dellink, 2004, Strategic Direction, 2005) – expand Souad

Raphie - Embodied and disembodied knowledge

Knowledge can be incorporate in machinery and products – economists refer to this as embodied knowledge. It can also be incorporated in people, routines, on paper and in electronic form – economists refer to this as disembodied knowledge. Knowledge stuck in individuals (or communities of individuals) which has not been captured and routinised and therefore can essentially be lost.

Knowledge can be tacit or codified

Knowledge can be codified – in written-down routines, in structured programmes of knowledge management, in IPRs. But they can also be tacit, embodied in the minds of humans, routines and structures.

In general, without IPRs, the greater the codifiability of knowledge, the lower the barriers to entry. Codification is thus a danger. But at the same time, the absence of codifiability may often mean that firms may fail to systematise their knowledge base and maximise the returns from their knowledge stocks and knowledge flows.

Similarities between disembodied and tacit – disembodied is held within people rather than machines – some of this disembodied knowledge may indeed be tacit – it cannot be made explicit, however there may also be disembodied knowledge held by the person that can be made explicit should the person choose to do so.

Disembodied and tacit – I don’t know what it should sound like but I’ll know when I hear it.Disembodied but NOT tacit - I know you have to tap on the side of this machine to make it work, but haven’t told anyone

Andrew – shared knowledge (between organisations), Protected knowledge (e.g. by patents), protectable knowledge (non-disclosure agreements), open source, rigid (legal), dynamic etc.

Knowledge can be classified as either explicit or tacit knowledge; the former being easily codified and the latter being embedded in the human brain and cannot be expressed easily (Grover and Davenport, 2001). The concept of tacit knowledge has hitherto found fascination among organisational/management theorists and the knowledge management research community and is derived from the philosopher Polanyi (1958), popularised by Nonaka (1991).

Styhre (2004) through reviewing the literature on tacit knowledge, highlighted Boisot’s (1998) distinctions of tacit knowledge to include:1. Things that are not said because everybody understands them and takes them for

granted;2. Things that are not said because nobody fully understands them. They remain elusive

and inarticulate;

3. things that are not said beause while some people can understand them, they cannot costlessly articulate them.

Styhre (2004) suggested that knowledge management theorists have been emphasising the third variant and it is the second variant that Polanyi had initially talked about. (Comment: The Knowledge Leakage project is precisely addressing, in my opinion, Boisot’s first and more importantly, second variants.) Styhre (2004) further critiqued that the demarcation between explicit and tacit knowledge is a false dichotomy as he employed Bergson’s sensualist process philosophy to point out that explicit and tacit knowledge is intertwined; a continuum between intellect and intuition.

This fits several similar classifications of knowledge found in the literature. For example, Gibbons et al. (1994) and Gibbons (1998) defined knowledge as Mode I and Mode II knowledge; the former being linked to scientific knowledge and the latter being application-oriented which is contextually-bound. Billett (1997) identified knowledge as propositional (i.e. Mode I), procedural (i.e. Mode II) and included a third category: dispositional (i.e. learnt values, attitudes and interests that predispose the acquisition and treatment of knowledge) (See Harrison and Kessels, 2004: 150 for a fuller explanation.) This is not dissimilar to Mukherjee’s et al. (1998) suggestion of conceptual versus operational knowledge: where the former relates to know-why and the latter relates to know-how. Arguably, these echo knowledge in a Popperian sense, where Popper’s (1979) three worlds can be summarised as follows: “World 1 consists of the physical world of objects and states. World 2 is the world of the subject which consists of consciousness, of subjective experiences and understanding. World 3 consists of objective knowledge, knowledge which is independent of the knower (Blackman et al., 2004: 12)”. However, rather than depict the three worlds as discrete entities, Popper (1983) argued, “world 3 objects have an effect on world 1 only through human intervention, the intervention of their makers; more especially, through being grasped, which is a world 2 process, a mental process, or more precisely in which world 2 and world 3 interact (p. 265)”, thereby invoking Styhre’s (2004) proposition of a continuum between intellect (objective knowledge) and intuition (subjective understanding). (See also Nelson and Winter (1982) on the incompleteness of knowledge) Indeed Tsoukas and Mylonopoulos (2004) appreciate that “theoretical knowledge, practical application and social context are all inextricably linked (p. S2)”.Classifying knowledgeExplicit versus tacit knowledgeMode I and Mode II knowledge (also Popper’s Mode III)Propositional, procedural and dispositional (Harrison, 2004) Can you define each of these with a few words Paul

3. The importance of knowledge

intro – diff types of knowledge – greater or lesser importance, different implications if lost of leaked etc

3.1 Dynamic capabilities and core-competences

Andrew – can you turn this lot (red) into expanded paragraphs:

Dynamic capabilities are the resources and capabilities that a firm draws upon to affect change.

These capabilities are limited by:The history of the firm such as technological trajectories (Teece, Pisano and Shuen, 1997);Market (e.g knowledge of market characteristics deter new market exploration;Relationships (e.g member of buyer network)

Resources – derived from RBV – rather than the capabilities per se (Eisenhardt and Martin, 2000)

Examples include:Internal capabilities that are explicit and homogenous such as product development and

strategic decision making which pool business, functional and personal expertise (Eisenhardt and martin, 2000)

Internal capabilities that are tacit and heterogeneous such as knowledge resources (Kogut, 1996; Grant, 1996); and Inter-relationship capabilities including commercial alliances/inter-firm cooperation (Eisenhardt and Martin, 2000; Lorenzoni and Lipparini, 1999; Schmitz and Knorringa, 2000; Bessant, Kaplinsky, Lamming, 2003)

Core Competences are:

Capabilities that are unique to particular firms, desired in the marketplace and difficult to copyThe collective learning in an organization, especially how to coordinate diverse production skills and integrate multiple streams of technology (Prahalad and Hamel, 1990).

