KNOWLEDGE Management for Technological Innovation in Orgns - For Creating Intellutural Capital

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ABSTRACT

Title of Dissertation: KNOWLEDGE MANAGEMENT FORTECHNOLOGICAL INNOVATION INORGANIZATIONS: THE FUSIONPROCESS FOR CREATINGINTELLECTUAL CAPITAL

Michael Clifford Heffner, Doctor of Management, 2006

Dissertation Directed By: Dr. Nawaz Sharif, Graduate School of Management and Technology, University of Maryland University College

In a knowledge-centric economy, knowledge, embodied as intellectual capital, is increasingly a

strategic resource for organizations in all areas of human endeavor. This dissertation presents an

integrative conceptual framework for knowledge management that encompasses a fusion process

for creating new knowledge and technological innovations in a competitive environment, using

management services firms as a specific economic context for application. The framework

embodies the premise that the most effective and efficient organizations are those that can learn

to learn to incorporate learning processes, including knowledge creation, into their everyday

operations and management.

The theoretical foundations of the framework include multiple perspectives of knowledge

formation and technological innovation, with a particular focus on conversion of knowledge

from tacit to explicit forms and ultimately to intellectual capital, especially technologically

embodied forms tools, skills, facts and procedures that are the knowledge-in-use within


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organizations. The framework is conceived as an organizational learning cycle or fusion

process, which encompasses sub-processes for knowledge acquisition and formation,

technological embodiment of knowledge, entrepreneurial application of technologies, and

assessment of knowledge-in-use by an organization, in order to create or form intellectual

capital.

The framework has been refined and validated through several means: (1) feedback from

participants in an academic conference; (2) four case studies that encompassed interviews with

practitioner professionals as well as application of the framework as an analytical framework infield studies of the associated firms; and (3) participation as an observer in an ICT solutions

project as an additional case for field study of analytic application of the framework.

Operationalization of the framework as a management tool is demonstrated by applying the

Analytic Hierarchy Process, using comparison matrices prepared by the interviewees.

Key findings include: (1) perceptions of knowledge management definition and use vary among

practitioners, even within a single industry; (2) there may be significant differences in priorities

between knowledge management professionals and practicing consultants; and (3) to be

actionable, knowledge developed in the organizational context must be re-assimilated by

individuals, who remain the main agents of action.

Keywords: technological innovation; intellectual capital; knowledge management; knowledgecreation; organizational learning; knowledge fusion; technoware, humanware, inforware and orgaware


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KNOWLEDGE MANAGEMENT FOR TECHNOLOGICAL INNOVATION INORGANIZATIONS: THE FUSION PROCESS FOR CREATING INTELLECTUAL CAPITAL

By

Michael Clifford Heffner

Dissertation submitted to the Faculty of theGraduate School of Management and Technology of the

University of Maryland University College, in partial fulfillmentof the requirements for the degree of

Doctor of Management2006

Advisory Committee:Dr. Nawaz Sharif, Chair Dr. John Aje, Member Dr. Jim Chen, Member Dr. Marcus K. Rogers, External Member


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UMI Number: 3213465

3213465

2006

Copyright 2006 by

Heffner, Michael Clifford

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Copyright byMichael Clifford Heffner

2006All rights reserved.


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Dedication

To Michele, Jason and Bryan for their constant support and understanding.

To my parents, Ann and Chuck, for instilling in me the value of life-long learning.

And to my brother, Jim, for demonstrating the courage of entrepreneurship.

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Acknowledgements

I thank the dissertation committee, Dr. Nawaz Sharif, Dr. John Aje, Dr. Jim Chen, and

Dr. Marcus Rogers, for their valuable assistance in this project. Dr. Sharif, as committee Chair,

advisor, and counselor has been a continual source of guidance and encouragement throughout

this project, as well as the entire course of my Doctoral studies. I also want to acknowledge the

valuable contributions of the faculty and staff of University of Maryland University College in

imparting the knowledge and providing an environment that enabled me to conceive and

accomplish this work. And I want to thank my fellow doctoral students and professional

associates for sharing this journey, providing support, and inspiring me to do that much more to

complete this project.

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Table of Contents

Dedication........................................................................................................................................ i i Acknowledgements......................................................................................................................... ii i Table of Contents........................................................................................................................... ..iv List of Tables .................................................................................................................................. .vi List of Figures.............................................................................................................................. ....ix Chapter 1. Introduction and Research Question....................................................................... 1

1.1 Challenges of a Knowledge-Centric Economy..................................................................... 11.2 Economic Sector Context ..................................................................................................... 6

1.2.1 Knowledge-Centric Organizations................................................................................. 61.2.2 Management Services Organizations............................................................................. 71.2.3 The Organization as a System........................................................................................ 8

1.3 Knowledge Sources for Management Services Projects ...................................................... 9

1.4 Research Question .............................................................................................................. 12Chapter 2. Literature Review.................................................................................................. 13

2.1 Knowledge .......................................................................................................................... 142.1.1 Personal Knowledge .................................................................................................... 152.1.2 Organizational Knowledge .......................................................................................... 162.1.3 Typology of Knowledge .............................................................................................. 20

2.2 Innovation ........................................................................................................................... 212.2.1 Innovation as Object .................................................................................................... 232.2.2 Innovation as Process................................................................................................... 262.2.3 Environmental Conditions for Innovation ................................................................... 28

2.3 Intellectual Entrepreneurship.............................................................................................. 30

2.4 Performance Measurement ................................................................................................. 312.4.1 Balanced Scorecard...................................................................................................... 322.4.2 Measuring Organizational Competence and Capability .............................................. 35

2.5 Knowledge Management and Intellectual Capital .............................................................. 372.5.1 Computer and Information Science, Knowledge Management (IT Perspective), andArtificial Intelligence ............................................................................................................ 372.5.2 Knowledge Management (Organizational Learning Perspective)............................... 382.5.3 Intellectual Capital ....................................................................................................... 39

2.6 Gaps and Limitations in the Literature ............................................................................... 41Chapter 3. Conceptual Framework and Research Method ..................................................... 42

3.1 Knowledge Fusion .............................................................................................................. 42

3.1.1 Transforming tacit to explicit knowledge .................................................................... 433.2 The Guiding Framework for Knowledge Management...................................................... 483.2.1 Acquiring Knowledge and Wisdom............................................................................. 493.2.2 Fusing Knowledge with Resources.............................................................................. 503.2.3 Executing Projects ....................................................................................................... 513.2.4 Assessing Performance ................................................................................................ 513.2.5 Building an Actionable Knowledge Base .................................................................... 52

3.3 Research Method ................................................................................................................ 52

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3.3.1 Specific Conduct of the Study ..................................................................................... 543.3.2 Methodological Considerations ................................................................................... 553.3.3 Limitations ................................................................................................................... 63

Chapter 4. Discussion, Results and Conclusions.................................................................... 65Overview of the Cases .............................................................................................................. 65

4.1.1 ICT Services Industry Description............................................................................... 654.1.2 The Nature of Work in the ICT Services Industry....................................................... 664.2 Interviews and Field Study Cases ....................................................................................... 68

