See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/247831655
A dynamic view of knowledge and information: A stock and flow based
methodology
Article in International Journal of Management and Decision Making · January 2008
DOI: 10.1504/IJMDM.2008.021221
CITATIONS
READS
53
1,106
2 authors:
Livio Cricelli
Michele Grimaldi
University of Naples Federico II
University of Cassino and Southern Lazio, Cassino, Italy
99 PUBLICATIONS 2,412 CITATIONS
107 PUBLICATIONS 4,580 CITATIONS
SEE PROFILE
All content following this page was uploaded by Michele Grimaldi on 01 June 2014.
The user has requested enhancement of the downloaded file.
SEE PROFILE
A dynamic view of knowledge and information: a stock and
flow based methodology
L. Cricelli, M. Grimaldi, 2008. A dynamic view of knowledge and
information: a stock and flow based methodology, International Journal
of Management and Decision Making, Vol. 9, No.6 pp. 686-698.
Livio Cricelli and Michele Grimaldi
Department of Mechanics, Structure and Environment, Faculty of
Engineering, Università di Cassino, Via G. Di Biasio, 43, 03043 Cassino
(FR), Italy, Tel: +39 0776 299 3418; Fax: +39 0776 299 4353; E-mail:
cricelli@unicas.it; E-mail: m.grimaldi@unicas.it
Abstract: The role of knowledge as strategic resource within many
companies has been widely recognized, but resulted difficult to be
evaluated. Traditional accounting systems focus on the evaluation on
tangible assets, neglecting the value addition contributed to business
performance by intangibles. This paper explores the intangible evaluation
concept and suggests a stock and flow based analysis to assess a
methodology that could put into evidence static and dynamic aspects and
their mutual impact on business performance. A general sketch, clarifying
the numerous cause-effect relations among intangible assets, is provided to
support the management in decision making. The aim of this methodology
coincides with the main target pursued by firms: to get a competitive
advantage in order to fill the gap respect to market leaders or to maintain
the already acquired leadership.
Keywords: Knowledge; Information and Knowledge Management;
Intellectual Capital; Intangible Asset Evaluation Methods; Stocks and
Flows Approach; Dynamic Capabilities.
1.
Introduction
In the last years, knowledge management has become one of the most
important topics in business performance analysis. Knowledge has
assumed the role of strategic resource within many companies and the
struggle of the market has made them aware of the primary role of
knowledge assets in the achievement of a distinctive position (Davenport
and Prusak, 1998; Nonaka and Takeuchi, 1995; Skyrme, 2000; Tiwana,
2000; Zack, 2000). But a really productive management of information
and knowledge results only from the definition of precise plans and
careful guidelines in organizations, in order to exploit the relevant impact
of the intangible assets on economic performance thoroughly. Moreover,
companies need to measure every asset concurring to the value creation
process.
Several models and methodologies have been developed to identify the
elements that influence performance primarily, on the basis of the
concepts: “you get what you measure” and “you get what inspect, not what
you expect” (Neely and Adams, 2000).
Traditional financial accounting methods focus on the evaluation of
tangible assets, looking at the identification and the application of
financial indicators, without taking into account knowledge assets.
Intangible evaluation methods have been set up to help organizations in
recognizing the fundamental role of intangible assets (Kaplan and Norton,
1996; Edvinsson and Malone, 1997; Sveiby, 1997), but it has been found
out the relevance of focusing not only on the value of each singular asset,
but also on their reciprocal interactions (Ghalib, 2004).
The purpose of this paper is the definition of an intangible asset evaluation
methodology that goes beyond their static analysis, taking into account not
only their economic value but also the added value generated by the
knowledge flows running among them. On the basis of the “Dynamic
Capabilities” theory, the methodology proposed in this paper identifies,
defines and analyses both the organizational knowledge stocks, that are
the contribution of knowledge assets to the value creation, and knowledge
flows, that are the dynamic interrelations among stocks. Thus, it has been
possible to show the real contribute of every knowledge asset and its direct
and indirect capability of influencing organizational economic
performance.
The paper is organized as follows. Section 2 provides the critical literature
analysis of the main evaluation approaches and methods about stocks and
flows approaches. In section 3, the contribution of the Dynamic
Capabilities theory to our methodology is described in the details. Section
4 outlines the methodology development, where knowledge stocks are
defined and classified on the basis of their meaning and pertinence and
where knowledge flows are analysed and evaluated. Section 5 draws
conclusions through a discussion on research results and their further
development.