Firms tend to list their capabilities but not their core competences.Firms unlikely to build expertise in more than 5 or 6 fundamental competences.Core products are ‘lynchpins’ leading to a proliferation of end products – for example, Honda’s engines (Prahalad and Hamel, 1990)

Andrew, could you please insert(where ever you see fit) your competences: the roots of competativeness diagram (refs?)

Complimentary Concepts

In recent years the capability approach has been supplemented by a wider perspective that recognises the primacy of inter-firm linkages in the attainment of systemic efficiency:

Global production networks (Ernst and Kim 2002; Henderson, Dicken et al, 2002)Lean production systems (Womack and Jones 1996)Supply chain management (Bessant, Kaplinsky et al, 2003)New Product Development (Wheelwright and Clark, 1992; Oliver and blakeborough, 1998) Learning networks (Bessant and Tsekouras 2001)Value Chain Framework (Gereffi, 1994; Gereffi and Kaplinsky 2002, Kaplinsky and Morris, 2001)

Paul – can you expand on these (green):

Resource-based view of the firm, as in above provided by Andrew. In addition, consider the following:

Scarbrough (1998) attacks the resource-based view of the firm for resulting in a weak link between competencies and performance, as he maintains “little attempt to demonstrate the mechanical links, between competencies and performance, other than in the broad terms of the root and branch metaphor propounded by Prahalad and Hamel (1990) (p. 224, original emphasis)”. Consequently, “theorists attempt only the sketchiest account of the nature of resources and competencies, preferring to identify them inductively from evidence on a firm’s functional outputs or competitive advantage (Scarbrough, 1998: 223)”. It is observed that our understanding of knowledge remains abstract, as Styhre (2004) argues “the doctrine of tacit knowledge is based on a belief in a rational human mind that can structure, organise and make sense of complex realities; when this process is not fully understood, the forms of knowledge generated are called tacit knowledge; tacit knowledge is thus an anomaly in a representativistic paradigm, a failure to express what we think we know; it is rare that the assumptions and underlying ideas of the notion of tacit knowledge are articulated or discussed.” Taylor (2002) also lamented on the level of abstraction where knowledge is concerned, and suggested that “Honest probing is needed now, rather than glib answers”. (Comment: Arguably, the Knowledge Leakage project is attempting to do this probing.)

On Peter Drucker’s shelf-life of knowledge, Andrew’s contribution on the six factors (towards the end of the document; ref: Drucker, 1999) would be useful here.

On agency theory versus stakeholder theory, see e.g. Shankman, 1999. There is a fundamental dominance of the agency theoretical perspective, which relies heavily on economic perspective (Comment: very reductionistic and opportunistic in my view). My personal opinion: The agency perspective contrasts sharply with the stakeholder perspective where cooperation is desired (see later when I discuss Paul Adler’s alternative view of Marxism and Trust). Another personal opinion that needs verification in the literature: I observe that many studies at the firm level tended to view from an intra-organisational perspective, and there needs to be a resolution of the inter-organisational viewpoint. On this point, a conflict in the notion of core-competencies arises; that is, if we now are suppose to cooperate with our supply chain, to whom will the competitive advantage belong to? The host organisation where the core-competence is developed? To the strategic alliance? Perhaps the Knowledge Leakage project can shed some light on this. Apologies for being quite inarticulate here, but I’m still in the thinking process on this.

On inter-play between state and industry, see Harrison and Kessels, 2004. State intervention in promoting lifelong learning and the development of a knowledge economy via national policy that has a strategic outlook (Harrison and Kessels, 2004; see also Lam, 1998, 2000). (Comment: The Knowledge Leakage project has the potential to develop a framework that can aid policy makers via the sandpit programme.)Resource-based view of the firm

Hamel and Prahalad’s notion of core-competencies (the challenge and need to identify clusters of ‘know-how’)Drucker suggested that knowledge has a shelf-life and constantly necessitates refreshing

Agency theory versus Stakeholder theory

Inter-play between the state and industry (lessons on social partnership in Continental Europe; also the Singapore example)

Raphies ‘stuff’ (technical term!):The challenge for the firm is sustainable profitability. In a highly competitive world, this requires the development both of internal dynamic capabilities, and the ability to influence the external world. Our challenge is with the dynamic capabilities side of this story.

Profitability is defined by the ability to construct or take advantage of barriers to the entry of competitors. Economists refer to this as the ability to appropriate “rents”, that is to take advantage of scarcity:

Rent describes a situation where the parties who control a particular set of resources are able to gain from scarcity by insulating themselves from competition. This is achieved by taking advantage of, or by creating barriers to the entry of competitors.

