中華大學博士論文

(1)

中華大學博士論文

Model for Measuring Effects of Existing Knowledge on the Creation of New Knowledge and Knowledge Creation

Process

系所別：科技管理博士學位學程學號姓名： D09703025 Dmytro Korposh

指導教授：魏秋建博士

李友錚博士

中華民國100年7月

(2)

i

ABSTRACT

Advancing technologies and constantly changing market needs induce competition between organizations and force enterprises to adopt better management methods to improve operational performance to survive and make profits. Knowledge management has been widely recognized as one of the effective methods to achieve the above objective. Knowledge management attracts attention of managers, researchers, scholars, and practitioners. Previous researches of knowledge management chiefly focused on qualitative approaches, and largely stressed key success factors of knowledge management, such as the infrastructure of information technology, the design of the knowledge management system, deployment of motivation schemes, interaction between IT and people, organizational culture and the like.

Among them, the knowledge spiral of socialization, externalization, connection and internalization are the core of researches and discussions. However, early studies only disclosed the necessary cyclical phenomenon of knowledge management. Main approaches are aimed at collection of knowledge available to the organization and its further implementation in analogical situations. These approaches are known as lessons learned.

Though reusing of existing knowledge is not always enough to fulfill organization‘s goals.

New knowledge is needed for the organization‘s development and product/service improvement. Therefore the creation of new knowledge is vital to the organization. A quantitative method revealing how the existing knowledge can support the creation of new knowledge or upgrade current knowledge remains nonexistent. To bridge this gap, this study proposes a mathematical model which can quantify the supporting effects of the existing knowledge on the creation of new knowledge, help managers to plan and to measure the outcome of new knowledge created based on the factors of combination index, mutation index, knowledge creation ability, knowledge needed from others, ability to share, ability to learn, physical distance, difference of knowledge areas and difference of knowledge levels. The model evaluates knowledge from the perspectives of complexity (knowledge type/knowledge area) and depth (knowledge level), and the results of the example illustrate that the proposed model can be an effective method of measuring the usefulness of the existing knowledge.

Keywords: Knowledge management, knowledge creation, knowledge complexity, knowledge level, knowledge spiral, modeling.

(3)

ii

摘要

技術的發展和不斷變化的市場需求加劇了組織間的競爭，並迫使企業採取更好的管理方法來改善營運績效與賺取利潤。知識管理已廣泛地被認為是一種可以達到上述目標的有效方法。知識管理也因此獲得經理人、學者與實務界的普遍關注。之前知識管理的研究者主要著重在定性方法的探討，而且大多數強調知識管理的關鍵成功因素，例如資訊技術架構、知識管理系統設計、激勵方案使用、資訊技術與人的互動與組織文化等。

在這些當中的主要研究與討論，都環繞在社交網路、外部連繫與內部溝通。然而，早期研究只有揭露出必要的知識管理週期現象，主要目的也只在於收集組織可用的知識，

以近一步印證於類似的情況而已。這些就是眾所皆知的經驗教訓。然而重複運用已存在的知識早已不能夠滿足組織的目標。為了組織的發展與產品與服務的改善，新的知識必須被持續發展出來。所以，創造新知識對組織而言是一件非常重要的事情。定量方法才可以發掘現有知識是如何創造新知識和提升現有知識。為了彌補這個缺口，本研究提出一個數學模式，可以量化現有知識對創造新知識的影響，並且幫助管理階層規劃和衡量新知識如何創造，模式應用到的參數包括綜合指數，突變指數，知識創造能力，對他人的知識需求，分享能力，學習能力，距離，不同領域的知識和不同等級的知識等等。本研究所提模式從複雜度(知識種類/知識領域) 和深度(知識等級)來評估知識，從案例的結果證明本模式可以有效評量現有知識對知識創造的貢獻度。

關鍵字：知識管理、知識創造、知識複雜度、知識等級、知識環繞、模式化。

(4)

iii

List of tables

Table 1 Various coefficients ...54

Table 2 Difference between knowledge areas ...54

Table 3 Knowledge needed from others ...55

Table 4 Mutation coefficient ... ...56

Table 5 Combination coefficient ...56

Table 6 Physical distance between persons ...57

Table 7 Amount of knowledge received from Person 1 ...57

Table 8 Amount of knowledge that can be created and best pairs ...59

Table 9 Knowledge types and levels of knowledge ... ...60

Table 10 Cumulative effect ...61

Table 11 Supporting effect of different knowledge types ...62

Table 12 Norm of level of knowledge ...63

Table 13 Total support for knowledge creation ...64

Table 14 Aggregated calculation of algorithm 1 ...75

(6)

v

List of figures

Figure 1 Research processes...4

Figure 2 Data, information, knowledge ...6

Figure 3 Knowledge types ... ...8

Figure 4 The SECI process ...17

Figure 5 Ba as shared context in motion ………...19

Figure 6 Creation of new knowledge by combination and mutation ...34

Figure 7 Difference of knowledge areas……...………...………...37

Figure 8 Knowledge creation process using combination ………...38

Figure 9 Existing and desirable knowledge ...………....46

Figure 10 Supporting effect of existing knowledge with increasing complexity …….………49

Figure 11 Influence of factors on desirable knowledge …………..………..51

Figure 12 Existing and desirable knowledge ...61

Figure 13 Importance of factors for knowledge creation by combination ...65

Figure 14 Knowledge created by combination. Tradeoffs... ……….65

Figure 15 Importance of factors for knowledge creation by mutation …...……….…...67

Figure 16 Knowledge created by mutation. Tradeoffs………..………67

Figure 17 Implementation Algorithm 1……….………78

Figure 18 Implementation Algorithm 2……….………79

(7)

1

Chapter 1 Introduction

This chapter describes the research background related to knowledge management, research motivation, research objectives, research limitations and assumptions and research processes.

Section 1 Research background and motivation

Rapid development of modern world in all areas of human life made people understand that current usage of resources without any changes will lead to their vanishing, this, in turn, has led to the origination of knowledge economy and faced people with the new reality that physical goods and resources are not as important for the modern economy as knowledge.