4.2.1 Case 1: IT Solution Provider........................................................................................ 694.2.2 Case 2: Consulting Practice ......................................................................................... 864.2.3 Case 3: Consulting Practice of a Public University................................................... 1004.2.4 Case 4: Large Systems Integration Contractor .......................................................... 116

4.3 Participant Observer Case Study (Case 5): IT Solution Provider for Commercial ClientServing the Government Sector ................................................................................ 130

4.3.1 Sample Extract from Observations ............................................................................ 1314.3.2 Activities Observed.................................................................................................... 133

4.3.3 Reflection................................................................................................................... 1344.4 Results............................................................................................................................... 1354.4.1 Validation of the Integrative Framework................................................................... 1354.4.2 Applying the Framework in an Operational Context................................................. 1364.4.3 Other Observations .................................................................................................... 139

4.5 Conclusions....................................................................................................................... 142Chapter 5. Recommendations for Future Work.................................................................... 145

5.1 Avenues for Further Research .......................................................................................... 1455.2 Use in Management Practice ............................................................................................ 147

References................................................................................................................................... 149Curriculum Vitae ........................................................................................................................ 158

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List of Tables

Table 1. Scale for pair-wise comparison under the Analytic Hierarchy Process......................... 60Table 2. Pair-wise comparison of Level 1 factors. ...................................................................... 61Table 3. Pair-wise comparison of Level 2 factors for Fusing Knowledge with Resources......... 62Table 4. Subset of the relative dominance table for the factors under Fusing Knowledge with

Resources. ......................................................................................................................... 62Table 5. Case 1 pair-wise comparison of Level 1 factors: raw scores......................................... 77Table 6. Case 1 pair-wise comparison of Level 1 factors: normalized scores............................. 78Table 7. Case 1 relative dominance of Level 1 factors................................................................ 78Table 8. Case 1 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

raw scores.......................................................................................................................... 79Table 9. Case 1 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

normalized scores.............................................................................................................. 79

Table 10 . Case 1 pair-wise comparison of Level 2 factors for Fusing Knowledge withResources: raw scores. ...................................................................................................... 80

Table 11. Case 1 pair-wise comparison of Level 2 factors for Fusing Knowledge withResources: normalized scores. .......................................................................................... 80

Table 12. Case 1 pair-wise comparison of Level 2 factors for Executing Projects: raw scores.. 80Table 13. Case 1 pair-wise comparison of Level 2 factors for Executing Projects: normalized

scores................................................................................................................................. 81Table 14. Case 1 pair-wise comparison of Level 2 factors for Assessing Performance: raw

scores................................................................................................................................. 81Table 15. Case 1 pair-wise comparison of Level 2 factors for Assessing Performance:

normalized scores.............................................................................................................. 82

Table 16. Case 1 pair-wise comparison of Level 2 factors for Building an ActionableKnowledge Base: raw scores. ........................................................................................... 82

Table 17. Case 1 pair-wise comparison of Level 2 factors for Building an ActionableKnowledge Base: normalized scores. ............................................................................... 83

Table 18. Case 1 relative dominance of Level 2 factors.............................................................. 83Table 19. Case 2 pair-wise comparison of Level 1 factors: raw scores....................................... 90Table 20. Case 2 pair-wise comparison of Level 1 factors: normalized scores........................... 91Table 21. Case 2 relative dominance of Level 1 factors.............................................................. 91Table 22. Case 2 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

raw scores.......................................................................................................................... 92Table 23. Case 2 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

normalized scores.............................................................................................................. 92Table 24. Case 2 pair-wise comparison of Level 2 factors for Fusing Knowledge withResources: raw scores. ...................................................................................................... 93

Table 25. Case 2 pair-wise comparison of Level 2 factors for Fusing Knowledge withResources: normalized scores. .......................................................................................... 93

Table 26. Case 2 pair-wise comparison of Level 2 factors for Executing Projects: raw scores.. 93Table 27. Case 2 pair-wise comparison of Level 2 factors for Executing Projects: normalized

scores................................................................................................................................. 94

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Table 28. Case 2 pair-wise comparison of Level 2 factors for Assessing Performance: rawscores................................................................................................................................. 94

Table 29. Case 2 pair-wise comparison of Level 2 factors for Assessing Performance:normalized scores.............................................................................................................. 95

Table 30. Case 2 pair-wise comparison of Level 2 factors for Building an Actionable

Knowledge Base: raw scores. ........................................................................................... 95Table 31. Case 2 pair-wise comparison of Level 2 factors for Building an ActionableKnowledge Base: normalized scores. ............................................................................... 96

Table 32. Case 2 relative dominance of Level 2 factors.............................................................. 97Table 33. Case 3 pair-wise comparison of Level 1 factors: raw scores..................................... 106Table 34. Case 3 pair-wise comparison of Level 1 factors: normalized scores......................... 107Table 35. Case 3 relative dominance of Level 1 factors............................................................ 107Table 36. Case 3 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

raw scores........................................................................................................................ 108Table 37. Case 3 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

normalized scores............................................................................................................ 108

Table 38. Case 3 pair-wise comparison of Level 2 factors for Fusing Knowledge withResources: raw scores. .................................................................................................... 109Table 39. Case 3 pair-wise comparison of Level 2 factors for Fusing Knowledge with

Resources: normalized scores. ........................................................................................ 109Table 40. Case 3 pair-wise comparison of Level 2 factors for Executing Projects: raw scores.109Table 41. Case 3 pair-wise comparison of Level 2 factors for Executing Projects: normalized

scores............................................................................................................................... 110Table 42. Case 3 pair-wise comparison of Level 2 factors for Assessing Performance: raw

scores............................................................................................................................... 110Table 43. Case 3 pair-wise comparison of Level 2 factors for Assessing Performance:

normalized scores............................................................................................................ 111Table 44. Case 3 pair-wise comparison of Level 2 factors for Building an Actionable

Knowledge Base: raw scores. ......................................................................................... 111Table 45. Case 3 pair-wise comparison of Level 2 factors for Building an Actionable

Knowledge Base: normalized scores. ............................................................................. 112Table 46. Case 3 relative dominance of Level 2 factors............................................................ 113Table 47. Case 4 pair-wise comparison of Level 1 factors: raw scores..................................... 121Table 48. Case 4 pair-wise comparison of Level 1 factors: normalized scores......................... 122Table 49. Case 4 relative dominance of Level 1 factors............................................................ 122Table 50. Case 4 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

raw scores........................................................................................................................ 123Table 51. Case 4 pair-wise comparison of Level 2 factors for Acquiring Knowledge & Wisdom:

normalized scores............................................................................................................ 123Table 52. Case 4 pair-wise comparison of Level 2 factors for Fusing Knowledge with

Resources: raw scores. .................................................................................................... 124Table 53. Case 4 pair-wise comparison of Level 2 factors for Fusing Knowledge with

