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UNIVERSITY OF VAASA 

FACULTY OF BUSINESS STUDIES 

DEPARTMENT OF MANAGEMENT  
 

 

 

 

 

 

 

 

Timo-Pekka Uotila  

EPISTEMOLOGIES OF COMPETENCE RELATED KNOWLEDGE 

A System-theoretical analysis  

 

 

  

 

 

 

  

 

 

 

Master’s Thesis in  

Management  

     

 

VAASA 2010

 



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TABLE OF CONTENTS 
 

 

LIST OF TABLES AND FIGURES          5 

 

ABSTRACT              7 

 

1. INTRODUCTION 9 

1.1. Research problem                                                                                   ............ 11 

    1.2. The structure of the study                                                                           11 

 

2. ORGANIZATION AS A SYSTEM – THEORETICAL PERSPECTI VES 13 

2.1. The principles of an open system 18 

2.2. The principles of connectionism 20 

2.3. The principles of an autopoietic system 23 

2.4. Competence system of organization 28 

2.4.1. Competence in different levels 28 

2.4.2. Open system view to competence management 32 

2.4.3. View of competence based on the self-organization 35 

2.4.4. View of competence based on autopoiesis 37 

 

3. KNOWLEDGE IN ORGANIZATIONS 42 

3.1. Different classifications of knowledge 42 

3.2. Theoretical perspectives to knowledge management 44 

3.3. Organizations as knowledge systems 46 

3.4. Different knowledge environments 48 

3.5. Three approaches to knowledge 50 

3.5.1. Cognitivist notion of knowledge 50 

3.5.2. Connectionist notion of knowledge 51 

3.5.3. Autopoietic notion of knowledge 53 

3.6. Summary of the views of knowledge in organization 56 

 

 



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4. RESEARCH METHODOLOGIES 58 

4.1. Research approach 60 

4.2. Research design and data collection 61 

4.3. Data analysis 62 

 

5. FINDINGS 64 

5.1. Supervisor level 64 

5.1.1. The role of a function 64 

        5.1.2. The way how competence related knowledge is seen 65 

5.1.3. The way competence development is seen 66 

5.1.4. How competence is seen 67 

5.2. HR level 68 

5.2.1. The role of a function 68 

5.2.2. The way competence related knowledge is seen 69 

5.2.3. The way competence development is seen 70 

5.2.4. How competence is seen 70 

5.3. Strategic management 71 

5.3.1. The role of a function 71 

5.3.2. The way competence related knowledge is seen 72 

5.3.3. How competence development is seen 73 

5.3.4. How competence is seen 74 

5.4. Summary of the interviews 74 

 

6. CONCLUSIONS AND DISCUSSION 77 

6.1. Conclusion of the study 77 

6.2. Theoretical contribution 78 

6.3. Contribution and challenges of empirical research 79 

6.4. Future research suggestions 80 

 

REFERENCES 82 

 
 



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LIST OF TABLES AND FIGURES 

 

 

Tables 

 

Table 1. Four main systems approaches 14 

Table 2. Different paradigms on systems 15 

Table 3. Characteristics of autopoietic system based on literature 24 

Table 4. Knowledge types and their uses 44 

Table 5. Living environments of knowledge 48 

Table 6. Role of cognition in cognitivist and connectionist epistemology 52 

Table 7. Three different organizational epistemolgies 56 

Table 8. Summary of the knowledge epistemologies 58 

Table 9. The framework for empirical research 59 

Table 10. Respondents 61 

Table 11. Overall 76 

 

 

Figures        

 

Figure 1. Self-organization in social systems  22 

Figure 2. Key features of autopoietic system 26 

Figure 3. A systems autopoietice nature 27 

Figure 4. Firm as an open system 34 

Figure 5. Context for human resource scalability based on self-organization  36 

Figure 6. Sensory function, memory function and boundary elements  

and their contents  38 

 

 

 

 

 

 

 

 

 

 

 



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UNIVERSITY OF VAASA 
Faculty of Business Studies 
Author:    Timo-Pekka Uotila 
Topic of the Thesis: Epistemologies of competence related know-

ledge – a system theoretical analysis 
Name of Supervisor:   Riitta Viitala 
Degree: Master of Science in Economics and Business 

Adminstration 
Department:    Department of Management 
Major Subject:   Human Resources Management 
Year of Entering the University 2004 
Year of Completing the Thesis 2010         Pages: 91 

 
ABSTRACT 
 
The purpose of this study is to examine the multiple views of knowledge and compe-
tence in organizations at different levels that cause indistinctness in competence man-
agement and to find out how competence related knowledge is achieved at different 
organizational levels. The objective is thus to bring underlying epistemologies of 
knowledge and competence into the academic discussion and further examine how 
they are expressed in practice. 
 
In the theoretical part of this study system theories and their use in management and 
organizational studies are examined. Open-system, connectivist and autopoietic ap-
proaches are clarified and their theoretical implications in organizational studies are 
presented. Also, the role of knowledge and its management in organizations is dis-
cussed, the vast field of knowledge management is presented and cognitivist, connec-
tionist and autopoietic ways to conceptualize knowledge are considered. After a theo-
retical review a theoretical construct was formed and empirical findings were com-
pared to it. This study was carried out in four Finnish companies and 11 persons from 
different organizational levels were interviewed in summer 2009. The methodology of 
this study is qualitative and empirical data was collected by using semi–structured 
interviews. In the analyzing phase the transcripts were carefully read, coded and fur-
ther analyzed.  
  
As a result of this study different approaches to knowledge and competence could be 
found in different organizational levels. The supervisor level was found to achieve 
knowledge in everyday work in own unit. The HR level acted as a bridge builder in 
organizations and gathered knowledge through networking. The strategic manage-
ment level created knowledge in strategy making process and focused on strategic 
competences. These findings were compared to the formed theoretical construct. 
Some distinctions could be made, autopoietic, connetionist and cognitivist characte-
ristics were all found in the examined functions, but more research in the area is 
needed and thus future research suggestions are presented. 
 
 

 
KEYWORDS: Epistemology, knowledge, competence, system, autopoiesis, com-
plexity

 



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9 

 

1. INTRODUCTION 

 

As we continue living in a society where knowledge plays increasingly big role (see for 

example De Geus 1997: 15–21), organizations struggle to excel in every level, from 

strategic management to individual employee. Competences in these levels are built on 

knowledge, and use of this knowledge forms the basis of the organizational system. As 

many past approaches to knowledge and competence are focused on a narrow area, sys-

tem theories take a different position and approach phenomenon from a holistic angle. 

However, understanding of knowledge differs between individuals and organizations, 

which makes competence building and developing difficult. Theories of organizations 

and management are based on different assumptions which affect on how we see organ-

izations and knowledge. Thus, understanding different ways to see organizations helps 

us to overcome the problems caused by different views. It is said that dealing with com-

peting viewpoints is one of the key competencies that needs to be developed as a basis 

for effective management (Morgan 1997: 8). 

 

Underlying assumptions can be examined with the aid of the concept of epistemology. 

The word epistemology comes from the Greek words episteme (knowledge) and logos 

(theory). This theory of knowledge deals with the questions of how individuals come to 

achieve meaning and thereby knowledge about the reality in which they live, how is this 

knowledge constituted and under what conditions can the knowledge achieved be 

claimed as true (Sandberg 2005: 48). In organizational setting, epistemology affects on 

our understanding of characteristics of management and organizational studies and af-

fects on how we see different processes and phenomena studied in the fields of strategic 

management and organizations (Von Krogh & Roos 1995: 7–8). Organizational episte-

mology can be interpreted to be constituted by following set of perspectives, theories 

and concepts related to following issues (Von Krogh & Roos 1995: 10): 

 

1. How and why individuals within organizations come to know? 

2. How and why organizations, as social entities, come to know? 

3. What counts for knowledge of the individual and the organization? 

4. What are the impediments to organizational knowledge development? 

 

Many theories, models and concepts have been created in order to describe the nature, 

structure and the way of behavior of organizations that have been more successful than 



10 

 

others. Competence, capabilities, intangible assets and knowledge are some of the key 

concepts that have been presented as the main factors in creation of competitive advan-

tage and different lines of strategic thought have derived from those concepts. Depend-

ing on the underlying assumptions of researchers and practitioners, the focus of these 

different streams has altered.  

 

The new winds in the field of systems theory may provide solution for the disconnec-

tedness of these management and organization theories. For example Löfsted (2001) 

examined eight research papers about competence development in organizations and 

found out that systemic models, methods and approaches can provide new insights in 

the field of competence development in SMEs. Sundberg (2001) states that it is imposs-

ible to affect directly into one’s individual competence, it is only possible to offer tools 

and environment and act as a catalyst, and presents a holistic and systemic approach to 

competence development. Paucar-Caceres and Pagano (2009) compared systems think-

ing and different system methodologies articles to articles in the area of knowledge 

management and concluded that they seem to share similar conceptual grounds and the 

dialogue between these two management fields enrich each other. McElroy (2000) 

states that communities of knowledge management, organizational learning and systems 

thinking, and complexity theory are getting closer to each other, and each of those 

groups has something to offer that the other two need. Finally, Luoma (2006) has stu-

died internal dynamics of organizations and presents a framework for management de-

velopment from complex adaptive systems point of view, and concludes that it offers a 

rich foundation for management development, without forgetting older management 

theories and ideas. 

 

System approaches offer holistic views of organizations, which encompass all the dif-

ferent functions, processes, people and their relationships. As the role of knowledge in 

organizations increases constantly, new system theories are presented to complement 

the older ones. The theory of complex adaptive systems derived from the studies of hu-

man brain and artificial intelligence, or the theory of autopoiesis, general systems theory 

based on the studies of cellular life, emphasize the role of knowledge and learning and 

can be proven to be useful.  