Nowadays, enterprises have encountered a great challenge to survive and to make profit among many others. Simply producing goods or services is not enough to fulfill the needs of customers and to satisfy clients. Increasing complexity in connections and interconnections between customers, producers, suppliers, and rivals needs to be understood and managed in order to obtain competitive advantage. Knowledge management has emerged in attempts to understand and explain the mechanisms of knowledge economy and to help the organizations to cope with new challenges.

Knowledge management has proved itself a powerful tool for organizations to take advantage over competitors. This raises attention to knowledge management of practitioners and researchers and provokes implementation of knowledge management in many organizations and catalyzes theoretical research in this field. As knowledge has been recognized as a powerful and indispensable source for organization‘s existence, the questions of how to measure, manage and use this source become significantly important.

As knowledge is so important and valuable, one will be naturally interested in how he or she can acquire it, transfer it, and create it. Knowledge creation seems to be the most important among these questions, because if organization is able to create knowledge, which is actual and demandable, this will produce potentially unlimited source of valuable resources.

Unlike natural resources, knowledge can grow and expand over time. Usage of natural resources will inevitably reduce their total amount; on the other hand, usage of knowledge will not only remain its total amount but also can lead to creation of new knowledge. This

(8)

2

phenomenon is incredible and deserves additional attention from organizations. Processes of knowledge creation have become the focus of practitioners and researchers. Though many theoretical researches and case studies have been conducted to understand and discover the processes of knowledge creation, however methods or tools that can measure the knowledge creation processes remain nonexistent. Such method can enhance the productivity of knowledge managers by giving them a powerful tool to predict, plan and implement the knowledge creation processes.

Ubiquitous application of knowledge management requires tools and methods that can be used by managers in their daily work. The need and desire to understand, to model, to predict and to measure the knowledge creation processes motivates this research. Besides, how existing knowledge can support and enhance the creation of new knowledge will also be explored in this study.

Section 2 Research objectives

Based on the research background described in the previous section, the objectives of this research can be summarized as below:

1. Describe knowledge creation processes,

2. Determine the factors which influence the processes of knowledge creation, 3. Establish how existing knowledge can influence the creation of the knowledge and 4. Develop a mathematical model to quantify the knowledge creation processes.

Section 3 Research limitations and assumptions

Numerous factors that influence knowledge management in an organization in general and the processes of knowledge creation particularly make it difficult if possible to examine all of them simultaneously. In this study, the most important factors based on existing researches and practices of knowledge management are considered. Besides, this study explores the knowledge creation processes from the perspective of evolutionary theory, i.e., knowledge creation is regarded as a continuous development process, and it is assumed that the knowledge needed to conduct knowledge creation processes comes from knowledge transfer, and knowledge transfer occurs between two individuals. Moreover, knowledge in this study is expressed in two dimensions, i.e., knowledge depth and knowledge complexity.

(9)

3

Additionally, because of the lack of real data, the model developed in this study is simulated using only experimental example.

Section 4 Research processes

This research was conducted to understand the mechanism and details of the knowledge creation process, to determine the factors that influence the knowledge creation process and to describe this process in terms of mathematical models that can measure how existing knowledge can influence and support creation of new knowledge, and how the outcome of knowledge creation process can be predicted and measured. In order to understand the mechanism and details of the knowledge creation process and to find the most important factors that influence this process, publications over the last few years and the most recognised studies from past in the field of knowledge management were reviewed. Knowledge creation process is considered as an evolution process in this study; therefore reviewing of theories of evolution is important and gives resources for deep understanding of how knowledge creation process can be seen from the perspectives of evolution. Analysis of literatures made it possible to define those factors and to build logical mathematical models. These models were tested with synthetic data and results were analysed and showed that models can be used by knowledge managers and can help managers in decision making when planning the knowledge creation process and choosing the most appropriate teams to solve organizational knowledge problems. Based on the models testing result, conclusion and suggestion for further research were provided, contribution to current body of knowledge from theoretical and practical aspects were discussed.

(10)

4

Figure 1 Research Processes

Problem statement

Literature review

Knowledge management

Evolution theories

Literature analysis

Model formulation

Model testing

Results analysis

Conclusions Further research Contribution

(11)

5

Chapter 2 Literature Review

By nature, people in all times wanted to explore unknown and to open new and interesting world to themselves and to others, and discovering unknown forms human knowledge. The unknown is unlimited as unlimited is the essence of our world, and it is desired by everyone for different reasons, and it is, to some extent, mysterious. Even there is no yet one definition for what is ‗knowledge‘ and what is included in ‗knowledge management‘, this can not diminish the importance and power which it gives to one who posses it. ‗Knowledge is power‘ from Sir Francis Bacon precisely describes situation in modern world. To know what, how, when and why are necessary to achieve one‘s goals. To put all these ―knows‖ together and accomplish the desirable results from them are the objective of knowledge management.

Knowledge management has become a hot topic over the last few decades and accumulated a great amount of discoveries in theoretical and practical spheres. Explosion of interests in this field demonstrates the importance of knowledge management to the modern organization. This chapter will provide explanation of what knowledge and knowledge management is; explore established and recognised theories of knowledge management, and review many of recent studies in the area of knowledge management. As knowledge management covers almost all organizational activities, it has been studied from different perspectives to answer numerous questions which appeared from intensive implementation of knowledge management in organizations. The subject is not completely learnt and studied yet because not all questions have been answered. Without comprehensive understanding of how to implement, manage, measure the effectiveness, predict the productivity of knowledge management in organizations can not realize the full potential of knowledge management.

Section 1 Data, information and knowledge

Knowledge is defined by the Oxford English Dictionary as: (i) expertise and skills acquired by a person through experience or education; the theoretical or practical understanding of a subject; (ii) what is known in a particular field or in total; facts and information; or (iii) awareness or familiarity gained by experience of a fact or situation.

(12)

6

Knowledge includes data and information in a specific context. Data by itself has no meaning, it should be organized and interpreted to get a meaning and become information.

Information indicates some relations between data. Information, by turn, needs to be placed in a specific, particular context to become knowledge. Figure 2 shows the hierarchy of data, information and knowledge. For example ‗30˚C‘ is a data which has no meaning without additional data or conditions which can explain or extend the original meaning.