Resources: normalized scores. ........................................................................................ 124Table 54. Case 4 pair-wise comparison of Level 2 factors for Executing Projects: raw scores.124Table 55. Case 4 pair-wise comparison of Level 2 factors for Executing Projects: normalized

scores............................................................................................................................... 125

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Table 56. Case 4 pair-wise comparison of Level 2 factors for Assessing Performance: rawscores............................................................................................................................... 125

Table 57. Case 4 pair-wise comparison of Level 2 factors for Assessing Performance:normalized scores............................................................................................................ 126

Table 58. Case 4 pair-wise comparison of Level 2 factors for Building an Actionable

Knowledge Base: raw scores. ......................................................................................... 126Table 59. Case 4 pair-wise comparison of Level 2 factors for Building an ActionableKnowledge Base: normalized scores. ............................................................................. 127

Table 60. Case 4 relative dominance of Level 2 factors............................................................ 128Table 61. Group activities attended by the participant observer. .............................................. 134

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List of Figures

Figure 1. Knowledge context for management services projects ................................................ 11Figure 2. Knowledge Transformation from Tacit to Explicit Form [Source: Sharif, 2005a]...... 44Figure 3. Transforming Knowledge and Natureware to Intellectual Resources for Wealth

Creation [Source: Sharif, 2005] ........................................................................................ 47Figure 4. Knowledge fusion process for creating intellectual capital.......................................... 49Figure 5. The framework restructured as an analytic hierarchy. ................................................. 59Figure 6. Comparison of plan vs. actual investment profile for Fusing Knowledge with

Resources. ......................................................................................................................... 62Figure 7. Comparison of AHP Scores for Level 1 Factors. ....................................................... 137Figure 8. Comparison of AHP Scores for Level 2 Factors. ....................................................... 138

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Chapter 1. Introduction and Research Question

A knowledge-centric economy presents many challenges to organizations, whether they

are for-profit or not. This dissertation discusses many aspects of knowledge creation and use

within organizations in order to develop an integrative conceptual framework that may be used

by managers to assess and improve the management of intellectual capital. This introductory

chapter outlines the challenges of a knowledge-centric economy, describes an economic sector

context for the study as well as the knowledge environment within which management services

are provided, and describes the research question addressed in this dissertation.

1.1 Challenges of a Knowledge-Centric Economy

A shift towards a knowledge-centric economy, from a primarily industrial-age economy

based on traditional mass production and generalized services, was observed four decades ago

(Machlup, 1962 & 1979; Drucker, 1969; Bell, 1973). Especially the rapid growth in capabilities

of information and communications technology (ICT) 1 has accelerated this transformation, and

recently has supported the emergence of a new digital economy, a marketspace 2 that exists

primarily, in some cases entirely, in the virtual world of electronic media. With the advent of the

digital economy, within which businesses are highly dependent on technologies and explicit

encoding of knowledge because there may be little or no face-to-face personal interaction,

effective use of intellectual resources becomes ever more important to sustain competitive

advantage. But the centrality of knowledge is not limited to the digital marketspace; knowledge,

1 The term information and communications technology (ICT) is an expansion of the earlier term informationtechnology (IT) this expansion emphasizes the importance of the integration of information with communicationstechnologies in the highly networked information infrastructure which has evolved over the past half century.2 Marketspace is a term that has emerged in recent years to evoke the changed nature of the marketplace. It isintended to differentiate virtual marketplaces, which include electronic marketplaces such as those available throughthe Internet, from the traditional physical marketplaces. It conveys the sense of a public, open space for conductingcommerce; yet recognizes that this space does not necessarily exist at one geographic location, or may be entirely avirtual marketplace with no physical location for conducting commerce at all. (cf. Rayport & Sviokla, 1994)

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embodied as intellectual capital, is increasingly a strategic resource for organizations in all areas

of human endeavor, including the work of governmental and not-for-profit organizations.

Development and execution of business strategies in a knowledge-centric economy can

present significant resource challenges, particularly intellectual capital challenges, to an

organization. Because of the limited resources within individual organizations, particularly

small entrepreneurial organizations typical of new or niche businesses, it is often necessary to

augment organizational resources with external resources in order to develop and execute

business strategies a number of businesses have arisen to provide this assistance, ranging from

individual consultants and staff augmentation firms to providers of full solutions to business problems. While individual consultants and augmented staff typically integrate directly into

projects within the organization, management services firms may take a more prominent role in

shaping the conduct and outcomes of a project, even, in some cases, taking the lead role, at least

from a technical perspective, because of their expertise.

However, in taking on this larger role, external management services and other providers

often are presented with significant challenges in developing effective solutions in partnership

with their clients. Many of these projects do not fully succeed ranging from projects with

significant cost and schedule overruns or reduced functionality, to projects that are never

completed, are not accepted by the client organization, or are rejected or ignored by the ultimate

customers. As one example, Sears recently sued to end a major technology services contract,

citing failure to perform (Frauenheim, 2005). High profile examples can be found in the public

sector as well. As examples, the Federal Bureau of Investigations Virtual Case File project was

canceled after the delivered system did not meet agency needs (Associated Press, 2005;

Goldstein, 2005), and the Marine Corps terminated the Global Combat Support System contract

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(Tiboni, 2006) for failure of the services provider to complete key documentation in the

requirements and design stages of the systems development life cycle.

Managers of both provider and client organizations are continually seeking ways to

achieve better outcomes from these solution projects. In addition to these immediate project

concerns, management services firms must remain competitive in order to garner new business.

Building capabilities and competencies, attracting and retaining knowledge workers, and

developing innovative approaches for projects are continual challenges. Means must be found to

enable effective sharing of knowledge, including organizational vision, goals, concepts and

image, as well as specific subject matter knowledge. And a particular concern is how to benefitfrom the learning accomplished by each individual project team, especially as a project draws to

a close it continues to prove difficult to replicate the successes of one project in another, even

if the project team (at least on the provider side) remains intact. The crux of the challenge may

be the management of knowledge both the knowledge within individual projects, and the

knowledge maintained and used by the organizations involved in the project.

As a result, knowledge management has emerged as one of the central foci of both

practice and research with regard to organizational dynamics and performance. The shift from

the old, industrial economy to a new knowledge-centric economy requires companies to

maximize their use of knowledge, often embodied as technologies. Nevens, Summe & Uttal

(1990) and others (Wheelwright & Sasser, 1989) have found that even industrial companies

compete more effectively when their products and processes are well managed, even maximized

with respect to technological content. As a result, intellectual capital has become a strategic

focus for the most successful businesses and is widely discussed in both academic and

practitioner literature.