Schumpeter provided an analytical framework to show how scarcity can be constructed. He distinguished the process of “invention” (having an original idea, a “new combination” in his words) from that of “innovation” (turning a new idea to commercial advantage), Entrepreneurship is defined in the act of innovation. If this innovation proves to be difficult to copy, then the entrepreneur earns a super-profit which exceeds not only the cost of the invention and the associated innovation, but the returns to economic activity in other activities which are less well protected from competition. Over time this innovation is copied (the act of “diffusion”) or superseded by a new, superior innovation. It is this “Schumpeterian motor”, the search for producer rents, which spurs the innovation process and subsequent diffusion and which drives forward economic growth. For Schumpeter, the entrepreneurial rents were almost always dynamic.

Figure 3.4 shows the process at work. In each industry the equilibrium is defined by the “average” rate of profit. Following the introduction of a “new combination”, the entrepreneur reaps an “entrepreneurial surplus” which provides for abnormal high incomes. Then as the new combination is copied and diffuses, the producer surplus is whittled away, and is transformed into a consumer surplus as prices fall and new and better quality products are made widely available. But all this does is to renew the search for “new combinations”, either by the same entrepreneur or another entrepreneur.

Figure 3.4: The generation and dissipation of entrepreneurial surplus

Rate of profit

Average rateof profit

Time

It is obvious from this that the link between innovation and income is to be found in barriers to entry which keep out competition. Given that a product is being produced which consumers want, the greater the barriers to entry, the more likely incomes will be high. So, the key questions for the producer are - how impervious are these barriers?; can the “new combination” be easily copied?; can it be circumvented, perhaps by using a similar process?; or, can it be superseded, by a new and even better combination? Thus it is that barriers to

Entrepreneurial Surplus

Innovation 1 Innovation 2 Innovation 3

entry are a central component of the theory of rent, and similarly that the theory of rent provides the key to understanding the availability and sustainability of high incomes.

In the current era, with the rapid progress of China, India and other low wage economies (including those in Eastern Europe), the barriers to entry are tending to be eroded in the physical transformation links in many value chains. In the development of dynamic capabilities, these are the easiest to master and “manufacturing” capabilities are becoming increasingly widespread. Conversely, the most enduring barriers to entry are increasingly found in knowledge-intensive sectors and activities, such as design, chain coordination (Tesco!) and marketing. This involves a combination of both moving to knowledge-intensive links in the chain ((fnctional upgrading in the value chain literature), and into knowledge-intensive activities within each link in the chain (process and product upgrading).

The East Asian countries which have successfully industrialised in the last quarter of the twentieth century, based in large part on the export of manufactures have been very systematic about this strategic positioning. Figure 4.6. shows the upgrading path which they have used. It is a path which begins with the simple assembly of components (OEA – original equipment assembly), and upgrades into the manufacture and assembly of products sold under the brandnames of other firms (OEM – original equipment manufacture). Then, when manufacturing in these sectors become too competitive, they have developed their own brands (OBM – own brand manufacturing), such as Daewoo and Samsung. But when even this is unable to protect their rents, they branch out into new chains. As Figure 4.6 shows, this is an upgrading path in which disembodied-knowledge rather than production skills alone becomes increasingly important.

Figure 4.6: The ideal-type of a successful value chain upgrading strategy

Type of upgrading Process Product Functional Chain

Trajectory

Examples Original equipment assembly

(OEA)

Original equipment

manufactureOEM

Original design manufacture

Original brand manufacture

Moving chains – e.g. from black and white TV

tubes to computer monitors

Degree of knowledge-intensity

Disembodied content of value added increases progressively

To summarise:

Sustainable incomes arise from barriers to entry and involve the appropriate of rents

The lower the knowledge-intensity in production, the more likely that firms will see their rents (and hence their profitability) eroded.

The ability to command and generate knowledge is thus the key component of dynamic capabilities and long term and sustainable profitability.

3.2 Knowledge intensity

Intro of some sort – how much a companies activities rely on knowledge….how critical it would be for KL to occur etc….

Rhodes to expand her stuff (pink):

high technology also a term – do a search

Ways of measuring knowledge intensityThrough R&D expenditure – harder to track with some outsourcing firms also engaging in R&D, 1980’s OECD classification, DTI top 750 companies etcThrough employee qualifications (Smith 2002)No of patentsThrough the development of a hierarchy of knowledge type tasksThrough taking a stock of managerial and production techniquesThrough an audit of current knowledge and future knowledge possibilities based on current knowledge (other knowledge audits)(Aution, Sapienza and Almeida, 1999, Smith, 2002, Shadbolt and Milton, 1999, Roper and Cronet, 2003, Ndofor and Levitas, 2004)

Through identification of technological intensity of the degree of sophistication and customisation of the production process (Lepak, Tekeuchi and Snell, 2003)By taking a stock of knowledge through a taxonomy of forms of knowledge, and the use of manufacturing techniques as inductive of the strength of the companies knowledge base (see table) (Roper and Cronet, 2003)

Table ? managerial, production and organizational techniques (Roper and Cronet 2003)

Management assessment questionnaires (see figure)

Knowledge intensity questions (Autio, Sapienza and Almeida, 1999)

Studies undertaken by the Work and Employment Research Centre (WERC)The need to excite knowledge workers with interesting workDevelopment of knowledge workers has to be done inductively rather than top downSample of research and technology organisations - expand please Paul and relate

to knowledge intensityWork done by Work and Employment Research Centre (WERC) in Bath on Knowledge Intensive firms focussed on knowledge sharing in KIFs (see Swart and Kinnie, 2003).