Figure 2 Data, information, knowledge

On the other hand, ‗it will be 30˚C tomorrow in Taipei‘ is information. Using this information and existing knowledge or experience, and putting it in different context might lead to originating new knowledge. Using this information and experience, one can know that he or she doesn‘t need to put on a coat tomorrow. Putting it in another context, the seller of ice cream can know that there will be demand for ice cream tomorrow; based on this knowledge and information about ice cream stock, one can make a decision to increase supply, so that ice cream will not run out of stock tomorrow. In other words, one cannot have knowledge without information and data, but pure data and information are not useful without a specific context.

The same data and information can be synthesized and interpreted into different knowledge depending on the requirements and abilities of knowledge creator.

Another difference between data, information and knowledge is the way to store and to transfer them. Data and information usually are easy to codify and store on paper, electronic devices, etc. This allows easy access to data and information and gives numerous ways of transferring, such as post, e-mail, databases, libraries, etc. Knowledge, on the other hand, is

Knowledge

Information

Data

(13)

7

not always easy to store or transfer; and some parts of knowledge are embedded into person‘s mind, interconnected with other knowledge and experience and therefore, impossible to store and hard to share or transfer.

Section 2 Knowledge types

As mentioned above, knowledge is not identical; it has different characteristics and features, In other words, knowledge is versatile. It can be highly perishable and durable, useless today and vital tomorrow, necessary at one place and unclaimed at another.

Classification between knowledge types is made to show which knowledge is easy to codify, understand, transfer and store, and which knowledge needs special conditions or tools, environment or forces to be understood, used and applied. In Encyclopedia of Knowledge Management, Prat integrated knowledge types which were highlighted by various researchers in various studies. He combined them into a hierarchical structure so one can easily see the variety of knowledge types. Figure 3 shows this classification (Prat, 2006).

1. Explicitness of knowledge. Explicitness divides knowledge into tacit knowledge and explicit knowledge. Tacit knowledge is embedded into person‘s mind and is difficult to express, share, transfer, codify and store, as a result that we know more than we can say or write down. Tacit knowledge is also based on personal and cultural features, experience and skills. An artist can‘t explain how he or she makes a painting, if you don‘t know how to ride a bike or swim, reading a manual about how to do so will not make you able to ride a bike or swim; you need to acquire these knowledge by doing and personal experimentation. Explicit knowledge on the other hand can be easily codified, shared and transfer. Human‘s explicit knowledge can be found in books, patents, instructions and manuals. One plus one equals two, how to assemble a bicycle form the spare parts, symptoms of flue are examples of explicit knowledge which can be easily taught, codified and stored (Prat, 2006).

2. Reach divides knowledge into individual and collective knowledge. Individual knowledge refers to the knowledge asset of particular person, collective knowledge includes group knowledge, organizational knowledge and inter-organizational knowledge. Obviously any group or organization cannot have a knowledge by itself, the aggregated knowledge of its current or former members or employees form collective knowledge. At the same time this

(14)

8

knowledge depends on relationships between members of group and if taken out of that group can lose its power. Organization‘s patents, industrial processes, etc. are examples of collective knowledge (Prat, 2006 ).

Figure 3 Knowledge Types.

Note. From ―A Hierarchical Model for Knowledge Management” by Prat, N.

Encyclopedia of Knowledge Management.

3. Abstraction level makes division between general and specific knowledge. General (abstract) knowledge is knowledge which is available to a large number of people and easy to share, such as laws of nature, general physics rules, knowledge about how to use computer, etc.

Specific knowledge is possessed by a limited number of people and is difficult to share such as knowledge about life behavior of bugs, how to use special medical equipment, market demand of specific goods in different regions, etc (Prat, 2006).

4. Propositionality divides knowledge into declarative knowledge and procedural knowledge.

Declarative knowledge (‗know-what‘) is the knowledge about objects and events, their attributes and characteristics. ―A hot water needed to make a tea‖ is an example of declarative knowledge. Procedural knowledge (‗know-how‘) is the knowledge about how to operate or how to perform, how to solve the problem, which describes a series of steps needed to be done to solve some problem. A consequence of steps need to be performed to make a tea is a procedural knowledge (Prat, 2006).

(15)

9

Section 3 Knowledge management

Knowledge management as a systematic science has not so long history but its constituents were exploited by people and organizations for centuries in order to get a desirable result and reach specific goals. Mostly, it was done unconsciously but this is the way all sciences were established, recognized, being started to develop and implemented. This way best practice were used by companies to optimize their processes and overall performance, people were using their practical knowledge in agriculture and hunting long time before any company was established. Focused use of knowledge management to exploit and to improve existing knowledge assets and to create new knowledge is relatively recent and there are many blank spots in it.

Knowledge management covers almost all aspects of organization‘s activities. It works with explicit and tacit knowledge, organizational and personal knowledge. Knowledge management exploits information technologies, human resources, organization theory, psychology and others. Objectives of knowledge management are improving organization‘s performance, rational usage of resources including knowledge resources, stimulation of innovations and overall organization‘s improvement.

Different organizations have different vision, priorities and strategies; this makes them use different knowledge management strategies. Advantages and disadvantages of different ways of implementation knowledge management in organizations, preferable models for different industries and countries, success factors of some organizations and failure of others were described in numerical resources. Wiig (1997) distinguished five basic knowledge- centred strategies:

1. Knowledge strategy as business strategy which focuses on knowledge creation, use of the best knowledge available at every action;

2. Intellectual asset management strategy which focuses on management of specific intellectual assets such as patents, technologies, operational and management practices, customer relations, organizational arrangements, etc.

3. Personal knowledge asset responsibility strategy which focuses on personal knowledge responsibility for knowledge use, sharing, creation, making it available for other workers of individual worker to achieve organization‘s goals.

(16)

10

4. Knowledge creation strategy which focuses on knowledge learning, research and development, motivation of workers to obtain new and better knowledge that will lead to improved competitiveness of organization.

5. Knowledge transfer strategy which focuses on knowledge systematic approaches to transfer, acquire, categorize, organize, store, repackage for deployment and distribute knowledge to points of action where it will be used to perform work. This also includes knowledge sharing and adopting best practices (Wiig, 1997).