2
Stock and flow approaches and intangible asset
evaluation methods
Traditional accounting systems, developed so far, have restricted their
purpose to help management in estimating quantifiable values of
economic performance and in assessing the tangible-based transactions
with the external environment. The inadequacy of these usual standards
has pushed companies to require new performance evaluation methods,
that could take into account also intangible assets, not enough considered
before. The new perspective, in fact, asserts that the value creation process
depends even more on intangible resources and on their exploitation
(Membrillo and Koenig, 1998; Smith, 1998) and that tangible resources
can be considered as commodities and should be analyzed jointly with
intangible assets. Traditional accounting systems, therefore, should be
integrated with instruments able to return a systematic monitoring and
evaluation of financial and non-financial assets. But, the complexity of
reporting intangible values in financial accounts only by means of
traditional indicators can not provide exact information on economic
performance. New approaches have been attempted in order to pursue
more accurate financial measures.
According to Dierchx and Cool (1989) and to Bassi and Van Buren
(2000), evaluation and management methods of intangible assets can be
classified into two groups, based on stocks or flows. They focus on
different perspectives and divergent suppositions: stocks represent the
available level of knowledge within the organization; flows represent the
outcome of knowledge processes in the stock interactions.
The stock approach is quite exclusively focused on the intellectual capital
that can be described as the economic value of three categories of
intangible assets (Bontis et al., 1999; Chatzkel, 2001): the Human Capital,
which represents the knowledge, generated and owned by individuals, and
refers to their know-how, capabilities, skills and expertise; the Structural
Capital, which includes the available capabilities and the gained
knowledge mastered by the organizational structure itself, such as patents,
processes and culture; the Relational Capital, which relates to all the
external relationships with stakeholders, such as customers and suppliers.
In general, the output of the stock approach consists in an inventory of
intangible assets, which provides a measure of their qualitative and
quantitative contributions.
The flows approach goes beyond the stocks value of intangibles and
intends to identify the value they produce or create, directly or indirectly;
so, interrelationships among knowledge stocks are examined, focusing on
their influence on economic performance and managerial effectiveness.
Research carried out so far has been centred only on the identification of
components of intellectual capital and many organizations have chiefly
attempted to measure the stock value, simpler to be ascertained than that
of flows (Botha, 2005), without taking into consideration the supply
provided by flows, that is a really important indication for the
management. The extension of the traditional method of analysis into a
dynamic systemic approach resulted as a necessary consequence of the
limits of the above mentioned theory (Nissen, 2000; Dostal, 2005).
The evolving path of the most diffused and applied intangible assets
evaluation methods starts from models that only care for knowledge stocks
to those increasing their attention to intrinsic dynamics among stocks,
apart from their chronological succession.
At the beginning of the path, the “Technology Broker” (Brooking, 1996)
bases its analysis on a financial evaluation of four components of the
intellectual capital, while the “Intellectual Capital Index” (Roos et al.,
1998; Pike and Roos, 2001) gives an index of the intangible assets
measured in a holistic way.
The “Skandia” Business Navigator (Edvinsson and Malone, 1997), too, is
based on the static interpretation of intangibles, since, although its five
perspectives of the intellectual capital assign the real contribute to the
innovation of each organizational and structural element, as a matter of
fact they remain aligned to the traditional accounting systems.
Along the developmental path, the transition towards a more dynamic
view of the intangible evaluation methods is represented by the Balanced
ScoreCard (Kaplan and Norton, 1996) especially for its purpose of relating
the output measures with the performance indicators, through a causal
analysis moving towards the mechanisms of value creation, but still
without considering the flows among intangible assets.
As an extension of the IC-Index, the empirical research of Chu et al.
(2006) deals with an association of components of the intellectual capital
with the value and the performance of the firm and show their
considerable influence in the direction of the value creation process.
Petrash (1996), as well, postulates that the components of the intellectual
capital contribute to the economic performance in a process of mutual
sharing, promotion, and growth.
Smith (2003) has suggested a new method of measuring the value of IC
and recommends improvements in the valuation of IC, providing ways to
measure human resources development contribution to the firm at the
organizational level.