Swart and Kinnie (2003) reviewed the various definitions of knowledge intensity to develop their precise focus. Examples include:

1. The Tobin’s q ratio (Sveiby, 1997): measuring the relationship between a company’s market value and its replacement value or its physical assets (higher ratio suggest greater knowledge intensity, e.g. 7 for software companies and 1 for steel industry).

2. Knowledge intensity has to be linked to problem-solving; standardised work is not regarded as knowledge-intensive. – “doing a clever thing over and over does not mean it is knowledge intensive (Swart and Kinnie, 2003: 62)”.

3. KIF defined in terms of nature and quality of highly skilled human capital, work processes that create market value through knowledge, and deployment of knowledge involving innovation, initiative and competence building in the provision of bespoke services

Swart and Kinnie (2003) looked at HR practices that enabled knowledge sharing across a software company, as part of a wider CIPD study, and established that:

1. There is a need to excite knowledge workers with interesting work2. Development of knowledge workers has to be done from bottom up inductively

Key comments: the use of knowledge appear to be very sketchy (see comments by Scarbrough, 1998 above). Also, the study focussed on research and technology organisations and our project will perhaps provide greater insights into non-research and technology organisations.

4. The movement of knowledge

Can anyone think of a better title? – info flows in supply chains – problems with info / knowledge and don’t want to just limit it to supply chains – knowledge transfer? Knowledge flow? Knowledge progress?

Raphie - Knowledge stocks and knowledge flows:

Knowledge must be seen in dynamic context – it is both a stock and a flow.

The stocks refer to the accumulated knowledge within the firm

The flows refer to both inflows of knowledge, and outflows of knowledge.

Many firms have weak routines for assessing their knowledge stocks, and maximising the potential returns from these knowledge stocks

To sustain barriers to entry and rents, firms have an active interest in minimising the outflow of knowledge

However, because firms are incorporated in chains, and because they are engaged in dynamic repositioning within their chains, they also have a simultaneous interest maximising inflows of knowledge, and outflows as well (for example, in supply chain development).

Rhodes to unpack:

Highly non-linear, dynamic, complex adaptive systems that differ between supply chains and between entities within supply chains

Types of information flows (possible classifications)

Internal flow external flowPre-product flow post-product flowExplicit flow tacit flowEmbodies flow disembodied flowEpisodic flow continous flowMacro-flow micro-flowProprietry flow shared flow

Understanding the diff types of info flow as they will have diff types of KL associated with them

Relationship effecting information flowRelationship to one anotherComplimentary knowledge portfolios – equal flow(Roper and Cronet’s assessment of complimentarity, 2003)

Relationship between entity and sourceSupply and demand, continous development

Effieicient, continous information flow reduces costs and maintains cycle times. Reduces machine down time (refs?).

Mechanisms for information flowPhone, fax, internet, post, person to person EDI, etc

Info exchangesStandardised / formalised (proformas, spreadsheets etc)Less formalised / casual (comments, remarks etc)

Diff types of flowMaterialsInformationResources

Surely they all have knowledge embedded (dianes comments)(Stefersson, 2002, Johnston 1998, Meer-Kooistra, Jud and Jijlttra, Pittaway, Robertson, Munir, Denver and Neeley,2004, Un and Cuero-Cazura, 2004 – sort refs!)

Table ? Information mechanisms in companies of varying size (Stefersson, 2002)

Forms of flows – inter-flow and intra-flow

Diane

Integration is the key to supply Chain performance. Information integration is important. Supply chain information and non-information characteristics results in business performance.In systems dynamics, a system is viewed as network of stocks and flows. Stock variables represent accumulations. Flows can be of two types. Physical flows either fill or drain stocks. They may only connect stocks and flow must be conserved. Information [FLOW TRIGGERS] flows connect different parts the structure and are used for controlling physical flows. These flows need not be conserved. We use the methodology of systems dynamics (SD) due to its close fit with the purpose. The SD model captures generic physical and information flow characteristics of a supply chain in the manner given below. Number of stages : Each stage of the chain is represented by two stocks representing inventory [STATIONARY KNOWLEDGE] of stage and material in transit [MOVING KNOWLEDGE] ; three flows that represent consumption [___], replenishment [___] and transition [___] from stock in transit to inventory. An n stage structure can be constructed by a cascade of N single stage structures. For this paper we used a two-stage supply chain. Shipping delays : These delays are represented by conveyers, which are simply special cases of stocks, where inflows are accumulated for a certain period of time before flowing out. The delay is determined by the transit time of the conveyer [SUBCONTACTOR…ETC].Information [FLOW TRIGGERS] content: Ordering policies, identified as common information flow content for supply chains, are represented via formulas associated with appropriate converters. The formula we have used indicates that reordering policy can make inventory replenishment more or less sensitive to demand fluctuations by adjusting a factor that expresses aggressiveness of inventory replenishment. Information delays : Information delay is also captured through formulas specifying information flows. (Dutta and Roy, ????)