Each organization chooses strategy (or combination of strategies) which, the organization believes, will better meet its vision, use entirely employee‘s capabilities, fit the organization‘s culture and structure and lead to success. This diversification originates from non maturity of knowledge management, and focusing just on some aspects of organization‘s activities will lead to one side development. Systematic knowledge management should cover all spheres of the organization activities so it can better operate knowledge assets, make proper conditions for employees to reuse existing knowledge, assist in new knowledge creation and make this new knowledge available to other workers so it can be turned into new products, services, and enhance existing processes.

Knowledge management is not a onetime action; it is a complicated process which needs to be performed continuously in the organization to make the organization competitive, productive, effective and successful. Establishing knowledge management in organization is a complicated and important process which should include all organizational levels. Isolated top-down or bottom-up activities will not yield desirable result.

1. Establishing knowledge management in organization

Kjæ rgaard and Kautz (2008) studied an interesting case of establishing knowledge management in organization. Their study focused not on relationship between dependent and independent variables and result of these relationships (like the most of studies do), but on events, organizational members and context interact over time. They described a bottom-up process and find that it cannot be successful without support of top management. They found that organization culture and identity play an important role for establishing knowledge management in organization. It is important for workers in all levels to clearly understand organization‘s knowledge management ideas, concepts and incentives. In many organizations, top managers feel that their knowledge management policies are effective, but non-senior

(17)

11

managers think that they get good results in spite of the policies (Soo, Devinney & Midgley, 2002). Small and medium firm in high technological industries need to cooperate in order to compete with large firms. Knowledge management is different in different companies, countries and industries. Industry features and specifics make knowledge management different for firms which cooperate within industry and ones who not (Lin, Yen & Tarn, 2007).

Industry-layer knowledge management consists of four modes: knowledge clustering, knowledge enlarging, knowledge exchanging, and knowledge initiating. Modes positively correlate each other and lead to overall improvement in industry-level knowledge management.

2. Human and system oriented knowledge management

Different knowledge management strategies have different features and views of their implementation (Choi & Lee, 2002). Choi and Lee (2002) distinguished human oriented and system oriented knowledge management strategies and three points of views for employing them: focused, balanced and dynamic. System oriented methods focused on codifying and storing of knowledge to enable its further access and use. The human-oriented methods focused on sharing and acquiring of tacit knowledge through interpersonal interaction.

Focused view suggests companies to choose one kind of strategy and follow it, the balanced views propose to choose a right balance between two strategies, and the dynamic view suggests aligning strategies with the characteristics of knowledge. Choi and Lee (2002) concluded that organizations need to align knowledge strategies along with knowledge creation modes and use different knowledge strategies in different types of departments. The effective utilization of information technologies was the part of the trend in which human- oriented approaches were combined with the systemic-oriented approaches (Baba & Nobeoka, 1998).

Lin and Hsueh (2006) proposed a knowledge map management system to facilitate knowledge management in virtual communities of practice. This system uses automatic categorization technique to extract the knowledge structure of documents; this enables the dynamic knowledge management in communities of practice.

However automated approach cannot work better than human oriented approach yet software but itself can be a source of knowledge (Klint & Verhoef, 2002). Though technology plays an important role in the knowledge creation process, information systems are necessary but not sufficient for knowledge creation (Soo et al., 2002). Virtualization of many areas of

(18)

12

people‘s life impacted the knowledge creation process as well. Use of information and communication technologies influences extension of old and creation of new knowledge (Vaccaroa, Velosoa & Brusoni 2009). Vaccaroa et al. (2009) argued that through virtual experimentation, more complex tacit knowledge can be generated than by using traditional working practices. If knowledge is not accumulated systematically, it cannot be used for future decision making or problem solving (Chen, Huang & Cheng, 2009). Chen et al. see three constructs for knowledge accumulation: database utilization, systematic management of task knowledge, and individual capacity for accumulation.

Adoption of new technologies must consider the influence of them on the knowledge management culture of the organization (Malone, 2002). Information systems are often not connected with the worker‘s job, and most systems are inadequate and fail to satisfy organization‘s strategic goals (Soo t al., 2002). These systems make it harder not easier to work and bury knowledge management initiatives. On the other hand, systems which are embedded into day-to-day job and provide useful information and knowledge are very successful and bring financial benefits to companies (Babcock, 2004).

Importance of human orientation for knowledge management is supported also by research in talent management field. Grounding talent management in a strategy field of the organization, developing environment, structure and tools which support talented workers can improve the quality of talent conversation on organization and lead to effective knowledge creation process (Lewis & Heckman, 2006).

Section 4 Knowledge management process

Knowledge management is a complicated continuous process which offers different strategies, tools and techniques to organizations so they can improve, increase, manage and utilized their knowledge assets. Knowledge management process consists of knowledge acquisition, knowledge storage, and knowledge transfer and knowledge utilization. These four processes can happen in different time in different places and are not linear (Prat, 2006).

Knowledge acquisition is focused on accumulating knowledge, ways to posses new knowledge and knowledge creation.

(19)

13

Knowledge storage tries to distinguish and categories existing or newly created knowledge and store it in organizational memory (knowledge repository, knowledge yellow pages, documents, patents, manuals, everyday routine, etc.).

Knowledge transfer makes organizational and individual knowledge available to knowledge workers within organization or in inter-organizational level. Different ways of knowledge transfer can be chosen depending on the aims of transferring (face-to-face communication, letters or e-mails, video conferences, seminars, etc.).

Knowledge utilization makes knowledge useful for organization through applying it to decision making, problem solving, process improvement, new product development, putting knowledge into organization‘s routine. All knowledge management processes are important but without application of knowledge, organization will not benefit from any knowledge asset.

1. Knowledge acquisition

Knowledge acquisition and knowledge creation as a tool to acquire new knowledge was considered by many researchers as a key factor of knowledge management. Knowledge creation can be compare with the terrain search with unknown paths which become known by moving to the goal (von Krogh, Nonaka & Aben, 2001). Tacit and explicit knowledge and interaction between them play the central role in the knowledge creation process (Nonaka, Toyama, & Konno, 2000). Cognitive component of tacit knowledge refers to individual‘s perception of reality and vision for the future. The articulation of tacit perspectives is a key element in creation of new knowledge (Nonaka, Byosiere, Borucki, & Konnot, 1994).