 

So it is presented (Venzin, Von Krogh & Roos 1998: 36) that different personal episte-

mologies affect how we categorize knowledge and there are three reasons why episte-

mological assumptions should be discussed: to match epistemological assumptions to 

practices in organizations, to understand different epistemologies which rise from dif-



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ferent contexts and the ability to recognize different epistemologies facilitates us to 

choose and apply the most appropriate one. Further, authors provide three different epis-

temologies based on the works of Varela, Thompson and Rosch (1991) and Von Krogh 

and Roos (1995). These epistemologies, cognitivist, connectionist and autopoietic will 

be discussed later. Even if this distinction between different epistemologies is not al-

ways easy to make, it still provides a tool for understanding the differences. 

 

 

1.1. Research problem 

 

Multiple views of knowledge and competence in organizations in different levels cause 

indistinctness in competence management. The contribution of this study is to provide 

clarity of different epistemologies in the most important functions in the organizations 

from competence and knowledge management perspective. Moreover, the purpose of 

this study is to find out how competence related knowledge is achieved in different or-

ganizational levels. 

 

The main research question in this study is:  

 

(1) How and why the most important actors in organization’s competence 

management system come to know? 

 

The following minor questions are presented in order to reach the conclusion for the 

main question: 

 

• How organization is understood in the context of competence management from 

the perspective of system theories? 

 

• How competence is understood in organizations? 

 

 

1.2. The structure of the study 

 

The first chapter gives background information for the study by presenting the study 

subject. Previous literature from the researched area is also presented briefly. Research 

problem is defined more specifically and overlook for the study is presented. Second 

chapter examines organizations as a system. It provides an overview of systems litera-



12 

 

ture and clarifies the systems thinking movement. The purpose of this chapter is to clari-

fy the basic assumptions on which different views of organizational competence sys-

tems are built. In chapter three, knowledge and its meaning for organizations are dis-

cussed. In chapter four research methods and the process of data analysis are presented. 

Respondents are also introduced. Chapter five presents the findings of this research and 

in chapter six conclusion of this study is presented, contribution of the study are ex-

amined and future research propositions are suggested. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



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2. ORGANIZATION AS A SYSTEM – THEORETICAL PERSPECTI VES 

 

Systems theories started their development around year 1950. A push for this movement 

was the publication of important papers in the areas of systems of control, the develop-

ment of computer language and cognitivism. As attention previously was in understand-

ing parts of which system was composed, now it shifted to interaction of subsystems 

which formed system. The new theories took three main currents: general systems 

theory, cybernetics and systems dynamics. Engineers developed further cybernetics and 

systems dynamics, whereas biologists were more interested in biological control me-

chanisms and developed general systems theory. These streams are the basis of the cur-

rent dominant management discourse, especially cybernetics. (Stacey, Griffin & Shaw 

2000: 64.)  

 

From the 1950s to 1970s systems thinking achieved the position where it was the most 

important influence to management sciences. There was a wide consensus in the field of 

practitioners and scientists about what system consisted of. However, systems thinking 

was dominated by positivistic and functionalistic characteristics view of systems, so in 

70s and 80s it became a target for increasing criticism from practitioners and theorists. 

(Jackson 2000: 3.)  

 

For example, Katz and Kahn’s (1966) social psychology of organizations’ presented 

organizations as open systems, taking general system’s theory as their starting point. 

Kast and Rosenzweig (1974) presented an open system approach to management and 

Lippit (1982) took a systems approach to organizational renewal. Further, especially 

sociology and organization theory were areas where critique against hard systems think-

ing rose. So, in 1980s new approaches were born, such as soft systems thinking and 

critical systems thinking, which were contradictory against the more traditional system 

theories (Jackson 2000: 3). In 1990s systems thinking got a new start: chaos and com-

plexity theories became popularized, Senge’s Fifth discipline, based on systems dynam-

ics, acted as an igniter of learning organization stream and Luhmann’s interpretation of 

Maturana and Varela’s concept of autopoiesis got more attention in areas such as family 

therapy, sociology and  law (Jackson 2000: 4). 

 

Jackson (2000) presents four main systems approaches in prevailing literature. Functio-

nalist system approach is interested in the relationships and laws that govern systems 

parts and subparts. By using the methods taken from natural sciences, these systems can 

be optimized to adapt and to survive. However, epistemologies differ among functional-



14 

 

ists (Jackson 2000: 107).  Some take positivist position and claim that empirical obser-

vation of the system reveals the laws between systems parts governing its behavior. 

Others take structuralist view and say that it is necessary to describe processes and 

structures at deeper level because these are the ones that causally create the observable 

phenomena. Hard systems thinking, system dynamics (Senge), organizational cybernet-

ics (Beer), living systems theory, autopoiesis and complexity theory are streams derived 

from this line of thought. The interpretive systems approach, (Jackson 2000: 211–290) 

commonly referred as soft systems thinking, focuses on people instead of technology, 

structure and organization. Its primary area of concern is perceptions, values, beliefs 

and interests. It accepts that there are many perceptions of reality which can cause con-

flicts, and tries to offer solutions, methodologies, methods, models and techniques for 

these kinds of problems professionals face at work. Interactive management (Warfield), 

social system design (Churchman), strategic assumption surfacing and testing, SAST 

(Mason & Mitroff), social system sciences, S3 (Ackoff), soft system methodology, SSM 

(Checkland), soft systems thinking (Senge) and the system of systems methodologies 

are examples of interpretative systems streams. For example Senge (1990: 73) sees the 

main idea of systems thinking in the shift of mind, seeing interrelationships rather than 

linear cause-effect chains, and seeing processes of change rather than snapshots. 

 

 

Table 1. Four main systems approaches (based on Jackson 2000). 

 Functionalist Interpretative Emancipatory Postmodern 

Focus: Relationships 

and laws that 

prevail be-

tween system’s 

parts 

Subjective  per-

ceptions, val-

ues, interests 

and beliefs 

Inequality be-

tween groups in 

society 

Ensuring di-

versity and 

emphasizing 

creativity 

 

 

The emancipatory systems (Jackson 2000: 291–329) approaches do not believe in cur-

rent social order and try radically to change it. According to this view, some groups in 

society are benefitting at the expense of other groups, which are dominated or discrimi-

nated. These groups are based on class, race, gender, sexual orientation, age, capability 

or other features. The postmodern approach (Jackson 2000: 333–357) in general seeks 

to reclaim conflict and ensure that marginalized voices are recognized and heard. It does 

this through methods like deconstruction and genealogy. As interpretive systems ap-

proach tried to seek order through accommodation and consensus, postmodern approach 



15 

 

promotes novelty and disorder. It is said that even though postmodernism and systems 

thinking are hard to fit together, they can still collaborate by using systems methods, 

techniques and models in the spirit of postmodernism, or by using tools and methods 

offered by postmodernism to assist systems practitioners (Jackson 2000: 335). 

 

Mingers (1997) states that different methodologies in organizational problem solving 

and intervention that have mainly been developed in the domains of operational re-

search (OR), systems thinking and information systems, are implicitly or explicitly 

based on particular philosophical assumptions of the nature of organizational world and 

appropriateness of various forms of action. These paradigms can be divided into hard 

(positivist), treating world as an objective reality, soft (interpretivist) focusing on the 

meaning and interpretations of human organizations and critical, accepting both soft and 

hard methodologies but emphasizing the oppressive and inequitable nature of social 

systems. (Mingers 1997: 1–2.) 

  

Ståhle (1998: 42–43) makes a different distinction between systems and has found three 

paradigms on which different streams of systems thinking are based. First paradigm 

concerns closed, mechanistic systems, and its aim is to “explain and define natural laws 

and principles and predict events conforming to the formulated theories”. Its roots are 

in mechanistic, Newtonian perspective and for example early cybernetics can be put in 

this class. Second paradigm concerns open systems and the main focus is on the rela-

tionships and interactions with their environment. Equilibrium, a stable state of system 

is considered ideal. Theories derived from general systems theory go in this category, 

although some advanced views show features that belong to the third paradigm. Third 

paradigm focuses on internal or spontaneous dynamics of systems and it is based on 

Edward Lorenz’s work on chaos and it has similarities to complexity research. Also, 

Ilya Prigogine’s work on self-organization and Maturana and Varela’s work on auto-

poietic systems are one of the greatest theoretical contributors to this paradigm. Further, 

concepts such as discontinuity, non-determinism and non-locality from quantum phys-

ics offer some theoretical insights.  

 

 

Table 2. Different paradigms on systems (Ståhle 1998: 43). 

Paradigm Originator Type of system Research in-

terest 

Operative in-

terest 

1.closed sys-

tems 

NEWTON Static  

Deterministic 

PRINCIPLES 

LAWS 

Predicting 

Controlling 



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Mechanistic 

2.Open sys-

tems 

von BERTA-

LANFFLY 

Near equili-

brium 

Equifinal 

Living 

FEEDBACK 

PROCESSES 

Steering  

Sustaining 

3.Dynamic sys-

tems 

LORENZ 

PRIGOGINE 

MATURANA 

VARELA 

Far-from-

equilibrium 

Uncontrollable 

Emerging 

SPONTANEOUS 

ORGANIZATION 

 

Understanding 

and cooperat-

ing with natu-

ral environ-

ment 

 

 

Ståhle (1998: 44) continues by saying that depending on paradigm the starting points 

and focus on research are distinctively different and the unclear identification on which 

paradigm research is based causes obscurity and confusion. Moreover, she concludes 

that as area of systems research has grown so large, some identification is necessary 

based on the purpose of research. None of the above mentioned paradigms are not nec-

essarily contradictory, they just provide different dimensions and characteristic of sys-

tem.  