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A large body of work exists with respect to knowledge management as it relates to

managing explicit, i.e. codified, knowledge, especially in the context of ICT systems to support

knowledge management, including so-called artificial intelligence. Another major research

stream has been the valuation of knowledge, particularly under the moniker of intellectual

capital, as well as development of various indices to aid in intellectual capital-related decisions,

especially with respect to national and regional development policies (Godin, 2003). A third

stream is focused on human behavior these researchers, building on basic theories of needs and

motivation, are focused on such subject areas as leadership, creativity, and entrepreneurship. Yet

another stream of research is focused on business functions, where knowledge is treated in anoperational context. All of the different characteristics of knowledge perceived from each of

these viewpoints become fused within knowledge-in-use, which is embodied within various,

often technological forms. The concern then in this paper is with the creation and use of

knowledge within organizations, with what is being called the fusion process of knowledge

management for technological innovation. This fusion process can be viewed as including three

major integrative sub-processes, the first of which generates concepts to be applied, the second

of which generates technologies both usually with an intent for use within specific application

contexts and the third of which actually applies knowledge and technologies in decision

making and problem solving.

Popper (1963) has observed that there has been a long-running debate between two views

of knowledge and epistemology: (1) controlled observation empiricism, which attempts to

develop knowledge from observation of nature and was the foundation of much of scientific

work during the late eighteenth through the mid-twentieth century, and (2) intellectual intuition

rationalism, which posits reasoned theory that is viable until proven wrong. In actual practice,

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especially in pragmatic knowledge use in organizations, knowledge is generated by an

integration of both perspectives. The fusion process being described, then, employs a pragmatic

view of knowledge knowledge must be actionable and useful within a given context. The

mechanism for the creation of new knowledge is a dialectical process that integrates diverse,

sometimes conflicting, tacit and explicit knowledge into new forms the key to knowledge

creation lies in mobilization and partial conversion of tacit knowledge through a process of

knowledge fusion: (1) integration of discipline-based knowledge, (2) integration of knowledge at

the intersection of related disciplines, (3) integration of socially acceptable beliefs, and (4)

integration of tacit and explicit knowledge through conceptual charts and other modelingmechanisms (Sharif, 2005b). But, actionable knowledge that results from this first fusion

process is still only a potential resource.

In order to bring knowledge to the marketspace, in the next stage knowledge must be

integrated with other resources available to the organization, generating technological

innovations, both internally (organization) and externally (market) oriented. Sharif (1988) has

partitioned technological embodiments into tools, skills, facts, and procedures, and has coined

the terms technoware, humanware, inforware, and orgaware, respectively. Such a partitioning of

technology facilitates managing the fusion process, as well as ongoing assessment of

organizational knowledge creation successful innovation can be measured by observing growth

and change in each technological type, as well as shifts in emphasis among them over time (e.g.,

relative levels of investment or use).

The focus in this paper is on how knowledge management involves a fusion process that

joins individual and group knowledge from many sources, and integrates this knowledge with

other resources to generate technological innovations, in ongoing cycles of organizational

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learning, technological development, action, and assessment with the goals of sustainability,

competitiveness, efficiency and effectiveness including, for commercial enterprises,

profitability.

1.2 Economic Sector Context

Before discussing in detail the knowledge fusion process, it is useful to establish a

specific economic sector context, knowledge-centric management service providers, which can

serve as a frame of reference for discussion and a source for examples.

1.2.1 Knowledge-Centric Organizations

Knowledge-centric organizations are a special subset of knowledge-intensive firms, a

term prevalent in the literature for firms whose focus of activity is on knowledge exploitation.

Starbuck (1992) defines a knowledge-intensive firm as one whose primary input resource is

knowledge, relative to other key inputs such as capital and labor. All firms are dependent on

knowledge (Prusak, 1998), but use of knowledge by firms can be considered as falling within a

spectrum from relatively low knowledge content (for example a firm involved in extraction processes such as timber harvesting) to highly-intense knowledge content (for example a think

tank) differentiation is manifest in how knowledge is used by the firm. But even the timber

company begins to move further along the knowledge continuum as soon as it progresses from

simple logging of existing forests to more sustainable strategies such as tree farming. Another

dimension of interest, closely related, is the knowledge content of the output of the firm, viewed

from the perspective of the customers ability to expand their stock of knowledge. It is from this

perspective of knowledge that the knowledge-centric firm is defined.

A knowledge centric firm is, then, a knowledge-intensive firm whose primary output to

the market has a high knowledge transfer component. In many cases, the primary economic

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purpose of a knowledge-centric organization is to provide knowledge, often in the form of

subject matter expertise; some of the value propositions being the offering of experts, quality of

research, specific competencies, and innovative means of delivery. The most obvious examples

of such firms, considering commercial enterprises, are a subset of professional business service,

also known as management service, firms (McKaig-Berliner, 2001) a subset because, while all

of these firms have knowledge-based outputs, some of them are merely conduits for individual

expertise, sometimes even at as primitive a level as staff augmentation for the customer.

Knowledge-centric firms, on the other hand, are posited to hold knowledge competencies at the

organizational level. Such firms may offer, in addition to expert consulting, other knowledgeoutputs such as knowledge bases and associated services or publications.

Sveiby (1997, pp ix-x) observes that managing knowledge-centric companies differs

significantly from managing traditional manufacturing firms. He notes that this is reflected, for

example, in the inadequacy of traditional accounting to reflect accurately the value of a business.

Managers of knowledge-centric firms must be concerned with managing invisible knowledge-

based assets: experts, concepts, image, and networks.

1.2.2 Management Services Organizations

Management service organizations provide expert services to enterprises in order for

those enterprises to pursue management strategies and objectives that would otherwise be

unachievable without using external resources, or at a minimum, without the validation from

independent review. At the core of such business relationships is a sharing of knowledge,

sometimes as expertise of individual practitioners, but also as complementary competencies. It

is in this latter sense that these firms are of particularly interest; and, when looking for examples

during this research, selections primarily have been drawn from a specific subset of management

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services organizations: ICT solution providers. ICT solution providers aid client firms in

applying information and communications technologies to solve business problems and exploit

opportunities in the market. Support may range from providing consultative advice to providing

full ICT solutions such as outsourcing of computing and communications infrastructure and

software applications.

1.2.3 The Organization as a System

Senge (1990, pp. 3-7) suggests that understanding an organization as a system is an

essential prerequisite to transforming the organization into a true learning organization;

otherwise, in concentrating on isolated phenomena, the full picture cannot be seen knowledge

may remain incomplete or narrowly focused. And, if an attempt is being made at problem

solving, the solutions may become the problem through unintended consequences, often the

result of not understanding the intricacies and interplay of the full system. These observations

are echoed by Gharajedaghi (1999, p. 123): We are less likely to be able to explain the behavior

of a complex whole by studying the behavior of the parts; contrarily, we are more likely toexplain the behavior of the parts by studying the behavior of the whole. Gharajedaghi places

particular importance on understanding the interactions or relationships among the elements of a

system, suggesting that management of a system is more and more about managing its

transactional environment (p. 51). He also emphasizes the importance of understanding the

system in context: the behavior of living (open) systems can be understood only in the context

of their environment, (p30) and a structure cannot completely explain its outcome and why

we need the additional concept of an environment as a coproducer. Structure, function, and

process, along with the environment, form an independent set of variables. Together they define

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the whole, or make possible the understanding of the whole (p112) Neither problems nor

solutions can be entertained free of context. (p116)

The idea of an organization as a living system is reflected in the work of Nonaka &

Toyama (2002), who treat the firm as a dialectical being that creates knowledge through a

process of resolving contradictions (p995). In the fusion model, this dialectical process is

expanded to encompass the fusion of varying perspectives of knowledge and technology as well

as diverse subject areas of knowledge.