Synthesis of tacit knowledge which is rooted in know-how depends on worker‘s ability to absorb knowledge and incentives of organization (Soo et al., 2002). The quality of the group tacit knowledge is also important for the knowledge creation. To use the potential of all individuals who work together, to make the group tacit knowledge more than just sum of individual‘s knowledge is the big challenge to the managers (Erden, von Krogh, & Nonaka 2008). Erden et al. (2008) recognized it as a leader‘s responsibility to mobilize tacit knowledge that is distributed among workers in organization and create a context for knowledge creation. They developed a ranking for the quality of group tacit knowledge and steps that group is passing through its developing from people put together to the group that thinks and acts as a one mind. High quality tacit knowledge not only helps in solving planed problems but also increases workers ability to create new problems, improve existing methods

(20)

14

of problem solving and not limit themselves by well known and everyday used approaches but improvise and create new approaches. Knowledge management refers to the ways firms capture and disseminate their tacit processes (Malone, 2002).

Kahn, Nowlan and McDermott (1985) in their work described and analysed the strategies of knowledge acquisition using the automated knowledge acquisition system, they described the MORE system and argued that the methods used by it can be used for developing other automated knowledge acquisition systems. Mineau, Missaoui & Godinx et al.

(2000) offered the use of the conceptual model languages which might help to extract knowledge which is embedded in databases. They see it as a way from data management to knowledge management and the way to develop knowledge management systems. Huang, Wei, & Chang (2007) discussed the acquisition of customer‘s knowledge in e-commerce.

They applied agent technology and fuzzy ontology to show how the seller can utilize the fuzzy knowledge about customers needs to fulfill customer‘s expectation. Interaction between the seller and the buyer is needed in order to transfer the information about real customer‘s needs, in more cases they see these knowledge as a fuzzy knowledge which is needed to be combined and crystallized in products, so the products will match with the customer‘s needs. Agent technology was seen as the best way to acquire fuzzy customer‘s knowledge.

Sherif and Xing (2006) proposed a knowledge creation process which is based on the principles of complex adaptive systems. They suggested several hypotheses of how exploitation and exploration, aggregating and abstracting, creating multiple versions of existing knowledge assets, establishing relations between knowledge assets, collecting the feedback of the knowledge assets performance will facilitate the creation of new knowledge.

They found that applying assets outside their domain will lead to the diffusion of innovation across the organization, and that the capture and dissemination of knowledge is not enough for knowledge creation, and that knowledge repositories might be harmful for the knowledge creation process, as the workers can use old solutions and don‘t feel the need for changes.

These results were based on the data from the leading IT consulting firms. Firms need not to focus on knowledge repositories but find alternative better practices for knowledge management (Malone, 2002). On the other hand, knowledge stored in knowledge repositories is often not used by workers due to the unusable form of its storing (Pasman, 2009). In the multinational corporations control system which explicitly applies knowledge development as

(21)

15

a performance evaluation criterion, can help establish close relations with the local customers and acquire customer‘s knowledge (Anderssona, Björkmanb & Forsgrena, 2005).

McAdam (2004) identified the critical TQM as a key factor in the organization‘s culture which can help to develop the meaningful knowledge creation process. He found that TQM and knowledge creation are connected and influence each other. However it should be not a mechanistic TQM but critical TQM which can be adopted to meet the needs of the organization for knowledge creation and idea generation. He also provided a conceptual model which integrates knowledge creation and idea generation using critical TQM principles.

Organizational constructs impact knowledge creation (Malone, 2002). It is important not only create and learn new relevant knowledge but stabilized it and unlearn old knowledge which is more not relevant (Gareis, 2010). On the other hand, what was once judged as not valuable next day can become valuable (Malone, 2002) if the environment or strategic goals of the organization will change.

Social support and information intensity influence knowledge creation. Social supports which workers receive in organization and information intensity are positively related to their perceived knowledge creation (Joe, 2010). There is also problem of forgetting, not using or ignoring knowledge obtained in the past by incidents (Pasman, 2009). Organizations must learn not only form their success but also form failures (Krogh et al., 2001).

2. Knowledge creation

Knowledge creation is the best way for the organizations to increase their knowledge asset and this makes it very important for the organization. Knowledge asset is not static, it changes with the time and it is a vital task for the organization to keep its current knowledge actual and valuable. Nonaka et al. (2000) described the process of knowledge creation as a spiral process of continuous transformation of existing knowledge into a new knowledge. This famous model consists of three elements: the SECI process (Socialization, Externalization, Combination, and Internalization) converting of tacit and explicit knowledge; the ‗ba‘ – space for knowledge creation; knowledge assets, the inputs and outputs of the knowledge creation process, and the moderators of the process. The pushing power for the knowledge creation process is dialectical thinking. Opposite the Western managers‘ traditions who were taking the organization as a problem solving unit which processes information in order to solve a given task, Nonaka et al. (2000) viewed the organization as an organism which creates and defines

(22)

16

problems, creates new knowledge to solve them and develops new knowledge while solving the problem. Organization not only processes information and knowledge but interacts with environment, continuously creating knowledge, changing environment and, sometimes, itself (Nonaka et al., 2000).

Knowledge can be created trough the interaction between explicit and tacit knowledge, among individuals or among individuals and environment. It is important to note that transformation of tacit and explicit knowledge is bidirectional: tacit knowledge can be transformed into explicit knowledge and explicit knowledge can be transformed into tacit knowledge. The SECI process, its phases and transformation between tacit and explicit knowledge are shown in Figure 4 (Nonaka et al., 2000).

Socialisation is converting existing tacit knowledge into new tacit knowledge. Tacit knowledge is difficult to express and share and often is time, cultural and space specific. It can be acquired through shared experience, informal communication, spending time together.