 

Depending on the system school, a system can be defined in many ways. Skyttner 

(1996) presents some definitions found on literature, such as Weiss’s “a system is any-

thing unitary enough to deserve a name”, Boulding’s “a system is anything that is not 

chaos” and Churchman’s “a structure that has organized components”, frequently used 

common sense definition “a system is a set of interacting units or elements that form an 

integrated whole intended to perform some function” and Ackoff’s ”a system is a set of 

two or more elements that satisfies following conditions: the behavior of each element 

has an effect on the behavior of the whole, the behavior of the elements and their effects 

on the whole are interdependent, and however subgroups of the elements are formed, 

all have an effect on the behavior of the whole but none has an independent effect on it” 

 

It can be said that systems exist everywhere. Boulding (1956) has described the hie-

rarchy of systems according to their complexity; 1. framework of static structure, 2. the 

clockworks of physics and astronomy, 3. the control mechanism or cybernetic system, 

4. the cell or self-maintaining structure, 5. the genetic or plant level, 6. the animal level 

with purposive behavior and self-awareness, 7. the human level, and 8. social organiza-

tion or individuals in roles. The idea of this classification is that phenomena that are 



17 

 

explained become more complex at each level. Boulding believes that adequate theoret-

ical models have been developed only for the first four levels and their analogical use to 

higher level phenomena is problematic. (Katz & Kahn 1978: 8; Magalhaes 1998: 93.) 

 

Lately dynamic or complex systems have gained a lot of attention. Different areas of 

science have used complex systems in their theory formation. For example, Arthur (Ar-

thur, Durlauf & Lane 1997; Arthur 1996; Arthur 1999) speaks about economy as an 

evolving complex system and states that traditional economic theories search equili-

brium, whereas theorists with complexity perspective broaden this view by focusing on 

the question of how actions, strategies or expectations might react in general, and endo-

genously change with the aggregate patterns these create. Further, Arthur (1996) speaks 

about the phenomena of positive feedback and increasing returns. Ilya Prigogine worked 

on the area of chemistry and physics and he was focused on chemical processes and 

systems, and eventually considered how his findings of self-organization could be ap-

plied to social systems (Ståhle 1998: 47–48). Booker, Forrest, Mitchell and Riolo (2005: 

3) state that genetic algorithm, which has played an important role for researchers of 

complex adaptive systems was developed by John Holland and his works on adaptation, 

learning and modeling of both natural and artificial systems has had a fundamental im-

pact on numerous fields. Another pioneer on the field of artificial life is Chris Langton 

whose research interest is the complex system behavior and self-organization which is 

based on the simple rules of the individual agents (Baets 2004: 57). With the aid of ar-

tificial life we can try to understand the behavior of different systems, for example the 

flock of birds or bee colony. Conway’s Game of Life is one of the computer applica-

tions which simulate life, and which is based on simple rules. According to Juuti and 

Luoma (2009) with the aid of these artificial life applications we (researchers, manag-

ers) can create our own systems (organizations, populations, etc.), give different rules 

(strategies, basic values, etc.) and see how they produce different systems based on the 

feedback loops (see De Geus 1997: 66-74 for practical example in Shell Corporation). 

Thus, we can evaluate different set of rules. It follows that these applications bring us 

whole new ways to understand the systemic nature of organizations.  

 

Last, Stacey (2001, 2007) attacks quite heavily against the prevailing system theories, 

especially traditional open system theory is criticized. He claims that we should move 

from system thinking perspective to complex responsive process perspective, and we 

should abandon the assumptions of autonomous individual, position of objective ob-

server and managers as objective designers and replace them with simultaneous social 

construction of individual and group identities, methodological position of reflexivity in 



18 

 

both individual and social terms, and thinking oneself as an “active participant in com-

plex processes of relating to other people in all aspects, both good and bad” (Stacey 

2007: 441). Still, even though Stacey criticizes system thinking it should be noted that 

complex responsive process perspective has also many characteristics common espe-

cially with the newer system theories. 

 

 

2.1. The principles of an open system 

 

Traditionally systems can be seen as closed systems or open systems interacting with 

their environment. Characteristic of closed systems is tendency to move towards entro-

py, randomness and disorder. Open systems interact with their environment through 

material, information and energy flows. They adapt to their environment and prevent 

entropy by changing their structure and processes of their internal components in order 

to maintain equilibrium, the balanced state. (Kast & Rosenzweig 1974: 109.) 

 

Katz and Kahn (1978: 23–30) give ten common characteristics for open system:  

 

• it imports energy from external environment 

• throughput and transformation of input in system  

• output of the system which is exported into environment  

• systems as cycles of events  

• negative entropy  

• information input, negative feedback and the coding process 

• the steady state and dynamic homeostasis 

• differentiation 

• integration and coordination 

• equifinality 

 

Energy is imported from external environment into the system, which is then trans-

formed during the process of throughput and exported into the environment as an out-

put. Bridges built by engineering firm or carbon oxide produced by lungs are examples 

of outputs. Systems are cycles of events, for example firm selling a product receives 

money and buys new raw materials, which in turn are transformed into output products. 

This cycle of input, transformation and output is cycle of negative entropy. The tenden-

cy to move towards chaos is reversed and is crucial for the life of a system. As system 

functions, it gets information about its own actions in relation to the environment. The 



19 

 

simplest information found in all systems is negative feedback. It tells a system to cor-

rect its position to the right course. As information from environment is too complex, 

system must select what kind of information it acquires. Coding process simplifies the 

information into a few meaningful categories of a system. As there is continuous inflow 

of energy into system, it still maintains its character, the ratio between energy ex-

changes and the relations between the parts as same. Differentiation refers to the act 

where global patterns are replaced by more specialized functions. As differentiation 

proceeds, integration and coordination processes in a system make it function as one 

entity. Finally, equifinality refers to the principle that a system can reach the same final 

state through different initial conditions and through different paths. (Katz & Kahn 

1978: 28–30.) 

 

Systems are separated from their environment by their boundaries. In a closed system 

boundaries prevent any interaction with its environment, whereas in open systems 

boundaries act as a filter between system and its environment. Especially in social sys-

tems boundaries are not easily identified. A system consists of many subsystems and it 

is always a part of a larger suprasystem. Through continuous feedback mechanisms 

open system acquires information from its environment which helps it to adjust. Whe-

reas closed systems move towards entropy, open systems move to the direction of high-

er level organization and differentiation. Causality does not hold in open systems, the 

final results can be achieved through different initial conditions and in different ways 

(Kast & Rosenzweig 1974: 114–119).  

 

Organizations can be divided into smaller interconnected subsystems. Katz and Kahn 

(1978: 52–55) have recognized a production or technical subsystem, concerned with the 

work done on the throughput; a supportive subsystem, providing inputs or disposing 

outputs; a maintenance subsystem, taking care equipment, including human beings; an 

adaptive subsystem, sensing environmental changes and a managerial subsystem which 

controls, coordinates and directs other subsystems. From those, managerial subsystem 

can be divided into its own subsystems, operative, coordinative and strategic, according 

to Kast and Rosenzweig (1974: 121–122). Operating subsystem’s primary concern is 

economic-technical rationality, and it tries to create certainty by closing the central core 

to many variables. Its primary task is to accomplish objectives effectively and efficient-

ly and its focus is on short run, and its point of view is optimizing. Its general processes 

are programmable and its decision making techniques are based on quantitative, compu-

tational numbers. Strategic subsystem’s primary task is to relate organization to envi-

ronment and to design comprehensive systems and plans. It is open towards environ-



20 

 

ment and its viewpoint is to find workable solutions to complex problems. Its general 

processes are non-programmable and its decision making techniques rely on judgmental 

and cognitive reasoning. Coordinative subsystem is situated between these two and its 

primary function is to integrate internal activities. It is involved in interpreting results 

from operating subsystem and focusing existing resources in appropriate directions. The 

smaller the firm, more likely one individual has to perform in many roles.  

 

 

2.2. The principles of connectionism 

 

Connectionism is a way to see information processing, which has been inspired by the 

understanding of our brain, and it is also known as neural network -model. Cilliers 

(1999: 26) describes the function of neural network accordingly:  

 

“Functionally the nervous system consists only of neurons. These cells are 

richly interconnected by means of synapses. The synapses convey the stimu-

lation generated in a previous neuron to the dendrites of the next neuron in 

line. If this stimulation exceeds a certain threshold, the neuron is triggered 

and an impulse is sent down the axon of neuron. This impulse in turn pro-

vides the synaptic input to a number of other neurons. The information 

passed from one neuron to the next is modified by the transfer characteris-

tics of the synapses, as well as by the physical structure of the dendrites of 

the receiving neuron. Any single neuron receives inputs from, provides in-

puts to, many others. Complex patterns of neural excitation seem to be the 

basic feature of brain activity.” 

 

In the connectionist model, also known as the neural network, biological neutrons are 

divided, active cells, which are capable of complex communication with each other and 

communication and interconnections of neutrons happen in “synapses”. History of 

neural networks can be drawn from 1960s, to the studies of cybernetics and from 1970s 

to the studies of perceptrons. These neural networks process information as typical for 

living systems in dynamic and self-organizing way. Self-organization is referred to the 

ability to simultaneously learn while processing. As required amount of connections 

between a set of neutrons is acquired, spontaneous self-organization phenomena 

emerge. Further, these networks can learn to (1) recognize common pattern from large 

number of examples, (2) associate one pattern with another and (3) distinguish one pat-

tern of input from others. (Aeh 1989: 23.)  



21 

 

 

Neural networks are one possible model to describe the function of complex adaptive 

systems. There is no unified theory for complex adaptive systems, but four interesting 

elements can be recognized. First (1) are agents with schemata. In organization they can 

be individuals, groups or coalitions of groups. The behavior of each agent is dictated by 

a schema, a cognitive structure that determines the actions of the agent based on its per-

ceptions of its environment. These schemas can be different or same amongst the 

agents. Second (2) element is self-organizing network sustained by imported energy. 