5. Trust and psychological contracts

Importance of trust in knowledge sharingLack of depth and specifics as to what knowledge is shared (and how types of knowledge is distinguished)Study looked at self-managed teams comprising unionised workers from an intra-organisational perspective in the manufacturing sector (aerospace) (Politis, 2003)

High trust institutional forms to proliferateGrowth in knowledge intensity increases reliance on trustConceptual paper that subscribes to Marxist theory (in particular the concept of ‘community’Need to modern forms of reflective trust (Adler, 2001) Adler (2001) provided an alternative reading into Marxism and conceptually reviewed the concepts of market (i.e. price mechanism), hierarchy (i.e. authority) and trust (i.e. community) literature to illustrate the future of capitalism and the role of the knowledge economy. Adler (2001) proposed that the trend of high-trust institutional forms will proliferate in the knowledge economy (where growth in knowledge-intensity is a trait). However, “for trust to become the dominant mechanism for coordination within organisations, broadly participative governance and multistakeholder control would need to replace autocratic governance and owner control […] for trust to become the dominant mechanism for coordinating between organisations, comprehensive but democratic planning would need to replace market competition as the dominant form of resource allocation (p. 230)”. Adler (2001) qualified the notion of trust to state that it is not “blind” trust. That is, “its rationality is not of the purely calculative kind assumed by economics [rather] the values at work in modern trust are those of the scientific community: universalism, communism, disinterestedness, organised scepticism (p. 227)”, so-called “reflective trust”.

Consider agency versus stakeholder perspectives highlighted above. Also the trend towards supply chain networks and clustering.

expand Paul

Stuff below - Expand Andrew

Learning in collaboration depends on high levels of trust between partners (Buckley and Casson, 1988; 1996)High levels of trust enhances internal organisational effectiveness (Arrow and Phelps, 1975; Fox, 1974)Trust facilitates continuing relationships between firms (macaulay, 1963)As technological collaboration has become more common, the levels and kind of trust relationships between firms is the focus of attention (Jarillo, 1988; Sako, 1992). (Dodgson 1993).

Saxenian’s (1991) study of Silicon Valley firmsThis involves “…relationships with suppliers as involving personal and moral commitments which transcend the expectations of simple business relationships”. (shared carpark etc).

Freeman (1990)Cultural factors such as language, educational background, regional loyalties, shared ideologies and experiences and even common leisure interests will continue to play an important role in collaboration.

TrustMacro

Putnam’s social capital (1991)Micro

Coleman’s game theoretic perspective on risk (‘the risk one takes depends on the performance of the other’, 1990)

Care taken to avoid a functionalist tautology (what’s tautology?)Mutually beneficial co-operation explains mutually beneficial co-operation!Confusing origins of trust and presumed benefits for performance

Farrell and Knight (2003)Defining trust as “a set of expectations held by one party that another party (or parties) will behave in an appropriate manner with regard to a specific issue”

Institutional theoryUsing changes within and between organisations to explain levels of trust (often a case of bargaining between relatively powerful actors to achieve outcomes including co-ordination)Not just institutional compliance (but is an indicator of trustworthiness).

Much of the trust debate uses examples from Italian industries districtsTrust regulates opportunism between co-operating firms.Notion of community and belonging.Breaking the ‘rules’ leads to expulsion from the community (Brusco, 1992)Recent evidence of a breakdown of trust arising out of structural changes in ownership (large firms) and mode of operation (Farrell and Knight, 2003)

An additional influence on the choice of outsourced design capability will be the long-term relationships that exist with suppliers who are considered development partners. “The automotive industry is a surprisingly close-knit community. If a supplier were to leak information of a truly strategic nature from one assembler to another, it would soon be known and the suppliers credibility would be destroyed. Leakage in the other direction – from one supplier to another via an assembler – is more difficult to detect accurately but appears to be more commonplace. (Lamming, 19993)6. Human resource management

The interplay between knowledge management and HRM is yet to be fully explored. Storey and Quintas (2001) focuses on knowledge sharing as a means to manage knowledge effectively. See Swart and Kinnie (2003) who explored through case study research HR practices of recruitment and selection, resource development and participation on knowledge integration within distributed knowledge systems. They emphasised the sharing of knowledge and highlighted “the provision of social supports for interconnecting various stakeholders in the knowledge sharing process (p. 70)”.

Social support mechanisms such as story-telling (Kleiner and Roth, 1997) communities of practice (Wenger, 2000) are increasingly important given developments in the labour market. For example, the problem of aging in Europe could mean 20% of the European population will be over 65 years old by 2025 (Farrell, 2005). Therefore, this means that knowledge of workers need to be harnessed effectively so that the impacts of knowledge loss amidst a rapidly retiring working population and a constricting labour market can be mitigated.

More crucially in the short-term, a recent study revealed that 90% of the UK workforce have permanent contracts; yet, these workers stay in the same organisation for merely an average of seven years and four months (Taylor, 2002). With such trends, the harnessing of knowledge from the workforce becomes an even more pressing priority.

90% of the workforce have permanent contracts (shifts towards flexible workforce)On average, these workers stay in the same organisation for seven years and four months (contrast with Japan) (Taylor, 2002)

Dominance of the cognitive perspective of knowledge sharingLack of unifying body of knowledge addressing group and organisational level of analysisAmbiguous notion of knowledge (analogies and metaphors)

“Honest probing is needed now, rather than glib answers (Taylor, 2002) Expand - Paul

7. Introducing the concept of Knowledge Leakage (KL)

References to Knowledge Leakage

In biotech clusters (Wolter, 2003) Expand Andrew

The Identification and assessment of knowledge leakage risks in 3D environments – “Knowledge leakage refers to the possibility of information or knowledge that is critical to the organization being lost or leaked – whether deliberately or unintentionally – to a competitor or unauthorised personnel. Risk refers to the probability of this occurring “ (http://isrg.shef.ac.fenio/) (Annansingh, 2005)From a PhD in which she asks

1) do the organisation have explicit policy for the storage of Knowledge2) what is the probability for Knowledge loss/leakage occurring?3) how high would the impact of intra-organisational KL occurring? (makes no

sense! - souad)

The importance of the word critical?