1.3 Knowledge Sources for Management Services Projects

In order to better understand knowledge management, it is useful to consider the specificknowledge context for management services during the ensuing discussion. As outlined in

Figure 1, the knowledge sources for providing knowledge-centric services transcend any

individual organization, drawing from sources both internal and external to the organizations

participating in the project. Particularly for small knowledge-intensive organizations, the breadth

and depth of knowledge areas required to support a typical customer engagement force many

organizations to look outside to supplement their own capabilities and competencies. As with

other organizational resources, growth of an organization may lead to increasing internalization

and integration of knowledge resources along both horizontal and vertical dimensions. Also, the

customer is a critical source of knowledge, and may even (probably ideally does) contribute

resources to the project team. It may be that under the ideal scenario, the provision of

knowledge-centric services involves mutual learning processes between the provider and the

client. The following summarizes the knowledge sources for the project:

(1) Project knowledge areas: the participants in the project team are the immediate source of

knowledge used in the solution. While the team may comprise mostly people from the

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provider organization, usually there are representatives of the client organization who

carry knowledge specific to the client. There also may be independent specialists on the

team to provide knowledge in various technical, managerial or market subjects.

(2) Provider: The provider organization is the primary conduit for knowledge specific to the

management services being provided. They often take the lead or share in the project

management.

(3) Client: The client organization is the primary conduit for knowledge of context-specific

strategies and management and business requirements, including those coming into the

project from the customers of the client, the clients industry cluster, and the economyand society at large.

(4) Communities of interest: Many people involved in the project will be able to draw on

knowledge from networked sources such as peers and professional organizations.

(5) Customers of the client: The needs and desires of end customers are ultimately a critical

element in the project. These needs and desires may be conveyed to the project team by

the client organization, there may be direct representation of customers on the project

team, or there may be specific project activities to collect customer-related knowledge.

(6) Industry cluster(s) 3 of the provider: The provider organization will sit within one or

more industries from which knowledge will be drawn, such as standards, best practices,

and other norms as well as knowledge of evolving technologies, trends and other

information useful in developing innovations.

(7) Industry cluster(s) of the client: Similarly, the client organization will be drawing

knowledge from the industry cluster(s) within which it sits.

3 This concept comes from Porter (2000). See the discussion in 2.2.3 Environmental Conditions for Innovation.

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(8) Economy and society: The overall economic, social and ethical context for the solution,

including opportunities and limitations, is defined by the economy and society at large.

Cultural norms will have a strong impact on project team behavior. The project team

may need to integrate disparate cultures, especially in a multinational context. And, in

the digital economy, especially business over the public internet, any organization may

have a global presence.

Figure 1. Knowledge context for management services projects

These diverse sources of knowledge, required to bring the project to a successful

conclusion, create a complex environment for executive and project managers. As an example,

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consider a project where a provider is integrating a commercial off-the-shelf (COTS) software

product with other applications already implemented at the client firm; the provider is exploiting

specific technologies developed as a result of their prior experience with this particular COTS

product. Members of the project team may also be writing extension software to provide

features that are not present in the baseline COTS product. The project itself includes a number

of analysts, programmers and system integrators, some of whom are independent consultants

brought into the project for their subject matter expertise in specific technological or business

areas. Representatives from the client firm are also key participants in the project, providing

knowledge of the specific firm context. Given this scenario, it is easy to see the complexity of the knowledge management problem with which managers are confronted on a daily basis

knowledge must be managed at the individual, project group and organizational levels.

1.4 Research Question

As discussed earlier in this introduction, there are many research streams addressing

knowledge creation and use in organizations, flowing from various perspectives in disciplinary

and philosophical terms. The challenge is to make sense of these varied observations and

theories so that they can be applied effectively in managing organizations. So, the specific

objectives of this research project have been: (1) to develop an integrative framework that

merges many of the most important concepts related to organizational knowledge creation and

use, and (2) to provide a means for managers to apply this framework in an operational context

in order to improve efficiency and effectiveness in achieving desired organizational outcomes.

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Chapter 2. Literature Review

Innovation will be the single most important factor in determining Americas success

through the 21 st century The Council on Competitiveness (2005, p.7)

The capacity of a society to produce, select, adapt, and commercialize knowledge is

critical for trade, competitiveness, and for the sustained growth of the economy.

World Bank working paper on Innovation Systems (Goel et al , 2004, p.1)

The role of intellectual assets in enterprise performance is of increasing interest to policy

makers. Intangible factors such as research and development, trade secrets, brands and

organizational capital are becoming the key to competitiveness. OECD Annual Report

2005 (p.34)

Every company ranks the capacity to innovate the transformation of knowledge and

ideas into new products, processes, and services as a top priority. Going Global (van

Opstal, 1998, p.7)

Innovation is absolutely essential to safeguard and deliver high-quality jobs, successful

businesses, better products and services for our consumers, and new, more

environmentally friendly processes The challenge is to create the conditions where

all our firms put innovation at the centre of their strategies for the future. British Prime

Minister Tony Blair (2003, p.3)

Innovation continues to be at the forefront of discussion for nations, organizations and

individuals its importance in the current dialogue on competitiveness and quality of life cannot

be overstated. Industry and government are searching urgently for ways to foster innovation and

entrepreneurship for economic advantage, seen as a core of sustainable development. As

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examples, the OECD has created the Centre for Entrepreneurship, Small and Medium

Enterprises and Local Development to foster an entrepreneurial society, which seizes the

opportunities provided by globalisation and innovates to promote sustainable growth, integrated

development and social cohesion. (OECD, 2005, p.32), and, in the United States, a consortium

of industry and academia, the Council for Competitiveness, has fostered the National Innovation

Initiative to optimize our entire society for innovation. And these initiatives are not limited to

the highly developed countries fostering the conditions for innovation in emerging economies

is a key focus of organizations involved in developing countries, such as the World Bank. As

Sharif has observed (2005a), the real difference between a developed and a developing societyis indeed the technological innovation capacity to better satisfy and restructure the human needs

set. Most of these innovation initiatives, regardless of the particular source or context,

recognize some variant of a definition of innovation that combines knowledge and ideas with

entrepreneurship to generate new products, services, processes, capabilities or competencies in

competitive markets and social contexts. This chapter discusses five research areas that underlie

an understanding of the fusion process of knowledge management for technological innovation:

(1) knowledge (including its acquisition and formation); (2) innovation; (3) intellectual

entrepreneurship; (4) performance measurement, and (5) knowledge management and

intellectual capital. Some of the gaps and limitations in the literature are then highlighted.