Agents are partially connected to each other by feedback loops, and each agent observes 

local information only, which is derived from other agents it is connected to, and acts 

accordingly. Imported energy is a necessity for self-organization. Third (3) element is 

co-evolution to the edge of chaos. Agents are unable to foresee system level conse-

quences for their choices, so they adjust their actions to “optimize their fitness” locally. 

As other agents also make their own choices, the environment where to mirror own ac-

tion changes continually. Thus, they co-evolve with one another. Fourth (4) element is 

recombination and system evolution. This happens through entry, exit and evolvement 

of agents. The local changes affect global characteristics of system, and for example 

actions do not just happen through feedback loops, they also change these loops. (An-

derson 1999.) 

 

The learning in connectionist model can be modeled through Hebb’s rule, named after 

its inventor Donald Hebb in 1949. He stated that the relationship between two neurons 

increases depending on how often it is used. If two neurons are active simultaneously, it 

increases the strength of their interconnection. This makes network to develop an inter-

nal structure, based only on the local information each neuron receives, which can be 

called learning. (Cilliers 1999: 17.) 

 

Cilliers (1999: viii–ix) makes a distinction between complicated systems and complex 

systems. If it is possible to give a full description of the parts of which a system con-

sists, it is considered complicated system. Computers and jumbo jets are given as an 

example. If the systems parts are interconnected with each other and with the environ-

ment and it cannot be analyzed by focusing only on its parts, system is considered com-

plex. The brain, natural language and social systems are given as examples. Dynamics 

of self-organization can be seen as general property of complex systems (Cilliers 1999: 

90). 

 



22 

 

Social self-organization happens in social system where the active human beings are 

components. Human actions are the basis of the social systems, and by the interaction of 

human actors new social qualities and structures can emerge, which are irreducible to 

individual level. This process of bottom-up emergence is called agency. In practice it 

means that at least one systemic quality that cannot be divided to its elements. Social 

structures also influence individual acting and thinking. They enable and constrain ac-

tions. This process is top-down emergence, where new group and individual properties 

can emerge. This circular process is a systemic societal self-organization. “Societal 

structures enable and constrain actions as well as individuality and are result of social 

actions (which are emergent result of connected individualities)”. (Fuchs & Hofkir-

chner 2005: 245.)  

 

 

           structures  

 

            agency    SOCIAL SELF-     constraining  

     ORGANIZATION    and enabling  

 

            actors  

 

Figure 1. Self-organization in social systems (Fuchs & Hofkirchner 2005: 245). 

 

 

Nobel prize winner, physical chemist Ilya Prigogine offers another view to self-

organization. Ståhle (1998) has studied the system’s capacity to self-renewal, and used 

the vast work of Prigogine, starting from the 60s and 70s as one of its corner stones, and 

has concluded five principal features of self organization. First concept is state of far-

from equilibrium. It is this state where system is able to self-organize, create order out 

of chaos. In practice this means that (1) contradictory conditions exist inside the system, 

for example opposing viewpoints in social system or (2) forceful fluctuations are taking 

place inside the system, for example in social system new information can cause system 

to move far-from equilibrium. Second concept is entropy, which signifies the kind of 

energy (or information) that cannot be utilized by the system. In order to self-organize 

the system must be able to produce entropy in order to reach the state of chaos and to 

dissipate entropy to yet again self-organize. In social system this could mean obtaining 

information without making interpretations and tolerating confusion and finally making 

decisions making priorities, focusing and abandoning the un-necessities. Third concept 



23 

 

is iteration, continuous, extremely sensitive feedback process. It enables system to form 

an existing pattern again and again. This feedback could be termed resonance as the 

word describes it better, it is that sensitive, and processes include both negative and pos-

itive feedbacks, which reciprocally support and obscure growth. Further, iteration pro-

vides the spontaneity to organization. In social system, more receptive the members are 

and react to environment and each other, more sensitive the system becomes. Fourth 

concept is bifurcation, which includes three characteristics: there are certain times in 

systems life when it can make genuine choices, these decisions cannot be predicted in 

advance and the choices made are irreversible. Fifth concept is constructive role of time, 

as system creates its own history as it moves from one bifurcation point to another. 

(Ståhle 1998: 51–67.) 

 

 

2.3. The principles of an autopoietic system 

 

Another way to view system and alternative to connectionist and open system view is 

the theory of autopoiesis, created by Maturana and Varela in the early 70s, which was 

developed to characterize the organization of living systems (Jackson 2007: 79). Von 

Krogh and Roos (1995: 34) state that this approach was a reaction against the prevailing 

reductionist method in natural sciences and especially in molecular biology. Reduction-

ist methods were used in dividing complex systems to always smaller parts, until it was 

possible to focus to one small component, for example on DNA and its elements. Auto-

poietic view focuses on cooperative relations of the whole cellular system instead. Ac-

cording to Varela et al. (1974), to be considered autopoietic following conditions must 

be met (Hall 2005; Jackson 2007):  

 

1. The system must have a boundary 

2. The components of a system are determined by the system.  

3. The system has dynamic nature. It determines the interactions and transforma-

tion of  its components 

4. The system dynamically maintains its identity. System processes work to main-

tain the integrity of the system 

5. System produces its own components. Components from internal or external en-

vironment are transformed by system processes to make them functionally and 

identifiably parts of the system 

6.  The produced components must be sufficient to produce the system. 

 



24 

 

Luisi (2002: 159) composes the requirements and refers to Varela (2000), and suggests 

that three criteria must be met: system has to have semipermeable boundary, which is 

produced within the system, which encompasses reactions that regenerate the compo-

nents of system. Jackson (2007: 79) clarifies the concept of autopoiesis using the dis-

tinction made famous by Maturana and Varela. He divides systems to allopoietic and 

autopoietic. Allopoietic machine produces something else than itself in its process of 

production. A blender, computer and a light bulb are given as examples. Autopoietic 

system on the other hand produces itself, and self-production is its only action. It can be 

said that autopoietic systems are thus purposeless (Jackson 2007: 79). 

 

 

Table 3. Characteristics of autopoietic system based on literature (Maula 1999: 82). 

CHARACTERISTIC DEFINITION 

Organization The relations between components and the necessary proper-

ties of the components that define the unity as a whole, and 

thereby its identity, type or class 

Structure The set of actual components belonging to a particular con-

crete example or instance 

Triggers Signals, treated only as perturbations, not as an input to the 

system 

Structural coupling Reciprocal interaction (mutual relationship or correspondence) 

with the environment. History of recurrent interactions leading 

to the structural congruence. 

Interactive open-

ness 

The system interacts with the environment and compensates 

the perturbations by improving knowledge (distinctions) and 

changing its structure 

Organizational clo-

sure 

Any change in the system is a structural change. The product of 

the transformation is the very organization itself.  

Self-referentiality 1. Accumulated knowledge affects the structure and op-

eration of system 

2. The system affects the (creation of) new knowledge 

Autopoiesis A system produces its own components and renews itself in a 

way that allows the continuous maintenance of the integrity of 

the structure. 

Identity • Being composed of components and their relationships. 

• Being distinguishable from other unities 

Social coupling Reciprocal interaction (communication) using language 



25 

 

All autopoietic systems have an organization and structure (Stacey 2001: 237). Organi-

zation (identity) describes the system; it is an abstract concept of the nature of compo-

nents and their relations between them that are required in order to system fit in certain 

category or type. It can be seen as the dynamics of interaction within the system, the 

context within which the components interact. Structure is the concrete operations of 

system, the arrangement of systems components in order to maintain its identity. Von 

Krogh and Roos (1995: 35) present the difference between organization and structure by 

using the words of Varela (1984: 25), who defines organization and structure as follows: 

“… its organization which are the necessary relations which define the system and its 

structure, which are the actual relations between the components which integrate the 

system as such. Thus ex-definitione, the organization is invariant while a system main-

tains its identity without disintegration; structures can vary provided they satisfy the 

organizational constraints.”  

 

Further, Stacey (2001: 237) states that autopoietic systems are organizationally (opera-

tionally) closed. Thus, system can import material, energy and information and export 

waste, but its organization (identity of system) cannot be changed from outside. Only 

operations inside system can change its organization. This does not mean that system is 

closed, it communicates with its environment and other systems, but they can only trig-

ger internal changes in system. It follows that as the environment can never determine, 

direct or control changes in a system, autopoietic system knows its environment in 

knowing itself (Von Krogh & Roos 1995: 38). It can be said that autopoietic systems 

are self-referential because they cannot enter into interactions that are not specified in 

the pattern of relations that define their organization, so its environment is really a ref-

lection and part of its own organization (Morgan 1997: 254). Thus, autopoietic systems 

are autonomous, which in this case means that they maintain their identity. System pro-

duces its own components, and the rules of functioning are coded in its organization and 

the way it reproduces itself (Von Krogh & Roos 1995: 37). Mingers (1995: 10) explains 

it (in Stacey 2001: 237): “Maturana and Varela pick out the single, biological individu-

al (for example a single-celled creature such as amoeba) as the central example of a 

living system. One essential feature of such living entities is their individual autonomy. 

Although they are part of organisms, populations, and species and are affected by their 

environment, individuals are bounded, self-defined entities.”  

 

Structural coupling is one of the characteristics of autopoietic system. The basic auto-

poietic entity is a cell. When many autopoietic entities become structurally coupled, 

they can create multicellural entities.  Further, these second order autopoietic entities 



26 

 

usually develop a nervous system and it becomes possible for them to interact with oth-

er beings, more deeply than mere perturbations. These interactions are often termed 

social phenomena, and the emergence of social systems which exhibit social phenomena 

become third order entities. (Parboteeah & Jackson 2007: 251.) 