International joint ventures (Tidd and Izumimoto, 2002) Licensing consortia (negative impact)Strategic alliances (negative impact) expand - Andrew

Terms used for KL:Knowledge seepage (rare use)Knowledge leakage (some use)Knowledge transfer (common use) (is this the same – or more flows of knowledge?)Knowledge loss (some use)Knowledge disclosure (only once)

Knowledge leakage: is transmitted in the form of information spillovers. Usually, information is a source of positive leakage, because know-how about a specific project is transferred to agents other than the project partners. In case of success, pioneer projects show the feasibility of a certain project type in a country or world region, which is also a piece of information that is associated with positive leakage (Vohinger, Kuosmanen, Dellink, 2004).

Knowledge, or sole ownership of knowledge, leaks away from the origin

discuss in relation to literature above

stuff below: split into mechanisms and implications? – split into intentional, unintentional?

Knowledge seepage “can occur when jobs are transferred from one set of employees to another. The circumstances of offshoring are often not beneficial to a full transfer of knowledge and know-how, particularly when the workers asked to transfer their knowledge face redundancy” (DiRomualdo, 2004)Knowledge seepage occurs when all human expertise in an area is gradually lost as the experts and users become dependent upon the system (Kingston, 2004)

OutsourcingLoss of Employees Organisational change

losses of organisational knowledge are the effects of re-organising around corporate managerialism without attention to differential evaluations of worth (Treleaven and Sykes, 2005) expand - souad

Exposing contingent workers to private, key competitive knowledge (MacDougall and Hurst, 2005)Inter-firm learning can lead to unintended and undesirable skills transfer (Mohr and Sengupta, 2004).

Staff retirement and other experience loss mechanisms

Benefits to knowledge transfer activities (outsourcing etc)

Movement to supply chain production is often cheaper and more efficient if organised effectively – increasing productivity. (10-40% reduction in costs and increased productivity (Brynjolfsson and Hitt, 2000) Gaining from knowledge leakage plus points – predictable order flows, reduction of stock, inventory, efficient product replenishment etc (hospital case study - Rhodes)Increased productivity from divestmentPossible closing of the productivity gap attributed to the promotion of two-way knowledge transfer between enterprise, science based and research institutions and supply chain partnersReduced productivity growth in the EU has been attributed to the slow exchange of knowledge in response to new technology.(Brynjolfsson and Hilt, 2000, O’Mahoy and van Ark, 2003)

Leakage of technical knowledge through outsourcing design workSuppliers learn from their experiences and embody these as improvements in their next client’s product;Guest engineers (engineers from supplier firms who permanently reside in the customer company) (Twigg, 19997)

Risks from intentional knowledge leakageIncreases time to market if not carried out effectivelyIncreased dependency on supplier (dev of tacit knowledge by supplier – removal of control factor)Loss of centralised information (loss of control of maintenance of drawings, info etc, for immediate or pre-emptive use – higher risk of productivity disruptions – difficulty in achieving real time knowledge from entities)Piracy of confidential knowledge – secondary supplier eg – in case of loss of primary

supplier without the award of significant volume = little trust or loyalty.Conflicts between source and entityLoss of market share – one party becomes superior in all competencesKnowledge loss as suppliers develop local knowledge that never returns to the source (see table) (Yanow, 2004)Increased risk of unintentional knowledge leakage

Increased immitability (see table – Autio, sapienza and almeida, 1999)Through other information – market geog from shipping notes etcLoss of knowledge value – need to market value to others

(Autio, sapienza and Almeida, 1999, Styhre, 2004, Yanow, 2004, Roper and Cronet, 2003, Ndofor and Levitas, 2004, Decarolis, 2002 – sort out refs!)

Table ? Local knowledge (Yanow, 2004)

Figure? Questions to illicit immitability (Autio, Sapienza and Almeida, 1999)

Loss of speculative work within in house R&D – transferring responsibility for advancing technology – and maintaining or advancing productivity)

EU productivity report showed the EU outperformed the US in industry groups where innovations rose from in house R&DR&D investments linked to increased productivity

Small suppliers are less likely to have the resources to plan for new technologiesSmall suppliers are less likely to ‘look sideways’ at potentially disruptive technologies emerging in other industry sectors(Reed and Walsh, 2002, O’Mahoy and van Ark, 2003)

Risks of unintentional knowledge leakageLoss of disembodied or tacit knowledge of production procedure through employee loss leading to disruptions in productivityLoss of value of ‘weightless goods’ – combine with before mentioned bitDecreased productivity from loss of knowledge within industries regarding inefficiency of manufacturing processes – KL due to partial interpretations, forgetting, verbal info etc – as projects proceed, leaks get compounded – Chinese whispers)(refs?)

8. Strategy

should this be in this document?

Objectives

To explore if companies appreciate the significance of KL To categories KL as a function of firm and inter firm activities

To develop an outline methodology for companies to assess their KL holistically, to understand the risks and benefits associated with the leaks

To explore if companies appreciate the significance of KL To provide an assessment as to the potential effect of KL on

productivity

Deliverables

A taxonomy of KL A web-based awareness, audit, and risk management tool for use

within companies, thus enabling benchmarking both during anf after this project.