2.1 Knowledge

If the foundation of technological innovation rests on knowledge, what then is

knowledge? From the perspective of an organization, knowledge exists in several forms. First,

all knowledge is based on personal knowledge (Polanyi and Prosch, 1974) but, personal

knowledge is formed in a human social context. Tsoukas (2005, p.3) observes that from a

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knowledge-based perspective, the locus of individual understanding is not so much in the head as

in situated practice . Organizational knowledge is a form of group or social knowledge which is

shaped by the particular lens of organizational purpose and action. Often, organizational

knowledge has become embodied in technologies in order to facilitate its sharing and use. This

section will discuss personal and organizational knowledge; this discussion will be expanded to

encompass the embodiment forms in the subsequent discussion of the fusion process.

2.1.1 Personal Knowledge

Much of the current body of research on knowledge in organizations, as represented by

intellectual capital, is grounded in the theory of tacit knowledge developed by Polanyi beginning

in the late 1940s through the 1950s. Addressing learning at the individual level, Polanyi (1957)

suggests that problem solving leads to knowledge; even identifying the problem may lead to

learning he provides the example of unsolved mathematical puzzles, the search for a solution

for which has led to other discoveries. There is a need to solve problems that is based on a

purposive tension found in all intelligent animals (p102), which at a minimum, if the problemcan be successfully mastered, leads to heuristics that are later applied consciously or less so (i.e.,

tacitly).

This pragmatic view of knowledge extends throughout Polanyis work. Deep

understanding is gained through alteration of analysis and integration (1961, p460). But this

usually cannot be a purely intellectual exercise better understanding is developed in conducting

this process in a context of real world experience. He provides the example of the pianist a

person cannot learn the proper touch on the key board by learning each of the constituent

motions, but rather must apply the full series of motions in context. Part of the problem lies in

the inability to capture all of the necessary information in language. This is not unlike a common

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conversion of tacit to explicit knowledge and then back again, at both individual and group

levels.

Some have argued whether organizational knowledge even exists (see the discussion in

Ambrosini, 2003). At a minimum, it has been posited by a number of researchers and

practitioners that a shared vision, a sense of common purpose and aspiration, and shared goals

and objectives are essential for organizations to perform at the highest levels. It would seem that

such shared knowledge is not simply multiple instances of individual duplication of the same

facts, but, rather, an evolving conversation in a social context that reinforces and unifies

(Barrett, 2004; Kiehl, 2004), even becoming in organizations with some longevity, part of aunique organizational culture. Nonaka & Toyama (2002, p1001-1002) use the concept of Ba, a

shared context in motion, shared, that is, among the individuals participating in a knowledge-

creating organization. 4 Friga (2003) has done recent work on the importance of fit between

knowledge strategies and the specific work context. It is argued in this paper that organizational

knowledge does exist, and is concretely evidenced by the presence of technologies created and

exploited by the organization.

Von Krogh and Grand (2000) discuss the importance of justification of knowledge in the

organizational setting. Justification involves processes of comparison to the dominant logic of

the organization and the resulting acceptance, rejection or modification of the new knowledge.

Dominant logic regulates what can be accepted into the body of organizational knowledge. 5

4 The concept of Ba is very similar to a concept of mental spaces for individuals that has developed in the course of a series of conversations I have had over the past fifteen years with Walter Ellis and Timothy Brooks, two of my

peers. The notion of mental space is useful in describing the cost of context shifting when a knowledge-worker or manager must alternate between different types of work or different projects. A similar concept also appears ingeneral use in varying applications using terms such as frame of mind.5 Closely related may be such bodies of knowledge as industrial standards, or the knowledge developed in anacademic or religious community.

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Much of the current body of research on organizational knowledge and learning

continues to be grounded in Polanyis concepts of personal knowledge, which were discussed

above. Of particular importance is the differentiation between tacit and explicit knowledge.

Tacit knowledge is held, mostly unconsciously, by individuals, or in relationships among

individuals in a social network. Such knowledge is developed in experiential contexts and is

reinforced by interaction and integration between mind and body such knowledge is difficult to

transmit and is best conveyed through personal relationships such as those between master and

apprentice. Explicit knowledge, that which can be expressed in words and other concrete forms,

is more readily transferable among people, but is limited in that it is, in many respects, a form of information that is subject to reinterpretation by the receiver, and lacks the mind-body bond that

is essential to tacit understanding (Sveiby, 1997). Yet, organizational knowledge must rest on

these forms; otherwise, the capacity for action, which involves individual agency, cannot exist.

Scharmer (2000) suggests that not-yet embodied knowledge, e.g., imagination and

understanding of the sources of new knowledge, is critical to sustaining competitive advantage.

It is the ability to foresee where the market is headed, or even to envision a new configuration for

the market that can be influenced by the organizations actions, that may differentiate the

successful from the unsuccessful innovations. Certainly, this ability to conceive of that which is

yet to be, and to devise a path to realize the conception, becomes an essential characteristic of

entrepreneurship.

In order to describe the interactions between tacit and explicit knowledge in knowledge

creation, Nonaka (1994) developed a spiral model of organizational knowledge creation. In this

model, explicit processes of combination and externalization of knowledge interact with

processes of socialization and internalization related to tacit forms of knowledge. Knowledge

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evolves in a conversation among individual, group, organizational, and inter-organizational

entities. Knowledge becomes explicit to be shared, and then is internalized to be processed, then

externalized in a more mature or enriched form, and the cycle continues. At the firm level, if

these various levels of knowledge processing are operating effectively, there is a growing body

of knowledge that can be applied in invention and innovation (cf. Biddle, 2004).

Leonard and Sensiper (1998) discuss three ways in which tacit knowledge is applied in

innovation: (1) in problem solving (unconscious pattern matching cognition), (2) in problem

finding (framing), and (3) in prediction and anticipation (intuition/hunches). Innovation occurs

through creativity and social interaction. Observations of this behavior have recently beenreconfirmed by Biddle (2004). Innovation is dependent on divergent inputs and intellectual

ferment, and requires a variety of alternative ideas. The conflict inherent in resolving divergent

views is a key element in generating new ideas. Intellectually heterogeneous groups tend to be

more innovative than homogeneous groups. Ultimately, convergence occurs on a viable

outcome of the group conversation that becomes the innovation. Three types of tacit knowledge

need to be managed: (1) overlapping specific knowledge (between individuals), (2) collective

system knowledge, and (3) guiding tacit knowledge.

Blackler (1995) has criticized the view of knowledge as a resource, and the emphasis in

the academic and management literature on such concepts. Instead, it is suggested that knowing

as a process is a more useful object of study to understand the workings of knowledge in a firm.

Blackler based this critique on emerging theories of the nature of knowledge (also to be reflected

in Sveiby (1997)): that it is socially constructed rather than disembodied (Blackler, 1995, p. 55).

Knowledge cannot be divorced from context and transmitted either as abstract data or as

universally applicable approaches to problem solving; learning is not a passive process ... but an

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active one. Such thinking has been reflected in much of the literature on learning organizations,

and is incorporated into this view of the fusion process.