A significative step was then put forward by the Intangible Asset Monitor
(Sveiby, 1997, 2001; Sveiby et al., 2002) that mapped the existing
knowledge flows among the three categories of the intellectual capital,
even though the causal link between intangible and financial economic
performance was not taken into the proper account. Also, human resources
were not recognized as fundamental for the knowledge creation and
distribution processes.
Within the transition phase towards flows analysis, it is worthwhile
mentioning Membrillo and Koenig (1998) who, in a stock and flow view,
have proposed a systemic approach, focused on flows of interaction
between the individual learning and the development of intellectual
capital. Following the same trend, Yim et al. (2004) have suggested a
knowledge-based method, centred on system dynamics theory that helps
management in decision making. The method proposes an integrated
knowledge model to transform individual mental models into explicit
knowledge by translating partial and implicit knowledge.
Ahn and Chang (2004) have developed a methodology to assess the
contribution of knowledge to business performance by employing product
and process as intermediaries between the two, identifying four
components: Knowledge, Process, Product, and Performance. Considering
process and organizational performance indirectly linked to product and
financial performance, respectively, they assess the contribution of
knowledge to business performance, rather than trying to measure the
value of knowledge directly.
Finally, a really consistent contribution was added to the flows perspective
by the research of Smith (1998, 2002) who provided a Systemic
Knowledge Management. This approach emphasizes the existing
interconnections among financial, tangible and intangible areas and
suggests how to manage them effectively and efficiently, through a
dynamic view.
3
The dynamic methodology to manage information
and knowledge
A dynamic approach to manage intangible assets that takes into account
both knowledge stocks and flows has been here defined. By this approach,
limitations of the above mentioned methods that consider stocks and flows
distinctly are attempted to be exceeded. The study is specifically based on
the analysis of the kind of the intangible assets involved in the
organization and on the analysis of their dynamic interactions. Knowledge
processes have been regarded to as a set of relations and propagations
within organizations that act as a system of actions and reactions mutually
influencing. Organizations have been considered open systems since many
knowledge processes are strongly dependent on internal and external
context. This methodology, based on the Dynamic Capabilities theory, has
intended to manage every organizational knowledge process, by
identifying and analyzing not only dynamic connections among the
organizational business areas but also interrelationships among each assets
within each area.
The methodology consists of four phases: (1) Definition and analysis of
the intangible asset categories; (2) Characterization of “intracategory”
flows among intangibles; (3) Identification of the “intercategory” flows of
the whole causal loop diagram; (4) Analysis of cause-effect relations and
knowledge-based decisions making.
3.1. Definition and analysis of the intangible asset categories
Intangible assets of a company have been grouped into four fundamental
categories derived by the well known distinction of the intellectual capital
into three components: human, structural, and relational. The classification
of intangible assets into the four categories has been greatly made easier
by the adoption of the dynamic view, which allowed a more correct
interpretation of their dynamic interactions. A classification of interactions
among knowledge assets has been carried on rather than the classification
of the assets themselves. The four categories, knowledge, processes,
customers, and suppliers, are described in the following (Fig. 1).
Figure 1: Intangible Asset Categories and their Interactions
The “Knowledge” category refers to the value creation capability of a
company through the internal available intangible resources in the aim of
generating new knowledge. Thus, “Knowledge” focuses on the
fundamental role of intangible assets in achieving business goals and takes
into account human capital elements, such as organizational know-how,
expertise, capabilities, skills, and competences.
The “Process” category considers the set of industrial, managerial,
organizational and technological processes. These assets are both
generated internally by the staff and represent the external knowledge
taken into the organization. In particular, this category includes those
intangible assets that belong to the company and remain inside it in a
value added long length process, such as patents, copyrights,
organizational culture, internal management practices, informative and
administrative system, and all the internal interrelationships.
As for the “Customer” category, processes of the customer oriented
approach have been analyzed having regard not only to customer
satisfaction, but also to the capacity of attracting new customers or of
retaining existing customers.
The “Suppliers” category examines the processes related to the Supply
Chain Management that cross the whole productive process horizontally.
In particular, this category should assess whether suppliers are in a
position to plan future operations and to participate in company business
processes, through the establishment of long-term and stable relationships.