 

In other words (Stacey 2001: 237), autopoietic systems are structural coupled with their 

environment and other systems. System is not dependent on environmental changes, but 

rather its own operations/identity/operational processes define the structural shape it 

takes. However, in case autopoietic entity loses its identity, it dies.  

 

Self-referentiality is also one of the characteristics of an autopoietic entity (Maula 1999: 

80). It means that (1) accumulated knowledge affects the system’s structure and opera-

tion and (2) system affects the creation and acquisition of new data. Knowledge that is 

formed from that data is dependent from system’s interpretation structure. As a conse-

quence, system’s environment becomes internalized. Ståhle (1998: 79) also explains 

self-referentiality and refers to Varela which states that the one who designates the bor-

ders of system actually belongs to system and specifies the boarders of the system ac-

cording to own needs and viewpoints. Moreover, she concludes that the logic of self-

referentality can be stated as “what we see is always a reflection what we are”. 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2. Key features of autopoietic system (Gregory 2006: 964). 

 

 

As autopoietic system is not accessible to anything except the system itself, it is only 

open to observation. Thus, all characteristics can be only given from the viewpoint of an 

observer. There are two ways to observe autopoietic system: focusing on its internal 



27 

 

self-
reference

the 
systems 

being
interaction

structure or focusing on its environment. In former case environment is seen only as a 

background and system properties emerge from the interaction of its components. In 

latter case system is seen as simple entity with certain interaction with its environment. 

This causes the problem of controlling the system’s behavior. As it is, the observation 

itself is an operation of an autopoietic system. (Von Krogh & Roos 1995: 40.) 

 

“…it is we who observe the event. The leaf, the wind, the frog, and the shadows are all 

part of our experience, and the events we describe, as well the differences between 

them, are the results of the relations we have established between parts of our expe-

rience … we cannot step outside [our cognitive domain] and see ourselves as a unit in 

an environment … what the observer now takes to be his own environment is still part 

of his experience and by no means lies beyond the interface that is supposed to separate 

the knower from the world he gets to know” (Varela 1979: 273–274 cited as in Von 

Krogh & Roos 1995: 34).  

 

 

 

 

 

 

 

 

   

Is not possible without    Always influences how

        one perceives  

  

 

 

 

 

          Is demonstrated in 

 

Figure 3. A systems autopoietice nature (Ståhle 1998: 81). 

 

 

According to Mingers (1990), the philosophical foundations of autopoietic theory can 

be found from the area of critical realism, which accepts the structural-determined na-



28 

 

ture of individual’s nervous system and thus accepts the limits on the access of external 

reality that an individual has (Kay 2001: 469). Maula (1999: 105–118) has studied fur-

ther the philosophical basis of autopoiesis theory, and found that the philosophical posi-

tioning is not necessarily easy. Maula (1999: 105–118) concluded that options are that 

autopoiesis theory can be interpreted within the critical realist paradigm, it can be asso-

ciated with phenomenological constructionism, its positioning is left open until the 

theories develop, it is regarded as independent and separate philosophical paradigm or it 

is seen as neutral meta-philosophy, which can be used to view old paradigms in a new 

way.  

 

Autopoietic systems approach is in summary, focused on autonomy realized through the 

process of self-production, production of feasible responses to perturbations, structural 

coupling between systems and how systems persist and maintain identity despite 

changes in components and structure. (Gregory 2006: 964.) 

 

 

2.4. Competence system of organization 

 

In this chapter different views to understand competence are studied. Moreover, pre-

viously presented system-theoretical frameworks are reflected to contemporary theories 

of competence. Further, some theoretical implications found in the literature of man-

agement and organizations are provided. Sanchez’s model (2004) is chosen for a first 

examined frame, as it tries to understand competence in organization at different levels. 

This model for organizational competence defines competence in dynamic, systemic, 

cognitive and holistic terms. Further, its open system view incorporates interactions 

between organization’s assets (capabilities and skills included), management processes 

and its strategic logic for using assets in order to reach its goals (Sanchez 2004: 519). 

Other framework is offered by Dyer and Ericksen (2005), whose framework is based on 

self-organization. Last, some alternative frameworks are provided which are based on 

autopoietic notion of systems. 

 

2.4.1. Competence in different levels 

 

The term competence is used widely in business literature. However, there are many 

overlapping ways to view the concept. At least following approaches and concepts re-

lated to competence and its management have been found in literature: learning organi-

zation, intellectual capital movement, knowledge management, individual or employee 



29 

 

competence, core competence, capabilities based competition, competence-based stra-

tegic management, dynamic capabilities and absorptive capacity (Hong & Ståhle 2005; 

Laakso-Manninen & Viitala 2007). As competence management literature encompasses 

a vast scale of literature, many authors have developed the field of competence man-

agement from different angles. Especially the end of 20th century was productive time 

for this movement. Among the terms “knowledge society” and “organizational learn-

ing”, resource-based approach gained attention. This view sees organizations’ resources 

and capabilities as the basis for competitive advantage. The roots of this view derived 

from Penrose’s (1966) theory of the firm. Main proponent’s for this movement were 

Prahalad and Hamel (1990) as they presented their core competence theory, Stalk, 

Evans & Schulman (1992) with their capabilities based competition and Teece, Piscano 

and Shuen (1997) with their dynamic capabilities theory. The common factor for all 

these concepts and approaches was to focus on the competence of organization. Since 

then, many approaches have molded the field from different points of view. Only em-

phasis differs. Some approaches take individual as a starting point, where as other side 

starts from organization level. The problem with many approaches to competence is that 

as they focus deeply on certain dimension, they neglect the other dimensions, which 

causes troubles in the real world setting.  

 

Crossan and Bedrow (2003: 1088–1089) state that research on organizational learning 

has been largely disconnected from strategy, because of too narrow conceptualization, 

failure to address the fundamental tension between exploration and exploitation, and 

lack of practical testing. The need of more holistic model is noted, and for example 

Spanos and Prastacos (2004) provide an integrating framework for organizational capa-

bilities, where human actors, their skills and knowledge are constituents of competence, 

and capabilities are seen socially constructed entities that weave organization’s assets, 

particularly human capital, together. Bontis, Crossan and Hulland (2002) suggest that 

firms might be over investing in the development of individual competencies and capa-

bilities and under investing in mechanisms that facilitate the flow of learning between 

individual, group and organizational levels. They continue by claiming that the dynamic 

interplay between these levels and processes has positive relationship to business per-

formance. 

 

Moreover, competence discussion should be examined from different levels. At the in-

dividual level concept of competence has some different interpretations. Håland and 

Tjora (2006), following Garavan and McGuire (2001), Hoyrup and Petersen (2003) and 

Sandberg (2000), have gathered two principal perspectives on competence in the com-



30 

 

petence management literature. The two principal perspectives they found were the ra-

tionalistic and positivistic perspective and the phenomenological-, humanistic-, and 

social constructivist perspective. Håland and Troja (2006) refer to Hoyrup and Pedersen 

(2003), who have identified two different views of competence. The first one is the ra-

tionalist, positivistic paradigm, where competence development means maximizing 

workers’ total work abilities. The purpose is to increase profit by developing individual 

workers’ competencies through learning. In this view, competence is seen as a context-

free, individual characteristic. The second one is humanistic, phenomenological and 

social constructivist paradigm, where competence is seen as relations and work life is 

meant to support workers’ independence and experience of work life as meaningful. 

Further, according to Garavan and McGuire (2001: 146–147) there are philosophical 

and epistemological tensions behind the different perspectives on competence. The ma-

jority of competency literature provides a rationalistic and positivistic perspective, in 

which competence is seen as attributes-based, context-independent, atomistic, mecha-

nistic and bureaucratic. Phenomenological approach is presented as an alternative. It 

suggests that the internal organizational context and the role of the employee and his 

experience at work should be emphasized. Finally, Sandberg (2000) divides discussion 

on competence into rationalistic approach, where human competence at work is based 

on a set of attributes, and into interpretative approach, where competence is understood 

as constituted workers’ experience of work. 

 

On the organizational level, definitions and angles to study competence also differ. Co-

hen and Levinthal (1990) studied organizations’ capability to recognize, assimilate and 

use external information, which they labeled absorptive capability. Nordhaug and Gron-

haug (1994) examined how individual competences and collective competences act as 

an organizational resource. Leonard-Barton (1992, 1995) used the term core capabilities 

and core rigidities. She pointed out that core capabilities can turn into core rigidities. 

Long and Vickers-Koch (1995) presented their view, where two kinds of capabilities 

were presented, starting from threshold capabilities, necessary to “be in the game”, like 

services for internal customer and skills and systems needed doing business in organiza-

tion’s industry and core capabilities which were further divided into critical core capa-

bilities, which create competitive advantage at the moment, and to cutting edge core 

capabilities, which provide competitive advantage in the future. Drejer (2000) composes 

competence from four elements: (hard) technology, tools that the human beings use to 

do activities, including machinery, software systems, databases, tools and so on, human 

beings, essential part of competence, organization, formal managerial system under 

which human beings functions including planning and control systems, reward systems, 



31 

 

information channels, hierarchy of responsibilities and other formal organization ma-

nifestations which affect human behavior, and finally culture, the informal organization 

of the firm, including shared values and norms, which guide human actions.  

 

According to Viitala (2005: 175) the infrastructure for competence management con-

sists of the following things: 

 

• planning and follow-up system ( quality and quantity of competence) 

• competence development system (familiarization, development discussions, 

competence mappings, human resources development and work community de-

velopment) 

• supporting HR functions for competence (recruiting, hiring, career planning, 

well-being, employment) 

• knowledge management and knowledge systems 

• organizational structure and task organization 

• operations models and practices supporting learning 

• management of competence risks 

 

These elements build a competence management system. Moreover, sustaining the 

competence level the organization needs, and developing it even further requires archi-

tecture which supports competence development and usability. It is common that only 

some of these elements are included in organization’s competence management system. 