Tacit knowledge can be shared and acquired without language. Learning-by-observing and learning-by-doing are typical ways to share tacit knowledge in an apprenticeship. Informal interaction between individuals, customers or suppliers is used as a way to acquire the tacit knowledge. Individuals empathise with their co-workers, customers and suppliers reducing barriers and increasing mutual trust between individuals (Nonaka et al., 2000).

Externalisation is a process of articulating tacit knowledge into explicit knowledge.

When tacit knowledge become formed and shaped in an individual‘s mind, it can be expressed and shared with others. This can be done by using of analogy, metaphors and experience sharing. It also happened when on-field experience and tacit knowledge make improvements on the manufacturing process. But, as mentioned above, not all tacit knowledge can be expressed or shared (Nonaka et al., 2000).

Combination is the process of combining existing explicit knowledge into more complex and sophisticated explicit knowledge. Knowledge from inside and outside of the organization can be used for this process, reconsidered, sorted, edited, categorised, shaped and connected into new explicit knowledge. Then it can be spread within the organization for further use. Modern computer technologies made this process faster and easier. For example, communication technologies can support this process allowing workers access to the organization‘s knowledge database (Nonaka et al., 2000).

(23)

17

Figure 4 The SECI Process

Note. From ―SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation‖, Long Range Planning, 33, p. 5-34.

Internalization is the process of embodying explicit knowledge into tacit knowledge.

Individuals in organization acquire explicit knowledge which is shared within organization and convert it into tacit knowledge. By learning the rules and steps of the new manufacturing process, visiting seminars and conferences, reading manuals about new software used by company, workers learn and convert this explicit knowledge into tacit knowledge. Then this enriched individual‘s tacit knowledge can initiate a new turn of the knowledge creation spiral.

Described above processes have their analogues with the organizational theory. Socialization is connected to organizational culture, internalization has connection to organizational learning and combination is embedded in information processing, but externalization is not well developed concept yet (Nonaka et al., 2000).

Furthermore, Nonaka et al. (2000) distinguished specific sub factors for each of the four types of knowledge creation process. Socialization consists of four sub factors: the mere

(24)

18

accumulation of tacit knowledge, the gathering of social information internal to the organization, the gathering of social information outside the organization in a broader societal context, and finally the transfer of tacit knowledge from the master to the team members.

Externalization consists just from one big factor but it is very important, because this process realises the practical benefits from tacit knowledge held by individuals and organization.

Combination consists of three sub factors: the integration, the synthesis and dissemination of existing knowledge into better structurally organized forms for broad dissemination.

Internalization consists of two sub factors: personal experience in which knowledge is acquired from real world experiences, and simulation and experimentation in which knowledge is acquired from the virtual world (Nonaka et al., 2000).

Knowledge creation starts in the individual level and expands into group level, organizational level and inter-organizational level. So does the ‗knowledge creation spiral‘, that is shown in Figure 4.

Knowledge needs a context to be created. Nonaka named this context ‗Ba‘ and defined it as a shared physical context where knowledge is shared, created and used. Ba provides the energy and place for the communication of individuals. Ba is the place where individuals can find context, put information into this context and therefore create knowledge. Ba includes not only space but also time. So it also provides time-space specific context for knowledge creation.

The main characteristic of Ba is ‗interaction‘. Similar to the knowledge creation process which is not constant but a dynamic process, Ba is a changing space, it settles the boundaries for interaction and these boundaries can be extended by bringing a new meaningful shared context into it. For knowledge creation, close interaction and mutual trust among participants is important and Ba provides a space and time where knowledge of area is concentrated, shared and transformed. Figure 5 shows the interaction of individual and shared context in Ba (Nonaka et al., 2000).

To make the knowledge creation process work and to give the energy to Ba, knowledge assets are needed. Knowledge assets are inputs, outputs and moderating factors for the knowledge creation process. Similar to the knowledge creation process, they are not constant but dynamic. Nonaka divides knowledge assets into four types: experiential knowledge assets, conceptual knowledge assets, systemic knowledge assets and routine knowledge assets.

(25)

19

Figure 5 Ba as Shared Context in Motion.

Note. From ―SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation‖, Long Range Planning, 33, p. 5-34.

Experiential knowledge assets are made of shared tacit knowledge. Emotional knowledge, know-how and skills, care and trust are examples of experiential knowledge assets.

These assets are built inside the organization through the sharing hands-on experience among workers, workers and customers and suppliers, as they are built of tacit knowledge, these are tacit organization-specific assets.

Conceptual knowledge assets are built of explicit knowledge and can be expressed by images, documents and language. They are concepts held by organization‘s workers and customers. Perception of brand by customers, understanding organization‘s vision and perspectives by workers are examples of conceptual knowledge assets.

Systemic knowledge assets consist of systematised explicit knowledge. Product specification, manuals, technology process, licenses and patents are examples of these assets.

These are most visible and tangible knowledge assets.

Routine knowledge assets are tacit knowledge which is embedded into routines, practices and actions of the organization. These are practical knowledge assets which are used in day-to-day actions. They are shared by continuous practicing and exercising (Nonaka et al., 2000).

(26)

20

(1) Knowledge creation and innovation

Other studies have learnt how existing processes and methods can influence knowledge creation, idea generation and innovation in the organization (McAdam, 2004) and how knowledge creation is related to innovation (Popadiuk & Choo, 2006). Organizations need to learn continuously and the objectives of this learning are continuous quality improvement of organizations processes, routine and daily business, and promotion of innovations in organizations (Gareis, 2010). Organizations can benefit from taking a proactive approach to its knowledge rather than just letting it be passive. (Krogh et al., 2001).