Another split in the streams of research occurs along the dimension of the role of the

firm. Dominant strands include the evolutionary theory of the firm, rooted in Schumpeterian

views of economic activity, and the resource-based view of the firm, the current stream

beginning with the work of Penrose. Nonaka has attempted integration by extending the

information processing view to the idea that firms exist to resolve conflicts that cannot be

resolved by markets alone, which he calls the dialectical view of the firm. In this conception, the

firm is perceived as being the most efficient locus for the resolution of conflicting ideas,discontinuities and dissonances, to develop new ideas that better reflect operational reality. The

entrepreneurial firm itself also can be seen in some sense as a thought experiment (Block and

MacMillan, 1985). These concepts of the firm as a dialectical being and as a thought experiment

form key underpinnings of the idea of knowledge fusion.

2.1.3 Typology of Knowledge

The nature of knowledge can be described in a number of complementary perspectives.

One perspective is concerned with the subject-matter of knowledge. For example, Simon

(1945/1997, pp. 54 & 347) suggests that invention and product development require two types of

knowledge: knowledge about needs to be filled and knowledge about things that can be done

(i.e., about the laws of nature and what they make possible). (p. 347)

Another perspective describes a progression of increasingly meaningful and actionable

states of knowledge, beginning with the capture of raw stimuli or sequences of symbols as data

and progressing through a series of integrations and distillations to eventually achieve wisdom

(Rehuser & Kremar, 1996, p6; Bell, 1999; Sharif, 2005a). Sveiby (1997, pp41-43), building on

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imagination of both researchers and practitioners at various times since. Schumpeter (1947)

describes a close relationship between entrepreneurship and innovation. He differentiates

innovation, which involves bringing something of value to market, from invention, which is the

generation of new ideas or things, not yet realized in the social milieu. This distinction between

invention and innovation is important, as many inventions languish or die on the vine if they

do not become viable through realization in the market through innovation.

Penrose built on the premise that long-term success of a firm was built on innovation, on

adaptation and extension of the firms resources and capabilities, especially technological

(Penrose, 1959 cited in Cantwell, 2000/2001). Penrose (1959) is often cited in the literature oninnovation and intellectual capital as the basis of the resource view of the firm, a prevalent theme

in these research areas.

Nelson and Winter (1982) describe innovation in terms of evolutionary processes. Their

theory involves the following components (Nelson, 1987, pp12-13): (1) a mechanism that

introduces novelties to the system its workings involve a significant random element, and

(2) a mechanism for selection expanding the relative importance of some (entities) and

diminishing that of others. Nelson also suggests the possibility of a radical introduction of a

new entity into the system not previously present.

The growth of scientific knowledge in many fields coupled with increased competitive

pressures from many sources has led to higher theoretical content of inputs to innovation. For

example, Senge (1990, p. 336) suggests that increasing the application of theory-based strategies

improves business performance. Drucker (1969, pp38-39) suggests that the new industries that

will expand and even drive the future economy will be based on technologies derived from

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knowledge but knowledge in its entirety. Not just scientific knowledge but also cultural

knowledge. Civilization and technology are intertwined and mutually shaping.

From a research perspective, two major loci of activity can be observed, one concerned

with innovations as the object of study, and the other concerned with the processes necessary to

create these innovations. These two areas are discussed in more detail in the following sections.

2.2.1 Innovation as Object

A considerable body of literature has been written about the genesis and development of

innovations as objects (often technological in nature), and then the subsequent diffusion of those

innovations over time and space. Most of the discussions of innovation, certainly as early as

Schumpeter (1947), differentiate between improvements in existing society and technologies

(incremental innovation) and more radical changes resulting in disruption or replacement (radical

innovation). The research interest in this distinction between radical and incremental innovation

has continued to generate new work (e.g., Nitenson (2005) discusses how perceptions of radical

vs. incremental innovation affect acceptance of innovation in ICT services).While many of the discussions of innovation focus on specific technologies usually

hard technologies such as tools or on technology in general, Sharif (1986, 1988, and 1995)

has suggested that it is useful to view technologies as manifest in four distinctive embodiment

forms:

(1) Technoware (Tools) Object-embodied physical facilities, like artifacts, implements,

machines, vehicles, and structures (Note that this is often the category associated with

discussions of technology). This component of technology is the necessary core for

every management function and transformation or/and services related activities.

Technoware represents the physical facilities of technical performance that amplify

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underpinning a technological system for a transformation operation, or services platform,

or the specific management processes in effect. Good inforware enables quicker skill

development and also results in savings in terms of time and resources utilized for any

organized endeavor; and

(4) Orgaware (Procedures) Organization-embodied operational schemes, like recipes,

operational steps and methods. This component of technology essentially refers to the

framework of organized collective work that makes the task-tool relationship useful and

rewarding. Orgaware is the implemented process for producing quality outcomes by a

team, at a particular time with a permissible cost. Orgaware is like a project managementroutine related to a team endeavor. Orgaware includes the logic of systematized method

for integration and coordination of activities and resources for achieving desired goals of

an organization in producing goods or providing services. Orgaware also includes the

practiced procedures of value networking and coordination/cooperation among

stakeholders.

In practice, these types of technologies are often found in various combinations

technological systems are used by organizations as transformation mechanisms for goods

production, as infrastructural platforms for services provision, and as drivers of operational

efficiency and effectiveness. For example, in a software development project, a subset of the

technologies in use includes computer workstations, communication networks and servers

(technoware); software standards, requirements and other documentation, and databases

(inforware); various subject matter experts, both business and technical, such as database

administrators, business and systems analysts and programmers (humanware); and

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methodologies and best practices (orgaware). All of these technological elements are

interwoven and interacting in the accomplishment of the project.

2.2.2 Innovation as Process

A second area of considerable research has been the process of innovation that is, the

processes, factors, conditions, etc. that lead to innovation. Utterback (1971, p. 78) proposed a

model of a technological innovation process that shows the driving force of customer needs and

technical means leading to innovation and eventual delivery of new offerings to the marketplace.

The overall innovation process involves three sub-processes: (1) idea generation needs are

recognized and technical means identified to meet needs. This information is then synthesized to

create an idea or proposal for development; (2) problem-solving the idea or development

proposal is partitioned into constituent sub-problems, technical goals and priorities are set,

alternatives are identified and evaluated; all of this leading to an original solution or invention;

and (3) implementation and diffusion manufacturing, engineering, tooling and plant startup

required to bring the prototype solution, or invention, to its first use (process) or marketintroduction (product). These processes operate in the context of and influence the ongoing

state of technical knowledge as well as economic and social utilization. Burgelman et al (2004,

p. 3) expand the model of the elements involved in technological innovation. Technological

entrepreneurship is portrayed as the linkage between the technical and the commercial world. A

number of interrelated activities are shown as producing inventions, discoveries, and

technologies (generated from tinkering, experimenting, research and development) as well as

technological innovations (generated from product and process development or market

development). Administrative capabilities are viewed as an essential element in managing these

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productive activities. There are knowledge flows and feedback among the various activities

encompassed by technological innovation..