An assessment as to the potential effect of knowledge leakage on productivity for policy makers and the overarching Sandpit research programme.

Companies’ need to: Develop a perspective on their knowledge profile and knowledge flow Map and manage internal knowledge resources Understand and optimise KL

Maximising for efficient collaboration but understanding the associated risks

Minimising where risk is too high or knowledge is unnecessary

Maximise inadvertent leak detection

Set boundries

Nothin decided yet – scooping study first

We need to locate this project in a theoretical contextOne way into this is by undertaking a literature(s) search(es) and identifying the hole(s). I would caution against this; there are so many (overlapping) literatures out there that this is an unmanageable task and will surely run foul of many specialisms.

Instead I suggest we be bold. On the basis of our experience, we identify a theory-related issue with practical implications for the firm, and we then show how this relates to various sets of literatures.

We should say, as did our external evaluator, that this is a bold and pioneering step, and therefore that we have to precede cautiously. The primary objective at his stage is to develop an overview, a taxonomy, and then to assess the extent to which different sets of firms (varying by sector and size) relate to the challenge we have identified. A second stage of the search would be to generate a larger variety of measurable indicators which can be utilised as stretch-points in programmes of continuous improvement.

Raphie - Based on these observations, we can think of an overview for “Knowledge Control”. Using the water/plumbing metaphor , the firm needs to :

Plumb the depths – make optimism use of knowledge stocks

Maximise inflows of appropriate knowledge and filter out the inflows of “kn owledge-noise”, ie inappropriate knowledge

Minimise outflows of inappropriate knowledge, and maximise outflows of appropriate knowledge

These needs to take account of both embodied and disembodied knowledge, and of tacit and codified knowledge.

Based on this, a taxonomical architecture might look something like this:

Tacit knowledge

Codified knowledge

Embodied knowledge

DisembodiedKnowledge

Knowledge stocks

Knowledge inflows:

Maximising appropriate inflows

Minimising inappropriate inflows

Knowledge outflows

Minimising outflows of knowledge targeted as dynamic capabilities

Maximising outflows of core rigidities

Our task in this stage of the research is to develop methods for determining the extent to which firms:

Are aware of each of these cells

Have procedures for dealing with each of these cells

And seeing how this varies by sector and firm-size (within the SME category?)

Our benchmark tool at this stage is merely a way of their assessing their comparative capabilities in relation to this overview and awareness

The next stage of our research – having tested this architecture in Phase 1 – is to develop methods for assessing comparative performance on each of these counts. This is much more difficult (and of course requires much more funding…)

Grounded Theory ?

BackgroundPrompting questions

8.1 Capability maturity – possible strategy for assessing KL / K intensity etc / our project etc etc

Origins

Process maturity models – 1986Quality issues for the US government in software procurementIt funded research (by the Software Engineering Institute, SEI, at Carnegie Mellon University with the assistance of the Mitre Corporation) to develop a framework designed to improve the software development process.SEI Capability Maturity Model (CMM) finally released in 1991The SEI itself has participated in developing models for systems engineering, software acquisition, and HRM (Ferguson, 1999)

All capability maturity models are based on one primary concept: it is very difficult consistently to deliver quality products to your customers, while also making a profit, if your product development process is poor (Cusick and Bruce, 1999)

Assumption – improving the development process helps product quality, customer satisfaction and profits.

“The underlying assumptions that organisations mature through various stages, towards rational, controllable processes and that this progress can be measured and assessed (Paulk, 1995) are questionable.”

“If applied uncritically, the CMM can be accused of assuming that the software process is managed wholly ‘from above’ through formal processes and procedures, ignoring ‘management from below’ (i.e practitioner discretion in the choice and application of methods and procedures). We have found the latter to be common in complex software and extremely important”. (Brady, Davies et al, 2003).

Put in Andrews CMM assessment results figure (ref?)

Managing riskDefine future products, determine their probability of occurrence and consequence of occurrence, implement mitigations, track the success of the mitigation activities.

Provide skills and knowledgeDetermine future skills and knowledge needs, determine whether to hire or train to get the necessary skills, hire or train as necessary (Cusick and Bruce, 1999)

There is also CMM work done in the construction domain: SPICE project in Salford (Standardised Process Improvement for Construction Enterprises) – see Amaratunga et al. (2002)

Derived from software optimisation techniques – generic approaches to developing an entity to its ultimate state.

Has a number of levels (commonly 4-6)Sequentially ordered from an initial state to a final level, normally perfection

Also refers to ‘knowledge maturity models’ could we have a ‘control of knowledge leakage maturity model’?

Employed in businesses trying to establish an effective knowledge management systemCan also be used to make comparisons between companies and to rank companies and for benchmarking.