However, in the ensemble these elements support each other and develop according to 

organizations strategic goals. (Viitala 2005: 175.) 

 

Drejer (2000) continues by proposing distinction between the competences based on 

their complexity level. First competence type is a situation with a single technology and 

a few people, and the competence is rather easy to identify. The second type consists of 

interwoven technologies in a larger organizational unit. This may require different ca-

pabilities to work efficiently, and organizational structure and processes are necessary 

for the coordinated use and interplay of the various technologies. The third type consists 

of complex systems connecting many persons in different departments and organiza-

tional units. This kind of competence is at the heart of the competitive strength of a 

company – it is complex, more difficult to imitate and less dependent on technolo-

gy/more dependent on knowledge. Naturally, it is difficult to identify this kind of know-

ledge. This complex type of competence builds on organizations quality management 

system, production management, system tacit knowledge of individual employees inte-



32 

 

racting collectively and attitude and organizational culture of the company, to name a 

few. None of these three types of competences should be viewed as static entities, but as 

always developing. 

 

2.4.2. Open system view to competence management 

 

Sanchez (1997, 2001, 2004; Sanchez & Heene 1996, 2004) offers a holistic approach, 

where competence can be seen as “the ability to sustain coordinated deployment of as-

sets in ways that help a firm achieve its goals” (Sanchez 2004: 521). Five modes of 

competences can be identified, which lead to organizational flexibility, and which pro-

vide different strategic options. These competence modes are cognitive flexibility to 

define alternative strategic logics, cognitive flexibility to define alternative management 

processes, coordination flexibility to identify, configure and deploy resources, resource 

flexibility to be used in alternative operations, and operating flexibility in applying 

skills and capabilities in uses of available resources (Sanchez 2004).  

 

According to Sanchez (2004), the first competence mode describes organizations’ cog-

nitive flexibility to think alternative solutions to create value in markets. The main 

source of this mode of competence is the collective corporate imagination, organiza-

tion’s managers’ ability to see different ways to create value to markets. Usually compe-

tence mode one resides with the strategic managers, who have power to act as visionary 

leaders or power to withhold the breakthrough of new ideas. Bove, Harmsen and Gru-

nert (2000: 37) found out that it is important to look holistically at those strategic com-

petences, instead of focusing on single competence that is thought to be basis for a suc-

cess without reference to other competences, as they are intertwined and form a com-

plex web within they support and suppress each others. Second competence mode re-

sults also from cognitive flexibility of managers to bring forth alternative management 

processes in order to implement strategic logics identified by competence mode number 

one. This competence mode consists of managers’ abilities to identify required re-

sources (assets, knowledge, capabilities) to carry out current strategic logic, to create 

effective organizational designs (allocation of tasks, decision making, information 

flows) for processes using required resources and to define controls and incentives for 

monitoring and motivating value creating processes that follow current strategic logic.  

 

Third competence mode builds on coordination flexibility to identify, configure and 

deployment of resources. Managers have to define the ways that created value is distri-

buted across the organization and attract best providers of those resources, which can be 



33 

 

found inside or outside the firm. Configuring of processes means defining activities that 

are most effective, when used just identified resources, and designing a way those activ-

ities interact with processes. To deploy a resource chain, managers must be able to focus 

on activities of a resource chain that are in line with direction determined by compe-

tence modes one and two. Fourth competence mode describes organizations flexibility 

to use existing resources in alternative ways. The flexibility of a resource can be de-

scribed by its usability in different ways, the time it takes to change a resource and costs 

that incur when resource is changed. This competence mode is based on flexibilities of 

resources organization can access or acquire when building resource chains and those 

flexibilities thus create organization’s portfolio of strategic options. Fifth competence 

mode builds on organization’s operating flexibility in applying skills and capabilities to 

available resources. The different process design decisions result from decisions in 

competence mode three and four. However, organization’s flexibility to operate effec-

tively within a chosen process design derives from competence mode five. (Sanchez 

2004.) 

 

Sanchez’s (2004) thinking is based on the view of organization as an open system. Or-

ganization viewed as an open system consists of different system elements, which inter-

relate with each other constantly. Product offers for certain product markets are the out-

puts of the system, operations connect organizations’ resources to its processes, tangi-

ble assets are physical assets of the firm, intangible assets consist of knowledge, intel-

lectual property, relationships and reputation, management processes coordinate organi-

zational resources and strategic logic defines how organization creates value in markets 

and it provides strategic goals for organization. (Sanchez 2004.) 

 

Sanchez and Heene (2004: 46–47) define a system accordingly: 

 

“a system is said to exist when a collection of entities (people, things, ideas) 

interact in ways that create interdependencies between the entities. The 

competence perspective characterizes an organization as a system of re-

sources (human, tangible, intangible) that interact and become interdepen-

dent in variety of ways, the most important of which are determined by the 

organization’s management processes.”  

 

Organizations are embedded and they co-evolve with their environment on several le-

vels. An organization as an open system is embedded most directly in its product and 

resource markets, but it is also embedded in strategic groups within its industry, in its 



34 

 

industry more broadly, in its national and regional economies, in the global economy 

and its society. (Sanchez & Heene 2004: 49.) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 4. Firm as an open system (Sanchez & Heene 1996: 17). 

 

 

As organization is guided by its strategic logic, which guides every action individuals 

and groups take in organization, it gives a framework for organizations’ management 

processes how to coordinate assets (Sanchez 2004). Management processes include 

three aspects:  they gather data from organizations product and resource markets, larger 

economic and industry environment and from other system elements, they interpret data 



35 

 

between external environment and internal system elements, and they are processes for 

making decisions, setting policies and defining standard procedures for coordinating 

resources and allocating budgets (Sanchez & Heene 2004: 52). Thus, this strategic logic 

is constantly tested through external and internal feedback (Freiling 2004: 43). These 

feedbacks affect strategic managers’ perceptions of current and desired state of organi-

zations elements in organization’s value creation process (Sanchez & Heene 1996: 16-

17, 2004: 53). Managers receive information through lower-order control loops, which 

include data from lower level system elements, product markets, operations and tangible 

assets, and through higher-order system elements, which include data from intangible 

assets, management processes and organizations strategic logic (Sanchez & Heene 

2004: 54). Strategic managers’ perceptions of strategic gaps depends on which control 

loops they rely on. The data from lower level system elements is useful in maintaining 

competence leveraging activities, but not good indicators of a need for competence 

building processes for improving higher-order system elements (Sanchez & Heene 

2004: 52). 

 

2.4.3. View of competence based on the self-organization 

 

Dyer and Ericksen (2005) emphasize the role of changing environment and state that 

human resource scalability is at least a hygiene factor for organizations acting in stable 

environments but it could be a source for competitive advantage for the many compa-

nies acting in more turbulent environments. They turn to complexity sciences and espe-

cially to the notion of self-organizing systems. They state that these systems can be 

found in organizations especially in an environment characterized by crisis: for example 

in the emergency room at hospital or in the case when army unit is cut off from the 

chains of command.  

 

 

 

 

 

 

 

 

 

 

 



36 

 

 

 

 

 

      

     

(1) Fluid organization 

(2) Discretionary work design  
(3) Relationships and connectivity 

(4) Open auctions for Talent  

(5) Continuous learning 

 

 

 

  

 

 

  

 

 

    (1)Sense of common purpose 

    (2) Contextual clarity 

    (3)Ownership and outcomes  

 

 

 

 

 

Figure 5. Context for human resource scalability based on self-organization (Dyer & 

Ericksen 2005). 

 

 

According to Dyer and Ericksen (2005) system designer’s and participants’ task is to 

provide guiding principles which on the other hand support freedom and flexibility and 

on the other hand promote discipline and order. The guiding principles for flexibility 

and freedom are: (1) static organizational charts should be avoided and leadership 

should be waited for to emerge where needed, (2) employees should be expected to de-

cide what needs to be done and also made sure it gets done, (3) social interaction should 

Hire for 
technical 
and expe-
riental di-
versity and 
cultural fit  
 
Smooth hir-
ing 

Minimize 
layoffs 
 
Cull non-
contribu-
tors 
 
Separate 
humanely 

Principles to promote 

 discipline and order 

Principles to promote free-

dom and flexibility 



37 

 

be encouraged, for example designing physical environments accordingly, (4) open dis-

cussions about career opportunities should be encouraged and (5) relentless drive for 

development should be fostered. The guiding principles for promoting discipline and 

order are: (1) vision and core values should be deeply embedded in organization, and 

rewards and performance should be reflected in part against these goals, (2) people 

should understand how and why human resource scalability matters and (3) hold per-

sons accountable for outcomes. Further, these guiding principles should affect inflow 

and outflow of talent in a way that facilitates and only minimally disrupts the internal 

fluidity. (Dyer & Ericksen 2005.) 

 

2.4.4. View of competence based on autopoiesis 

 

Another view in organizations has been presented lately. This view approaches the 

question of competence and organizations holistically; it questions the rationalistic defi-

nitions of organization’s boundaries and does not make clear distinction between organ-

ization and its environment. For example Hall (2005) takes this different angle to an 

organization and view’s organization as an autopoietic entity. According to this functio-

nalist interpretation, many organizations fit criteria for autopoiesis. He responds to the 

requirements of autopoietic entity accordingly: 

 

1. First is that organizations must be distinguished from its environment. Within 

the collective or industry organizations actions, logos, corporate names and such 

differentiate organizations from environment. Individuals in organizations are 

“tagged” in many ways to members of organizations, such as employment 

agreements and uniforms. 

2. Second is the requirement of organization to determine its own components. 

Human members become members through induction processes; legal docu-

ments define the ownership of intangible assets, etc. 