These models often treat, or at least describe as such for simplicity, innovation as a linear

process with some degree of feedback often resembling related models for product engineering

processes. Of course, these activities do play out over time in any given development activity,

and in a macro sense can be discussed usefully in the sequence shown, but the actual sequence of

individual events and activities is less clear, and may vary considerably among specific cases of

innovation. This tendency towards linearity shows up in discussions of the primacy of market-

pull versus technology-push that recur in the conversation on innovation (e.g., Gumbau-Brisa,2004) a key difference between these two conceptions is the source of requirements: (1) in

technology-push, invention creates the possibility of new products, or (2) in market-pull,

customer needs and desires generate requirements that spur the search for means of satisfaction.

In actuality, both forces may be at work simultaneously in a messy back and forth as ideas,

processes, and outcomes evolve.

Another train of discussion in the literature is described by von Hippel and von Krogh

(2003), contrasting two modes of innovation: (1) a private investment mode where intellectual

capital is closely held (e.g., through intellectual property protection regimes) to maximize return

to the innovator, typified by most businesses, and (2) a collective action mode where

innovators collaborate to produce a public good not being provided by the market, for example

academic research. Their recent work suggests that new private-collective modes, such as

open source development, are emerging that combine elements of both models. Von Hippel and

von Krogh suggest that study of private-collective modes may offer new insights into innovation,

especially given the messiness and richness of the hybrid model even leading to substantial

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reconsideration of current models of innovation processes. Study of such models may provide

insight into the workings of internal markets for innovation (i.e., those mechanisms for stocks

and flows of information within the organization), where there is a need for both personal reward

and collective achievement as an example, there may be implications for devising incentive

models for knowledge workers. Similar dynamics may be at play in exploiting the fruits of

academic research intellectual entrepreneurship, described in Section 2.3 Intellectual

Entrepreneurship , has been described as one means to achieve this realization.

2.2.3 Environmental Conditions for Innovation

Wallace (1982, pp. 151-154), studying innovation in the early industrial age, observes

that institutional and societal characteristics influence whether successful innovation can occur.

He observed that institutions that had an opportunity to exist for a span of time permitted internal

transfer and concentration of technical information in a small paradigmatic community.

Successful innovation also required access to resources, including skilled labor, and willingness

on the part of the institution to support innovation and invest in best practices. Externally,innovation was more prevalent in societies that had a general ambience of encouragement of

technological innovation as a contribution to social progress, as well as a certain degree of

social mobility that allowed entrepreneurs to perceive the possibility of personal gain from their

activities. From a structural standpoint, chartered legal entities evolving from extended families

and partnerships in some senses a nascent form of corporation can be seen emerging for such

reasons as to protect patent rights (pp. 66-67).

According to Porter (1990, 2000), the companies that will do best in the global market

are those that have ideal conditions "at home" for fostering companies with a high competitive

advantage. Porter observes that a comprehensive combination of production factors, demand

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conditions, related and supporting industries, and firm strategy, structure and rivalry are needed

to create an environment within which a competitive advantage can be created. And these

conditions must be created by the nation and by the industrial cluster. Even so, any advantage

gained must be sustained through relentless improvement. Ultimately, even given the ideal

environment, companies themselves are responsible for creating and sustaining a competitive

advantage.

Nations do best in those areas they value -- "where their heroes come from." The best

and the brightest have to be attracted to an industry. This has implications for industry and

government in creating a public image for certain occupations, investment, policy, etc.A cluster of industries and institutions is proving to be a useful construct for examining

competitive advantage (Porter, 2000). Companies do not exist in a vacuum, but instead grow

and thrive in a network of suppliers, customers, universities, governments, and other institutions.

The cluster, in the best conditions, is mutually reinforcing. Innovation is fostered through the

exchange of ideas and through competitive pressures -- the more so if local rivalries are intense

(as long as they are not destructive). New businesses often materialize in the context of the

cluster through spin-offs, those who have a better idea, and other ferment of knowledge and

ambition. Clusters also offer resource alternatives to companies' vertical integration. For

example specialized skills, manufacturing, and other applications of knowledge and technologies

can be outsourced to other firms in the cluster, allowing a company to maintain its focus. (An

example of the cluster behavior, although domestically focused: In the Federal ICT industry,

there is a constant interweaving of corporations and consultants to gain the specific expertise to

be able to perform various projects. The shortage of qualified technical resources usually means

that even the largest firms must seek at least some of the best talent and knowledge from outside

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sources. Local universities also are a part of the equation -- with educational services targeted

specifically to the needs of this cluster. Dozens of associations and trade groups help foster the

exchange of ideas and healthy competition as well as cooperation.)

Government's role in general factor creation (e.g., education, basic infrastructure) is

necessary but not sufficient to create competitive advantage. There must be ways to encourage

or stimulate specialized (industry specific) factor creation. Government must avoid

protectionism and apply pressure where needed e.g., in fostering anti-trust, safety &

environmental standards.

2.3 Intellectual EntrepreneurshipRecognizing the importance of intellectual capital, it was a logical step to develop the

concept of intellectual entrepreneurship, an evolving area of study championed in particular by

Kwiatkowski in Poland and Cherwitz in the United States, each with their unique perspectives

Kwiatkowski has been concerned with entrepreneurial activity in general and how knowledge

transformation, including knowledge developed in academia, is a key focus in the economy

(Johannisson et al, 1997; Kwiatkowski, 1998/1999) while Cherwitz is more focused on shifting

academic focus to create citizen-scholars. (Cherwitz & Darwin, 2001). In either case, at the

core of the idea is entrepreneurship applied to the conversion of knowledge to wealth, i.e.,

developing and exploiting intellectual capital that is based on a solid foundation of theoretical

knowledge. That this idea is gaining some traction even outside of academic circles is evidenced

by a number of non-academic articles including a recent editorial in the Washington Post citing

Cherwitz work at the University of Texas (Raspberry, 2005). Sharif (2005a), building on

Mintzberg (2004), discusses the importance of balancing science, art, context (craft) and courage

in intellectual entrepreneurship. At the project level, Hollandsworth-George (2004) has looked

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at the specific dynamics of the project team learning environment, with particular emphasis on

the key role the project manager plays in the learning processes. The project manager guides the

learning processes within the team and is an important source of knowledge, echoing the

characteristics of the intellectual entrepreneur.

Part of the capacity of the intellectual entrepreneur must be for critical thinking and

reflection. This is congruent with Senges (1990) observation that effective managers in a

learning organization must have time to reflect on the successes and failures of their

organizations in order to be able to learn leading to better strategies for the future.

2.4 Performance Measurement Drucker (1995, pp 6-7) proposed in 1995 that effective methods for assessing costs and

outcomes of most knowledge-based and service work, with the possible exception of laboratory

research, would be developed within 10 to 15 years. From the cost side, Drucker saw activity

based costing emerging as a new model for assessing the complete value chain of a given service

offering. 6 He points out (p. 8) that, at least in economic terms, the individual company is

essentially a fiction the customer is concerned with the total value versus cost of the received

good or service, and is less concerned with the details of the value chain that contributes to the

ultimate delivery (with the notable exception of customers that impose

Documents

KNOWLEDGE Management for Technological Innovation in Orgns - For Creating Intellutural Capital