1 case studies:

Microsoft ‘ knowledge landscape’8 levels – unaware to leadershipRanked via 77 criteria using a 4 level scale

KPMG ‘knowledge journey’5 level – knowledge chaotic – knowledge centric

Gallagher and Hazletts KMƒlevels – aware to optimisationsplit into separate focus’ of culture, infastructure and technology(klimko, 2001 – all)

Example of a knowledge maturity model (Klimko, 2001)

Relationships between Knowledge and productivity – add into text

Brown and Eisenhardt (1998) examined inter-firm cooperation in a study of 12 major computer firms. They found that more effective firms limited knowledge transfer to the most strategically valuable information, rather than all possible information. NOTE: cf. Harrison and Kessels (2004) – will chase up reference

Andrew to put these where he sees fit

Transferring knowledge for productivity (Lapre and Van Wassenhove, 2001)Mukherjee et al. (1998) analysed in one factory over a decadeProcesses in quality improvement projects exhibit considerable variation along two learning dimensions: conceptual and operational learning.Conceptual learning is the process of aquiring a better understanding of cause-and-effect relationships, i.e., the acquisition of know-why. Operational learning is the process of optaining validation of action-outcome links, i.e., the acquisition of know-how.

Only 24% of the projects, the ones that aquired both know-why and know-how, accelerated the factory’s learning rate.

Projects that produced know-why without the corresponding know-how were ‘disruptive’Projects that failed to aquire know-why did not affect the learning rate.An organizational structure called model line, a production line run as a learning laboratory, consistently produced know-why and know-how that was successfully transferred to the rest of the factory.

What is the next production frontier? The author argues that it is operating factories as learning ‘laboratories’. These are complex organizational ecosystems that intergrate problem solving, internal knowledge, innovation and experimentation, and external information. (Leonard-Barton, 1992)

“For example, in the 1970’s he had participated in an R&D project on the ability of tire cord to withstand corrosion. From this R&D project, he remembered that some copper-related variables determined in the brass coating step were relevant for the problem at hand in the WWD department. The MLA team tested the model with controlled experiments. As a result the MLA obtained a sharp improvement in productivity” (ref?).

“What we didn’t understand when we started model lines in plants B and C is that a model line manager needs to have authority over production and projects, and a young engineer is not a good choice to run a model line. Young engineers lack experience in formal problem solving…” (ref?)

Taylor was the first person to apply knowledge to work

There is equal – or even greater – opportunity in the developed countries to organize non-manufacturing production (i.e., production work in services) on the production principles now being developed in manufacturing.

There is equally a tremendous amount of knowledge work – including work requiring highly advanced and thoroughly theoretical knowledge – that includes manual operationsSix major factors determine knowledge-worker productivity:

1. Knowledge-worker productivity demands that we ask the question: “what is the task?”2. It demands that we impose the responsibility for their productivity on the individual

knowledge workers themselves. Knowledge workers have to manage themselves. They have to have autonomy.

3. Continuing innovation has to be part of the work, that task and the responsibility of knowledge workers.

4. Knowledge work requires continous learning on the part of the knowledge worker, but equally continous teaching on the part of the knowledge worker.

5. Productivity of the knowledge worker is not – at least not primarily – a matter of the quantity of output. Quality is at least important.

6. Finally, knowledge-worker productivity requires that the knowledge worker is both seen and treated as an ‘asset’ rather than a ‘cost’. It requires that knowledge workers want to work for the organisation in preference to all other opportunities (Drucker, 1999)

A more effective productivity strategy is to share knowledge about up-to-date activity including process, change in product and services. (ref souad?)

Linking productivity to efficient information flow along administrative flow (invoices etc) in parallel to process supply chain (Singh, 1996)

Rhodes to move

Assess knowledge leakage in countries with increased productivity in order to assess if knowledge leakage does effect productivity.

Or within companies with similar productivity growth or decline levels (OECD STAN database

Sector competitiveness analysis of the software and computer service industry by the DTI found the productivity gap in India was due to high levels of staff turnover (KL through employee loss) and due the the high levels of piracy)

Difficulty in assessing effect of KL on productivity as intentional KL (outsourcing) is often linked with other activities(Reynolds, Howard, Dragon, Rosewell and Ormerod, 2005, van Ark, Inklaar and Mcgucken, 2003 – sort refs!)

EU Report on productivity suggests sector specific improvements in technologies within industries with wide applications in other industries and promoting knowledge flows along product supply chains in order to increase productivity (O’Mahoy and van Akin, 2003)

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General comments (Paul): Think Rhodes in right about having too many issues in this literature review paper. Nonetheless, I believe this is a good start to put down all the issues and then we can cherry-pick the ones we want to reinforce in our review paper (nothing is to stop us from putting in a couple of review papers in the longer-term). I have expanded the points from my original slides with a full list of references to support those points. As I went through this “synopsis”, I found a distinct lack of theoretical perspectives in our paper. For example, borrowing from Knowledge Management literature, Kakabadse et al. (2003), in a recent review, looked at philosophy, cognitive science, social science, management science, information science, knowledge engineering, artificial intelligence and economics as defining theoretical perspectives. I am not suggesting we follow these: but perhaps we need to think about it (or perhaps these might emerge as we populate this “synopsis”?). Second, and perhaps more crucially, the “synopsis” appears to be a little haphazard when we deal with levels of analysis. Are we talking about individual, group, firm, industry, national levels? The literature seems all over the place and I think our final review paper will be able to contribute by clarifying the levels of analysis (maybe?).

In my contribution, I have, where possible, tried to link the points with our Knowledge Leakage project explicitly. Just a suggestion here: I’ve seen a number of review papers that conclude with a set of hypotheses that the authors will test (in a very loose sense of the terms here) in

their research. I think this can be quite useful for us to (a) set the context (and boundaries) for our review and (b) allow us to gain feedback and a sense of direction in our project (relatively unknown at the moment). Just some thoughts at the moment, no doubt we’ll refine these on 12 January.