3.2. Characterization of “intracategory” flows among intangibles
This phase of methodology consists in deriving the main initiatives
pertaining to each category and in identifying and analyzing the existing
flows among the intangible assets within each category. Interconnections
among the derived intangibles within each category have been illustrated
graphically in an influence graph, where vertexes represent stocks and
edges represent causal flows. In particular, full lined arrows represent
positive influences among stocks, while broken lined arrowsmean
negative influences.
3.2.1
“Knowledge” intracategory flows
Knowledge competences can be developed and/or increased through four
main initiatives: learning and training programs, recruitment, retribution
policies based on wage incentives, and staff motivation (Fig. 2).
Figure 2. “Knowledge” intracategory flows
These initiatives improve economic performance, increasing quality and
productivity. Knowledge impacts on decision making at every
organizational level: strategically, in defining targets; tactically, in
acquiring and coordinating intangible available resources; operatively, in
exploiting individual knowledge and sharing collective one. In particular,
companies offer learning and training programs in order to increase the
individual knowledge of participants. In this way, knowledge embedded
within the company expands, because individual performance and internal
satisfaction improve and knowledge becomes more applicable. The value
creation process strictly depends on individual skills and competences and,
above all, on their transformation into company skills and competences. In
this case, the codification of knowledge from tacit to explicit allows the
increase of organizational knowledge and the achievement of a
competitive advantage. Also, recruitment policies enable companies to
reduce the gap between necessary and available human resources, while
retribution policies influence employees’ satisfaction, encouraging and
directing their efforts towards organizational growth. Finally, motivation
initiatives require vision and mission shared within organizations and,
therefore, need internal communication investments.
3.2.2
“Processes” intracategory flows
The “Processes” category is influenced by the development and the
improvement of internal processes, by IT and R&D investments and by
the diffusion of organizational culture (Fig. 3). In an excellent structure, in
terms of organizational culture and internal processes, employees
recognize effectively the company vision and the business aims,
enhancing their working activities, in terms of effectiveness and
productivity. R&D investments enable companies to develop new
products, copyrights and patents, strengthening organizational image and
increasing the potential customer portfolio. Finally, IT improves internal
communications, allowing staff members to acquire and to transfer
knowledge. As a consequence, the increase of organizational competences
influences economic performance positively.
Figure 3. “Processes” intracategory flows
3.2.3
“Customers” intracategory flows
Value generation and its transfer to customers depend on three main
initiatives: relationships, marketing and promotion. Every firm should
enforce relationships with its customers, by monitoring and improving
customer satisfaction, in order to increase “customer capital” (Fig. 4).
Customers should be considered as central actors of the organization:
through their opinions, suggestions and claims, the company should
redesign and improve productive and selling processes. Moreover,
marketing and promotion investments can enforce organizational image
and brand awareness. Indeed, promotion and marketing operations support
the selling process of products and services, favouring the interest and
attraction of new customers.
Figure 4. “Customers” intracategory flows
3.2.4
“Suppliers” intracategory flows
Knowledge sharing, partnerships and communication have been
considered fundamental “Supplier” initiatives (Fig. 5). Through the
interaction of these initiatives, suppliers and companies should be
facilitated in cooperation on product development and process
improvement. Intensive flows stress on relationships between suppliers
and commitment, sharing requirements for productive aims.
Communication activities with suppliers allow companies to capture their
suggestions, by improving the productive processes and exploiting
collaboration benefits. Companies should create and enforce partnerships
with suppliers, in order to implement R&D activities, innovation processes
and to ensure a high rate of quality and delivery time efficiency.
Figure 5. “Suppliers” intracategory flows
3.3. Identification of the “intercategory” flows of the whole causal
loop diagram
The existing relations among the four categories are shown in figure 6,
where a view of the dynamic internal and external interactions is
illustrated. The causal loop diagram outlines the most essential dynamics
and, in particular, the most relevant existing dynamic aspects, due to
feedback and reciprocal iteration, that make clear their consequence in the
long period; these aspects are often neglected, because of the well known
complexity of a company system.
From the figure, it is possible to follow the impact of each intangible asset
on the other stocks and, consequently, their influences on each category. It
results also evident that a company aiming to improve its competitiveness
in respect to the performance of competitors should define which
initiatives has to invest on. So, the four category account for the range of
potential investments that can reduce the gap with competitors.