3. Third is organizations complexity. The organization is constituted on physical, 

human and economic components, which usually are complex by themselves. 

4. Organization maintains its identity. Routines, processes and procedures, such as 

corporate account systems, personnel systems, etc. act to maintain the identity. 

5. Organization produces its own components. Organizations processes such as 

personnel recruitment, induction and training are production activities as they 

transform components as part of a system. 

6. Organizations own components are enough to produce the organizations. The 

processes of self-production are embodied in the organizational structure itself 



 

and encoded in the orga

procedures. 

 

He adds his own final characteristics, arguing that self

sustaining over time, they survive longer that their individual members.

 

Other applications for autopoie

pretation, where organization is seen as an entity with two major functions: memory and 

sensory function. In this model, the focus is on the character of autopoietic entities to be 

open and closed system simultaneously. Memory function refers to organizations self

referentality. It is argued that the accumulated knowledge affects the firm’s way to o

erate and accordingly the way to operate affects the creation and acquisition of new 

knowledge. This memory function offers access to organizations knowledge repertoire, 

its internal structure such as shared culture, strategies, rules and practices, its comp

tence and expertise of its individuals or its knowledge database.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 6. Sensory function, memory function and boundary element

(Maula 2000). 

38 

and encoded in the organizational memory in the form of written processes and 

final characteristics, arguing that self-produced systems are self

sustaining over time, they survive longer that their individual members. 

Other applications for autopoietic theories are for example Maula’s (1999, 

pretation, where organization is seen as an entity with two major functions: memory and 

sensory function. In this model, the focus is on the character of autopoietic entities to be 

em simultaneously. Memory function refers to organizations self

referentality. It is argued that the accumulated knowledge affects the firm’s way to o

erate and accordingly the way to operate affects the creation and acquisition of new 

ry function offers access to organizations knowledge repertoire, 

its internal structure such as shared culture, strategies, rules and practices, its comp

tence and expertise of its individuals or its knowledge database. 

Sensory function, memory function and boundary elements and their contents 

nizational memory in the form of written processes and 

produced systems are self-

 

1999, 2000) inter-

pretation, where organization is seen as an entity with two major functions: memory and 

sensory function. In this model, the focus is on the character of autopoietic entities to be 

em simultaneously. Memory function refers to organizations self-

referentality. It is argued that the accumulated knowledge affects the firm’s way to op-

erate and accordingly the way to operate affects the creation and acquisition of new 

ry function offers access to organizations knowledge repertoire, 

its internal structure such as shared culture, strategies, rules and practices, its compe-

s and their contents 



39 

 

 

 

Sensory function in organization enables interaction with its environment. Organiza-

tions can accumulate and create new knowledge principally in three ways. By accelerat-

ing their learning and renewal processes by experimenting, interacting with their envi-

ronment or by increasing the exposure to relevant triggers from environment. It is ar-

gued that through the understanding of these two major knowledge flows and integrat-

ing and aligning them with organizational variables helps building sustainable know-

ledge management solutions which enable continuous learning, knowledge creation and 

renewal. (Maula 1999; Maula 2000.) 

 

Magalhaes (1998: 114) says that way to see systems as untouchable (organization) and 

part of system which can be changed (structure) by managerial action (languaging) is a 

powerfull resource for a resource-based approach. 

  

Lately the autopoietic framework has been connected to organizational learning. Jack-

son (2007) compared autopoietic system to learning organization and presented follow-

ing list: 

 

1. Entity must have boundary. The learning organization has a boundary, which 

separates it from another learning organizations and its environment. 

2. Entity must have distinct components.  Individuals and different knowledge 

bases such as documentation, training systems and databases form the compo-

nents   

3. System is made up of inter-reactions of its parts. Components of organization 

create the organizational learning system (its rules and culture) through their 

reactions, interactions and transformations. 

4. Boundary components are a result of interactions of other components. The 

boundary of the learning organization is a result of the organizational routines 

that are unique to its system of processes of production. 

5. Boundary components must be produced from inside the system. The compo-

nents that make up the boundary (rules and regulations) are produced by the or-

ganizational learning system 

6. All other components must be produced from inside the system. The compo-

nents that make up the system (knowledge bases, culture) are produced within 

the system. 

 



40 

 

Jackson (2007) continues by saying that even if it looks like learning organization is a 

perfect example of an autopoietic system, one should still take a careful approach to it, 

as it is possible that the theory of autopoiesis is overly simplified if taken strictly analo-

guosly. He stresses the issues of individuals as components, purposelessness of system, 

the role of the external knowledge and the boundary of system should be discussed. 

Still, he continues that in metaphorical level for example autopoietic self-production 

provides an insight on how feedback-loops make organizational learning work. 

 

One example could be the model presented by Crossan, Lane and White (1999), who 

have developed a framework for organizational learning. In their framework learning 

and organizational renewal happens in four processes through three levels. New ideas 

are explored by individuals through intuiting process, which are then fed forward to 

group and organizational levels through interpreting and integrating processes. At the 

same time, institutionalizing process feeds back from organizational level to group and 

individual level exploiting what has been learned and creating routines. Intuiting 

process happens through experiences, images and metaphors and it is largely subcons-

cious process. It can be divided to expert view, which can be described as pattern re-

cognizing, and to entrepreneurial view, which is more about making connections and 

discerning possibilities. Interpreting process enables individual to create cognitive maps 

and to name feelings, sensations and hunches. The domain and environment affect the 

formation of cognitive maps, but cognitive maps also define how environment is inter-

preted. Through the explicit language interpreting process becomes social action and 

shared meanings and understandings are created. Thus this process of interpreting turns 

into process of integrating. Institutionalizing process is more than sum of individuals or 

group learning. “Some of this learning is embedded in the systems, structures, strategy, 

routines, prescribed practices of the organization, and investments in information sys-

tems and infrastructure”. These four processes link individual, group and organization-

al levels together. (Crossan, Lane & White 1999.)  

 

Moreover, Parboteeah and Jackson (2007) provide another framework for organization-

al learning as they view it through the lens of autopoiesis. In their interpretation they 

build their work on a model proposed by Kim (1993), whose model connected the pre-

vious organizational and individual learning theories together. They conclude that 

people in organizations can be considered as first order autopoietic entities and organi-

zations as second order autopoietic entities. They continue that organizations can be 

considered as first order autopoietic entities, but it is not desired as the modeling of rela-

tionships between people and sub organizational processes is difficult. Moreover, they 



41 

 

claim that autopoietic learning resembles single-loop learning and allopoietic learning 

double-loop learning, both individual and organizational level, as it determines the crea-

tion of new mental models and in autopoietic entity change cannot be determined, only 

triggered by the external factor. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



42 

 

3. KNOWLEDGE IN ORGANIZATIONS 

 

Knowledge plays a crucial role in building, sustaining and developing competencies in 

organizations. Thus, one eyed approach to knowledge as easily transferred commodity 

can cause serious setbacks at organization’s everyday life. System approach provides a 

wider conceptual framework and allows us to examine knowledge from different sides, 

and it thus may reveal the possible failures of our current thinking. Understanding the 

complex factors related to knowledge does not necessary remove all the challenges, but 

it gives us at least tools to handle those. In this chapter different approaches to know-

ledge and its management found from literature are presented, and different ways to see 

knowledge and its role in organizations are studied.  Moreover, cognitivist, connection-

ist, and autopoietic epistemologies to knowledge are examined more closely and their 

role in organizational life discussed further. 

 

 

3.1. Different classifications of knowledge 

 

Traditionally knowledge is divided into tacit and explicit knowledge. Nonaka & Takeu-

chi (1995: 9) state that the realized importance of tacit knowledge gives rise to a com-

pletely new view of organizations, not as a machine processing information but organi-

zation as living organism. In this context the understanding of what company stands for, 

where it is going, what kind of world it wants to live in and how to make that world 

reality becomes much more crucial than processing objective information. Other divi-

sions are also made, for example Engeström (2007) suggests that knowledge used and 

generated in work activity can be divided into two types, based on the uses of know-

ledge. Stability knowledge is created to simplify complex reality. It is used when we try 

to understand difficult concepts and objects, human beings and things. Molding the real-

ity in easier form around different categories leads to creation of “stigmatic stamps” on 

stabilized objects. Another form of knowledge, possibility knowledge emerges when one 

is able to depict meanings in movement and transaction, which destabilizes knowledge 

and thus opens up new possibilities.  

 

It is presented (Blackler 1995) that knowledge in organizations can be seen accordingly: 

embrained knowledge is knowledge that is dependent on conceptual skills and cognitive 

abilities. Embodied knowledge is action oriented and likely to be only partly explicit. 

This kind of knowledge is often context-specific and based on the awareness of people. 

Encultured knowledge refers to the process of achieving shared understandings. These 



43 

 

understandings create cultural meaning systems, which are heavily dependent on the 

language used and thus socially constructed. Embedded knowledge is knowledge which 

resides in systemic routines and it can be found in relationships between technologies, 

roles and procedures for example. It should be analyzed from a holistic view. Encoded 

knowledge is information conveyed by signs and symbols. It can be found in books and 

manuals or in the electronic form. Alavi and Leidner (2001) state also that knowledge 

can be situated in different forms in organization. It can be tacit, rooted in actions, expe-

rience and involvement in specific context, in mental models (cognitive tacit) or know-

how applicable to specific work (technical tacit). It can also be explicit, articulated and 

generalized knowledge. There can be a social dimension, when knowledge is created by 

and inherent in collective actions of a group or it can be individual, created by and inhe-

rent in the individual. Knowledge can be divided to declarative (know-about), procedur-

al (know-how), causal (know-why), conditional (know-when), relational (know-with) 

and pragmatic, useful knowledge for an organization. Quinn, Anderson and Finkelstein 

(1996) continue in a same line and argue that knowledge exist in four levels. Cognitive 

knowledge is basic knowledge that employee has through training and education. Ad-

vanced skills are knowledge to apply “book learning” into action. Understanding sys-

tems is greater understanding of complex cause-and-effect relationships. The last level 

is self-motivated creativity, which encompasses employees will, motivation and adapta-

bility for success. The last one resides inside the individual while the three former levels 

can exist in organization’s systems, databases or operating technologies.     