Hoegl and Schulze (2005) tested which well known knowledge management methods are used by firms to support new product development. Informal events, experience workshops and experience reports are the most known and deployed ones. Firms were also satisfied more with effects of informal events and experience workshops when they used these methods to support new product development. Among ten most popular and used methods, eight are focused on combination and externalization. This shows that modern methods aimed on explicit knowledge and very few emphasize using of tacit knowledge. The fact that the organizations are not completely satisfied with the existing methods outlines gaps which need to be filled with the more sophisticated methods to support new product development. For collaborative new product development knowledge integration is important (Kleinsmann &

Valkenburg, 2010). Human oriented methods are more effective for socialization while system oriented methods are more effective for combination (Choi & Lee, 2002). Factors which can be enablers or barriers for collaborative new product development are divided in three levels:

the actor, project and company. The equality in language used between the actors, the ability of an actor to make a transformation of knowledge, the efficiency of information processing, the quality of project documentation, the allocation of tasks and responsibilities are the most important of them. R&D intensity of the firm and personnel qualification has a strong relationship with firm‘s ability for innovation and new product development (Caloghirou, Kastell & Tsakanikas, 2004). Chen and Occen (2000) made a knowledge bases decomposition of the new product design process. They proposed decomposition and further integration of knowledge in order to create new knowledge. Decomposed knowledge from different sources was put into a blackboard system, and then expert designers organized and integrated this knowledge to create a new knowledge about product design. They distinguished three spaces

(27)

21

for knowledge flows and integration: problem space, knowledge space and solution space.

Baba and Nobeoka (1998) showed how modern information technologies can play a central role in the knowledge-based product development. They regarded 3-D CAD systems not only as a tool but as a key element in a firm‘s product development activities. Visualization of the components, pre-assembly capability, simulation capability and other features help to diminish errors, simplify the process of product development and give more space for creativity, especially in the automobile and aircraft industries. These models contribute to adductive reasoning process which is important in product development.

Marz, Friedrich-Nishio & Grupp (2006) developed an evolutionary simulation model to test performance of innovative and imitative strategies of knowledge creation. Their founding show that in a long term perspective, imitative strategy can be more economically successful and even in high innovative industries there is place for imitating strategy.

Knowledge creation has a strong connection with innovation. One of the keys to producing innovation is how organization can organically network knowledge created inside and outside the organization and acquire the synthesizing capability through dialectical leadership it need to generate new knowledge (Kodama, 2005). Leaders and managers have to understand the situation, see what knowledge assets are available and what knowledge assets they are lacking to bring this information to the knowledge creation teams and give them directions according to the knowledge vision of the organization (Nonaka et al., 2000).

Innovation includes novelty, implementation or commercialization. If the new knowledge or an idea failed to be developed and transformed into a product, service or process it is not classified as innovation. Socialization and internalization have a positive impact on the novelty of product ideas, whereas externalization and combination have a negative impact on the novelty of product ideas. (Schulze & Hoegl, 2008). Knowledge about market needs is one the necessary components of the innovation process (Popadiuk & Choo, 2006). From the evolutionary point of view, adopting of random innovation by workers will lead to changes in all organization that is difficult to predict and might bring not obvious benefits to workers and organization (Allen & Strathern, 2005).

(28)

22

(2)

Collaboration for knowledge creation

Dynamic collaboration between individuals or organizations can lead to the creation of new knowledge (Kodama, 2005). Knowledge sharing in strategic alliances is beneficial for further knowledge exploitation and innovativeness (Caloghirou , Kastell & Tsakanikas, 2004).

Adequate allocation and sharing of resources is important for successful collaboration between organizations. Knowledge creation can be a very expensive, especially in the high technology industries. Collaboration can help to get missing financial, technological and intellectual resources. In the collaborative knowledge creation process, the question is not only how to produce new knowledge but also determine what recourses will be shared (Samaddar &

Kadiyala, 2006; Lin, Yen & Tarn, 2007). Samaddar and Kadiyala (2006) developed and tested a leader-follower collaboration model with the exclusive current knowledge creation efforts and with prior knowledge creation efforts. Combination of current and previous efforts showed to be the most productive. For the formation and continuation of the collaboration, it is important to maintain the optimal ratio between organizations‘ marginal gains included in collaboration. Collaboration between private organizations and public research institutes and role of the government with its programs and assistance as a possible regulator of this collaboration was studied by Drejer & Jorgensen (2005). Different researches showed that collaboration between private firm and research institutes is productive only in a very few cases. Difference between the goals and type of organizations make this collaboration difficult.

Drejera & Jorgensen (2005) proved the collaboration between firms and public research institutes as a long run challenge which can extend the boundaries of the space for knowledge creation. Firm‘s experience of in-house development has a positive impact on firm‘s capability to acquire external knowledge. It is important for knowledge creation process of the firm to recognize, assess and use information and knowledge from external sources (Caloghirou et al., 2004).

(3) Organizational structure and knowledge creation

Changes of organizational formal structure and incentives influence organizational learning (Gareis, 2010). Centralization or decentralization of system‘s functions might impact ability of firm to integrate and incorporate knowledge strategies of different types. Not only organizational structure but also leaders play an important role in creating networked strategic communities (Kodama, 2005). Kodama (2005) described and analysed the establishing of

(29)

23

networked strategic community in the field of veterinary medicine in Japan and the process of knowledge creation in it. He highlighted three important elements in the formation of networked strategy communities: collaboration (interaction among members, strategic partnership among firms that form this community, interactive information sharing, etc.), embeddedness (the degree to which collaboration is enmeshed in inter-organizational relationships), resonance process of values in community. In the learning based strategic communities, members teach each other and learn from each other. Leadership in networked strategic communities must be decentralized and focused on creative thinking and behaviour.

(4

) Models for knowledge creation

After Nonaka and Takeuchi (1995) presented their SECI model of knowledge creation, many arguments pos and pro this model was proposed (Erden et al., 2008; Martin-de-Castro, Lopez-Saez, & Navas-Lopez, 2008; Tsai & Li, 2007; Schulze & Hoegl 2008; McLean, 2002).