As the flows outgoing from the “Knowledge” category indicate,
investments on this category let the company obtain several benefits, such
as the improvement of internal processes and the increase of customer
satisfaction and retention. In addition, the satisfaction of company internal
demands, in terms of human capital requirements, and of external
demands, in terms of supplier or partnership requirements, is achieved,
due to the effort of transforming knowledge from tacit to explicit.
The flows outgoing from the “Processes” category show that investments
on this category improve the service level, acting on customers’
requirements and on their satisfaction, and have positive influence on
company attraction and client loyalty, making vision, targets and internal
values shareable.
Also, flows outgoing from the “Suppliers” category show that investments
in this category can enhance their level through the establishment of
partnerships with suppliers, thus favouring the collaboration on productive
processes; moreover, these investments sway the knowledge base of the
company positively, with a direct action on knowledge sharing and
communication with suppliers.
Figure 6. Intercategory flows
3.4. Analysis of cause-effect relations: knowledge-based decisions
making
A significant impact on organizational performance has been derived by
the application of knowledge to decision making. The proposed
methodology transforms mental models into explicit knowledge by
translating partial organizational knowledge into an integrated dynamic
view. The analysis of the whole causal loop diagram provides a useful
general sketch that clarifies the numerous cause-effect relations among
different intangible assets. This diagram allows, when necessary, to
operate on the items really affecting the analyzed aspects. In other words,
it is possible to decide which initiative is more performing than another. In
this way, the variation of the proper value-driver can improve the
performance of all the intangible assets. For instance, it is well known that
the same procedure is applied in the medical context to identify and to test
the suitability of some medicines on the basis of their collateral effects.
The greatest difficulty for a decision maker is the ability to know how
assessing the consequences of decisions. The evaluation of a direct causeeffect relationship among two factors is relatively simple, while it gets
more complicated if they are not directly connected or if their link is
characterized by noise or feedback. Moreover, the evaluation failure
makes high the risk to invest on no performance issues or on negative
effect aspects; such uncertainties strongly impact on strategic decisions.
When a reality replication modelled mechanism is supplied for the
decision-making process, it is possible to test each possible decisional
choice and evaluate behaviours and results with the utmost flexibility and
simplicity. Such an effective tool allows to carry on the analysis not only
by examining real-time images of the situation - that should be a poor
enhancement of the strategic management intervention - but essentially by
estimating the possible future scenarios that evolve from the strategic
decisions adopted.
Conclusions
Traditional evaluation methods of intangible assets focus on knowledge
stocks and hardly ever take into consideration knowledge flows among the
stocks. But any measurement of intangible assets should consider the
value of the synergies and the interrelations existing among intangible and
the value added by knowledge flows to the overall company profitability.
The described methodology represents an attempt to consider both
knowledge stocks and flows at the same time and provides a static and
dynamic analysis of their impact on company performance. The
methodology originates by the need to get over the limitations of the
traditional evaluation approaches: the short term static point of view. In
fact, it allows to design actions and to analyze, in the present, their future
consequences in the medium and long term, giving the proper value
drivers the suitable power and changing strategies timely.
The proposed approach, derived by the Dynamic Capabilities theory, gives
the possibility to show the contribute of each intangible asset to the
knowledge management and to the value creation within organizations. In
this way, the deep awareness of the whole system of intangible assets and
of their open dynamics could not but help in adjusting aims carefully. To
this end, the intangible assets of a company have been grouped into four
fundamental categories, on the basis of their pertinency. All knowledge
flows existing among the intangible assets within each category have been
considered in order to evaluate each category properly. Each category, in
fact, is characterized by a system of stocks and flows that determines
influences of growth and development. In this connection, not only flows
among stocks within each category have been detected (intracategory
flows), but also relationships existing among those flows pertaining to
different categories have been analyzed (intercategory flows). The
analysis of the four categories is not limited to present, but is future
oriented in order to define medium and long term consequences of the
appropriate initiatives to be adopted.
The methodology considers the systemic nature of the firm and the
economic environment in which it operates, showing the contribution of
knowledge to the value creation process and to decision making. The aim
of this methodology coincides with the main target pursued by firms: to
get a competitive advantage in order to fill the gap respect to market
leaders or to maintain the already acquired leadership.