 

Sanchez (2004, 1997: 174–179) claims that there are three levels of knowledge within 

the firm: state, process and purpose forms of knowledge. Thus, there are three different 

contents of knowledge, know-how, know-why and know-what. Know-how refers to 

practical understanding of processes and products. The main learning process is learning 

by doing. Know-why knowledge refers to theoretical understanding, and it affects on 

adapting existing processes and products or development of new products or processes. 

Its main learning process happens through theoretically directed learning by doing or 

through importing new theory. Know-what knowledge is manifested by identifying and 

defining new kinds of products and processes. Learning process happen either bottom-

up, learning from changes in state or process theory, or top down learning by emulation, 

metaphor or imagination. 

 

 

 

 



44 

 

Table 4. Knowledge types and their uses (adapted from Sanchez 2004). 
Focus of knowledge in 
organizations 

Type of knowledge 
needed 

Processes 
Strategic logic 

Know-what 

The use of resources 
Creation of alternative 
processes 

Know-why 

The use of skills and capa-
bilities 

Know-how 

 

 

Alternative views have been presented also. Some authors (Firestone & McElroy 2005; 

Campos 2008; Hall 2005) base their distinction on Popper’s (see for example Sahavirta 

2006) notion of knowledge. In this philosophy three kinds of knowledge are distin-

guished. World 1 knowledge is represented in physical reality, in objects and structures. 

World 2 knowledge refers to internal mental world, including cognition and conscious-

ness. World 3 knowledge refers to autonomous world of mental products, including 

scientific theories, social and cultural products and linguistic formulations. It is argued 

that it is more appropriate in the studies of organizational knowledge than conventional 

views of knowledge (Hall 2005: 172). 

 

 

3.2. Theoretical perspectives to knowledge management 

 

Even if the concepts differ, there is one thing in common: knowledge is seen as one of 

the most important factors in organizations success. In fact, knowledge-based view of 

the firm sees knowledge as a main source for competitive advantage (Grant 1996). As 

knowledge can be seen as resource, it differs from other resources, such as financial, 

physical, organizational, technological, intangible, or human resources drastically, as it 

takes many forms and shapes at given moment in time, it may be dynamic, hard to grasp 

theoretically and most importantly, it is the underlying basis for forming competences 

(Von Krogh & Roos 1995b). Thus it is no surprise that different ways to analyze know-

ledge in organizations is presented. Kakabadse, Kakabadse and Kouzim (2003) found 

five knowledge management perspectives from the knowledge management literature: 

philosophy-based model, cognitive model, network model, community of practice mod-

el and quantum model. The main concern of philosophy-model is how information is 

gathered about social and organizational reality, and it is focused on objectives, type 

and the source of knowledge. It is also interested in the relationships between know-

ledge and certainty, belief justification, causation, doubt and revocability. Cognitive 



45 

 

model is rooted in positivistic science and sees knowledge as value creative asset. It is 

based on the rationalistic definitions of knowledge. Focus of network model is on the 

network organization and on sharing, acquisition and transferring knowledge. Commu-

nity of practice model is possibly the oldest knowledge management model. It is fo-

cused on interpersonal relationships and that knowledge resides in communities, in the 

network of actors. Quantum model assumes that communication and information tech-

nology will change radically when built using quantum principles. New knowledge is 

not enough, meaningful knowledge is required in order to cope with new levels of com-

plexity and decision making.  

 

Many authors have brought something in knowledge management discussion. Nonaka 

and Takeuchi (1995) brought commonly known knowledge creation-creation cycle and 

later (Nonaka & Konno 1998; Nonaka, Toyama & Konno 2000) the concept of “ba” 

into the discussion. Choo (1998) in his model added cultural knowledge in tacit and 

explicit knowledge classification. Leonard-Barton’s (1992, 1995) approach is the notion 

of the importance of knowledge creation and diffusion for innovations in organizations.  

The core capability and creativity are built upon innovations which require the building 

of organizational knowledge. For example, Edvinsson (2002) and Sveiby (1997) pro-

mote intellectual capital movement (utilizing organizations intangible assets), and Svei-

by has also presented an autopoiesis based model on strategy formulation (Sveiby 

2001). Zack (1999) speaks on behalf the importance of knowledge architecture and fo-

cuses on information technology and the importance of explicit knowledge whereas 

Davenport and Prusak (1998) put emphasis on knowledge generation, codification, 

coordination and transfer through knowledge management projects. Moreover, Von 

Krogh (2009) states that current discussion between individualist view of knowledge, 

which sees knowledge residing in individuals, and collective view of knowledge, which 

sees knowledge in collectives, shouldn’t compete with, but complement each other and 

information systems could facilitate that. Further, Gao, Li and Nakamori (2002) com-

bined systems thinking and systems methodologies to knowledge management. Last, 

lately research streams on knowledge management, complexity sciences and organiza-

tional learning are getting closer to each other in order to provide holistic, system based 

approach (McElroy 2000). For example, in their vast systematic review of the debate of 

organizational learning and knowledge conversion, Nonaka and Von Krogh (2009), 

present suggestions for a future research needs on the area. Those research suggestions 

all include the aspect of social practices, for example the relationship between know-

ledge creation and social practices and the role of social practices in conservation of 

tacit knowledge, existing routines, organizational knowledge creation and innovation 



46 

 

3.3. Organizations as knowledge systems 

 

Choo (1998) offers a holistic model to view knowledge in organizations, drawing espe-

cially from sense making and information processing theories, and distinguish three 

modes how organizations use information: sense making, knowledge creation and deci-

sion making. His view is that through interpretation, conversion and analysis of infor-

mation shared interpretations, innovation and rational, goal directed behavior are 

created. Together these three form the knowing organization. Other authors also see 

organizations as knowledge systems. According to this view, collective understandings 

and interpretations that emerge in companies over the time play crucial role. Moreover, 

most important resource in organizations is knowledge that enables management to 

make distinct uses of organizational resources by devising distinctive value-creating 

strategies, organizational knowledge – the ability to collectively make “better” judge-

ments of significance than others- is what makes the difference (Tsoukas & Mylonopou-

los 2004: 9). Previously mentioned Nonaka’s and Konno’s (1998) model common place 

or space where knowledge is created is labeled as organization’s “ba” . Firstly, it can be 

originating ba, which refers to socialization mode of knowledge creation circle. This is a 

common place where experiences are shared primarily through face-to-face interaction. 

Secondly, it can be interacting ba, which is associated with externalization mode of 

knowledge creation. Here tacit knowledge is transformed through dialogue and collabo-

ration to explicit knowledge. Thirdly, cyber ba, virtual interaction, represents the com-

bination mode of knowledge creation. Fourthly, exercising ba facilitates the process of 

converting explicit knowledge to tacit knowledge and it is a space for continuous and 

active individual learning (Nonaka & Konno 1998). Gupta and Govindarajan (2000) 

emphasize the importance of social ecology and its necessity for successful knowledge 

management. Social ecology refers to that social system, within which people operate. It 

defines organization’s formal and informal expectations towards individuals, chooses 

types of people who fit in the organization, shapes the freedom of individuals to act in-

dependently and aim for goal, and it affects how people interact with each other, both 

inside and outside the organization. Culture, information systems, rewarding systems, 

processes, people and leadership define social ecology. Social ecology should be 

viewed as a single entity where every element affects to others.  

 

Alavi and Leidner (2001) base their idea of organizations on the research in sociology 

of knowledge and they view organizations as social collectives and knowledge systems. 

According to them, these knowledge systems consist of four sets of socially enacted 

knowledge processes: creation (construction), storage/retrieval, transfer and application. 



47 

 

These processes are not just at set of activities functioning separately, but intertwined 

and interconnected set of activities, happening simultaneously, embedded in physical 

structures, groups and individuals (Alavi & Leidner 2001: 123)  Gupta and Govindara-

jan (2000) see that as the life time of knowledge is getting even shorter, an effective 

knowledge management machine must excel at two central tasks, which are creating 

and acquiring new knowledge and sharing and mobilizing knowledge through organiza-

tion. The task of accumulating knowledge can be further divided into three subtasks, 

which are knowledge creation, knowledge acquisition and knowledge retention. The 

task of mobilizing knowledge can also be divided into subtasks, which are knowledge 

identification, knowledge outflow, knowledge transmission and knowledge inflow. 

There are always some challenges in these processes. All of these challenges derive 

from the dysfunction of social ecology. Boer, van Baalen and Kumar (2004) divide the 

relationships where knowledge is transferred in organizations in four modes, based on 

theories from the areas of sociology, social anthropology and social psychology. In this 

model humans are considered social in nature and arranging their social life according 

to others, and relations are considered definitive, satisfactory and meaningful. First 

mode is communal sharing which describes group or dyadic relationship which mem-

bers are equal and focus on common characteristic instead of individual differences. In 

these groups people think that they own a common factor and thus consider it natural to 

show friendliness and unselfishness. Authority ranking relationships are built on some 

kind of linear social hierarchy. The higher the rank one is, the more information one has 

access compared to the individuals at lower level, and they share it when needed. Indi-

vidual in higher level possess privileges and authority that individuals in lower levels 

don’t. On the other hand, lower level individuals are justified for protection of higher 

level individuals. Equality matching relations are based on reciprocal giving and taking. 

People are focused on keeping relationship on the balance and observing how far from 

balance relationship at certain moment is. Everyone, who bri