Studies in different industries and countries were conducted to test the completeness and applicability of the model. McLean made a review and evaluation of the Nanaka‘s theory from the viewpoints of applicability, conceptual development, operationalization, continuous refinement, comprehensiveness, operability, practicality, and confirmation of theories. He concluded that the theory is on an emerging stage, it is well-conceptualized, important, precise and clear, contributes to the existing body of knowledge on organizational knowledge creation, but to get to the next step of maturity, theory needs to be operationalized and work towards confirmation or disconfirmation need to be done. Martin-de-Castro et al. (2008) examined firms from the United States and Spain to find if SECI model can be applied to describe the knowledge creation process. Their found that model does not clearly appeal in real management and that knowledge creation process is different in these countries. The firms from America work with tacit knowledge in two different ways which was called by Martin- de-Castro et al. (2008) as ‗two kinds of ‗socialization‘ forms‘. All companies from Spain were focused on using methods which allows externalization and internalization of knowledge, then where was a split between the firms who were focused on combination and the firms who were focused on socialization. These findings can be explained by the difference in knowledge management development in America and Spain, and applying some stages of the knowledge creation process indirectly. Managers therefore should focused not only on the model of knowledge creation but also consider industry, regional, country and cultural factors which

(30)

24

affect the process of the knowledge creation. Choi and Lee (2002) studied Korean firm in order to find the link between knowledge management strategies and the knowledge creation process. Tsai and Li (2007) showed that knowledge creation process can influence firm‘s performance which use new venture strategy. New venture can lead to knowledge mobilization and trigger new spiral of knowledge creation.

Yang, Fang, & Lin (2010) proposed their EICE model as an extension of Nonaka‘s SECI model in order to form a new strategic model for knowledge creation. They categorized exploration, institutional entrepreneurship, combination and exploitation as the dimensions of knowledge creation process and discussed their influence on organizational knowledge assets.

Soo et al. (2002) proposed their own model of knowledge creation in organization based on five factors: the role of the firm‘s network of interactions, the integration of information and knowledge that is acquired with that currently existing in the organization, high quality problem solving processes, the impact of specific organization factors, and the output of the knowledge creation process. They viewed the process of knowledge creation as followed:

information is sourced from internal and external networks and converted in to know-how that is acted upon by decision makers in their daily activities that leads to new knowledge, which increases innovative output and, hence, organization‘s performance.

In knowledge-based economy, computerized models found many implications:

scientific computations, simulation of various technical systems, operational research problems, knowledge engineering and decision support systems, knowledge repositories and knowledge management (Wierzbicki, 2007). In his study Wierzbicki (2007) argued that mathematical modeling should be used for representing and organizing knowledge. To help this, information technology must be human-centered. Combining hard and soft system approaches will give more evident representation of knowledge management than using just one of these approaches. Mathematical modeling can see self-organization and evolution as knowledge creating factors (Allen & Strathern, 2005). Allen and Strathern built several examples of evolutionary market systems and demonstrated how knowledge is constantly created and destroyed in these systems.

(31)

25

3. Knowledge storage

Knowledge storage is important to the organization as if there is no place, method or way to store knowledge, it will be lost and this means the organization loses the time, efforts and money. Newly created knowledge needs to be stored as well as existing organizational knowledge. There are several ways and methods to store knowledge and make it stay in organization. Storytelling, organizational culture, manufacturing processes, knowledge repositories, documents, manuals, and patents are just some examples of them. Not all of them are suitable for every organization and for every type of knowledge. For example, tacit knowledge will be better stored in the organizational culture than manuals or patents, if storytelling is not used as a common tool in the organization, it will be useless to make an effort to store knowledge in some story, if there is an knowledge management system in the organization and employees are used to use it, then obvious this system will be a great place to store organizational knowledge (Encyclopedia of Knowledge Management, 2006).

If organization will not store its knowledge, and knowledge will be stored only in individuals mind, organization can lose this knowledge if the individual will leave the organization. To avoid these, organizations must convert individual knowledge into organizational knowledge. There is another reason to store knowledge: not all knowledge in organization is used simultaneously, newly created knowledge might be used not completely but only the part of it which is crucial today, another part can be needed with time and if it is not stored, then the organization needs to spend time and efforts to recreate it again (Encyclopedia of Knowledge Management, 2006).

4. Knowledge transfer

Knowledge transfer leads to the exchange of knowledge among individuals, groups, organization and beyond organization‘s boundaries. Both tacit and explicit knowledge can be transferred, though tacit knowledge is more difficult to transfer than explicit knowledge due to its deep interconnections with one who posses this tacit knowledge. Knowledge transfer is a very important process, as without it we will have only our personal knowledge, and when meeting some problem, we will need to create the knowledge which is needed to solve this problem by ourselves even somebody else has solved this problem before. This is endless invention of the wheel. Knowledge transfer is the basic principle of learning and human‘s

(32)

26

knowledge was transferred through the centuries building up civilization (Encyclopedia of Knowledge Management, 2006).

Knowledge transfer includes the source and recipient. To send knowledge doesn‘t mean to transfer it, the recipient needs not only receive knowledge but also to understand it. Without understanding knowledge, it will not be possessed by recipient. To write a manual or to show how to work with the new software is just a part of knowledge transfer, it should be done in the way the recipient will understand and will be able to use this knowledge by him.

In transferring tacit knowledge, mutual trust between the source and the recipient is very important. Willingness of the source to transfer knowledge and readiness of the recipient to receive knowledge should match in place and time. Having a knowledge transfer experience is also important to transfer tacit knowledge (Encyclopedia of Knowledge Management, 2006).

Lack of motivation can cause the fail of knowledge transfer. Obviously organization is interested in its workers transferring knowledge but not always workers want to transfer valuable knowledge to others. The motivation need to be used to encourage knowledge transfer. Some of the workers are self motivated, they want to be useful and contribute to the organization‘s success, being recognized as experts and asked for an advice or help in solving difficult problem, others need to be stimulated by managers or organization‘s policies to be involved into knowledge transfer as a source or as a recipient. It also can be opposite and the recipient will play passive role in knowledge transfer as he or she might not be interested in transferred knowledge or he or she thinks that the source is unqualified (Encyclopedia of Knowledge Management, 2006).

Communications channels can enhance knowledge transfer. Use of modern IT, video and audio conferences, e-mails, online forums and chat rooms make knowledge transfer possible for the individuals who are located in different places. Choosing the proper communication channel to transfer knowledge will also influence its effectiveness. Sometimes face-to-face communication can be replaced by other way of communication and save time for knowledge transferring.

Individuals and organizations have to pay attention to all of these factors to make knowledge transfer productive, effective and successful.

The success of knowledge management depends on knowledge sharing (Wang & Noe, 2010; Yang & Wu, 2008). Knowledge sharing is a part of knowledge transfer process.

中 華 大 學 博 士 論 文