A further advancement of this research should require the transformation
of the cognitive aspects of intangibles into quantitative variables and
functions. In this way, not only a validation of relationships among stocks
and flows, but also the verification of all the systemic knowledge
methodology could be achieved.
References
Ahn, J.H., Chang, S.G. (2004), “Assessing the contribution of knowledge
to business performance: the KP3 methodology”, Decision Support
Systems, Vol. 36, No.4, pp.403-16.
Bassi, L.J., Van Buren, M.E. (2000) “New Measures for a New Era”, in
Knowledge Management: Classic and Contemporary Works, Morey
D., Maybury M., Thuraisingham B. (eds), MIT Press, London.
Bontis, N., Dragonetti, N.C., Jacobsen, K., Roos, G. (1999) “The
Knowledge Toolbox: A Review of the Tools, Available to Measure
and Manage Intangible Resources”, European Management Journal,
Vol. 17, No. 4, pp. 391–402.
Botha, D. F. (2005) “Towards an instrument for surveying knowledge
management practices”, South African Journal of Business
Management, Vol. 36, No. 1, pp. 1-6.
Brooking, A. (1996) Intellectual Capital: Core Assets for the Third
Millennium Enterprise, Thomson Business Press, London.
Chatzkel J. (2001) A conversation with Goran Roos, in: Chatzkel (Ed.),
Article Accepted for the Journal of Intellectual Capital and Accepted
as a Chapter in the Internet-Published Book Conversations on
Intellectual Capital.
Chu, P. Y., Lin, Y. L., Hsiung, H. H., Liu, T. Y. (2006) “Intellectual
capital: An empirical study of ITRI”, Technological Forecasting &
Social Change, Vol. 73 pp. 886–902
Davenport, T. H., Prusak, L. (1998) Working Knowledge: How
Organizations Manage What they Know, Harvard Business School
Press, Boston.
Dostal, E. (2005). Biomatrix: A systems approach to organisational and
societal change. Cape Town: AFRICAN SUN MeDIA.
Edvinsson, L., Malone, M. (1997) Intellectual Capital: Realising Your
Company’s True Value by Finding its’ Hidden Brainpower, Harper
Collins, New York.
Ghalib, A. K. (2004) “Systemic Knowledge Management: Developing a
Model for Managing Organisational Assets for Strategic and
Sustainable Competitive Advantage”, Journal of Knowledge
Management Practice, January.
Kaplan, R. S., Norton, D. P. (1996) “Using the Balanced Scorecard as a
Strategic Management System”, Harvard Business Review, JanuaryFebruary.
Membrillo, A., Koenig, U. H. (1998) “Impact of Individual Knowledge on
the Increase of Sustainable Intellectual Capital of Organizations - A
Systemic Approach”, System Dynamics Society 16th International
Conference, Quebec, Canada, July 20 – 23.
Neely, A., Adams, C. (2000) “Perspective on Performance: The
Performance Prism”, Journal of Cost Management, Vol. 15, No. 1,
pp. 7-15.
Neely, A., Kennerley, M. (2000) The Catalogue of Performance Measure,
Centre for Business Performance.
Nissen, M.E. (2002) An Extended Model of Knowledge-Flow Dynamics,
Communications of the Association for Information Systems,Vol. 8
pp. 251-266.
Nonaka, I., Takeuchi, H. (1995) The Knowledge Creating Company: how
Japanese Companies Create the Dynamics of Innovation, Oxford
University Press, New York.
Petrash G. (1996) “Dow’s journey to a knowledge value management
culture”, Eur. Manag. J., Vol. 14, pp. 365–373.
Pike, S., Roos, G. (2001) “Measuring the Use of Knowledge and the
Intellectual Capital of Companies”, special issue of Journal of
Operations
Research
Society
(JORS),
[online],
http://www.intcap.com/ICS_Article_2001_Msrg_Use_of_Knowledg
e_and_IC_in_Cos.pdf
Roos, G., Roos, J., Dragonetti, N., Edvinsson, L. (1998) Intellectual
Capital: Navigating in the New Business Landscape, New York
University Press, New York.
Skyrme, D. J. (2000) “Developing a Knowledge Strategy: From
Management to Leadership”, in Knowledge Management: Classic
and Contemporary Works, Morey, D., Maubury, M. and
Thuraisingham, B. (Eds.), MIT Press, MA.
Smith P. A. C. (2002) A Performance-Based Approach to Knowledge
Management, Journal of Knowledge management Practice.
Smith, P. A. C. (1998) “Systemic Knowledge Management: Managing
Organizational Assets for Competitive Advantage”, Journal of
Systemic Knowledge Management, April.
Smith M. E. (2003) “Another Road to Evaluating Knowledge Assets”,
Human Resource Development Review, Vol. 2, No. 1, pp. 6-25.
Sveiby, K. E. (1997) “The Intangible Asset Monitor”, Journal of Human
Resource Casting and Accounting, Vol. 2, No. 1.
Sveiby, K. E. (2001) “Methods for Measuring Intangibile Assets”,
[online], http://www.sveiby.com/articles/IntangibleMethods.htm
Sveiby, K. E., Linard, K., Dvorsky, L. (2002) “The Dynamic Intangible
Assets Monitor”, [online],
http://www.sveiby.com/articles/sdmodelkstrategy.pdf
Tiwana, A. (2000) The Knowledge Management Toolkit: Practical
Techniques for Building a Knowledge Management System”;
Prentice-Hall PTR, New Jersey.
Tyndale, P. (2002) A taxonomy of knowledge management software tools:
origins and applications’, Evaluation and program planning, Vol.
25, pp. 183-190.
Von Krogh G., Ichijo K., Nonaka I. (2000) Enabling Knowledge Creation
– How to Unlock the Mistery of Tacit Knowledge and Release the
Power of Innovation, Oxford University Press, New York.
Yim, N.H., Kim, S.H., Kim, H.W., Kwahk, K.Y. (2004) Knowledge based
decision making on higher level strategic concerns: system
dynamics approach, Expert Systems with Applications, 27, pp. 143158.
Zack, M. H. (2000) “Competing on Knowledge”, Handbook of Business
Strategy, pp. 81-88.
Figures
Figure 1: Intangible Asset Categories and their Interactions
KNOWLEDGE
CUSTOMERS
SUPPLIERS
PROCESSES
Figure 2. “Knowledge” intracategory flows
Human Resources
Necessity
Gap
KNOWLEDGE INITIATIVES
Available Human
Resources
Recruitment Retribution Learning and
Training
Internal
Satisfaction
Individual
Performance
Productivity
Individual
Competences
Motivation
Explicit
Knowledge
Internal
Communication
Applicable
Knowledge
KNOWLEDGE
Organizational
Vision
Organizational
Competences
Figure 3. “Processes” intracategory flows
Desired Level of
Processes
Gap
PROCESSES INITIATIVES
Current Level of
Processes
Organizational Culture Internal
Diffusion
processes
Organizational
Vision
Patents
IT
IT
R&D
New
Products
Organizational
Competences
Internal
Communication
Brand
Organizational Knowledge
Customer
satisfaction
PROCESSES
Service level
Productivity
Figure 4. “Customers” intracategory flows
Desired
Market share
Gap
Current Market
Share
CUSTOMERS INITIATIVES
Attraction
Relationships Marketing Promotion
Customer Satisfaction
Brand
Awareness
CUSTOMERS
Figure 5. “Suppliers” intracategory flows
Gap
Desired
Market share
SUPPLIERS INITIATIVES
Knowledge
Sharing Partnerships
Communication
Current Market
Share
Delivery Time
Quality
SUPPLIERS
Process
Collaboration
Figure 6. Intercategory flows
Gap
Necessary
Human
Resources
Organizational
Competences
Gap
CUSTOMERS INITIATIVES
Gap
Quality
Process
Collaboration
Current
Market Share
SUPPLIERS INITIATIVES
Partnerships
SUPPLIERS
Delivery
Time
Relationships Promotion Knowledge Communication
Sharing
Marketing
CUSTOMERS
Customer
Satisfaction
Awareness
Service
level
Desired
Market Share
Performance of Competitors
Gap
Current
Market Share
Competitiveness
Desired Level
of Processes
Performance
Gap
PROCESSES INITIATIVES
Productivity
PROCESSES
Current Organiz. Internal R&D IT
Attraction
Level of Culture processes
Processes
KNOWLEDGE INITIATIVES
KNOWLEDGE
Training
Recruitment
Learning
Retribution
Available Human
Resources
Productivity
View publication stats