Degreeproject ManagingKnowledgeforInnovationinSMEs:theroleofDigitalTechnologies

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Degree project

Managing Knowledge for Innovation in SMEs: the role of Digital Technologies

Author: Zihan Song

Supervisor: Niki Chatzipanagiotou

Examiner: Associate Professor Päivi Jokela Date: Spring Semester 2020

Subject: Informatics Level: Master (30 credits)

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Abstract

This master thesis research aims to explore and interpret the perceptions of knowledge workers of small-medium enterprises (SMEs) in the Chinese context in regards to managing innovation in their knowledge work with the support of digital technologies.

A literature review formed the theoretical basis of this work by presenting its main concepts of knowledge, knowledge work and knowledge workers, innovation in knowledge work and digital technologies used in support of knowledge work. The literature review along with Socialization, Externalization, Combination and Internalization (SECI) model, initially proposed by Nonaka in 1994 and expanded by Nonaka and Takeuchi in 1995, formed the theoretical framework of the research which were used to discuss the research findings.

The interpretive qualitative research included data that was collected through semi-structured face-to-face individual and group interviews. The collected data was analysed by using thematic analysis, which yielded the following themes about the Chinese SMEs knowledge workers’ perceptions regarding innovation in the four conversion process from tacit to explicit knowledge: (1) ‘Make the contact’: innovation in the conversion from tacit to tacit knowledge, (2) ‘Associate by metaphors’: innovation in the conversion from tacit to explicit knowledge, (3) ‘Analyse and synthesize’: innovation in the conversion from explicit to explicit knowledge, (4) ‘Learn from practice’: innovation in the conversion from explicit to tacit knowledge; and how innovation in the four conversion modes can be supported by digital technologies: (5) In the process of socialization, synchronous collaboration tool can support ‘make the contact’, (6) In the process of externalization, mind mapping software and office drawing software can support ‘associate by metaphors’, (7) In the process of combination, database system and professional software can support ‘analyse and synthesize’, (8) In the process of internalization, database system, asynchronous collaboration tool and mind mapping software can support ‘learn from practice’.

The findings show that knowledge workers’ active interaction with knowledge, supports the conversion from tacit to explicit knowledge back and forth. This assists the creation of new knowledge and, therefore, innovation in knowledge work; digital technologies play a supportive role in managing innovation in employees’ daily knowledge work. This master thesis research contributes to the current body of knowledge within informatics by empowering knowledge workers to share their viewpoints in regards to managing innovation in their knowledge work with the support of digital technologies. Knowledge workers’

process of converting tacit to explicit knowledge promotes to achieve innovation in the corresponding four knowledge conversion modes, which deepens the understanding of the formation mechanism of innovation in the knowledge work. In addition, the discussion on the supportive role of digital technologies in the innovation process of knowledge work enriches and extends the existing body of knowledge and provides some valuable insights for the use of digital technologies in knowledge work to promote innovation. The conclusions of this master thesis research provide new ideas to be examined for the management of innovative practices and the application of digital technologies in knowledge work.

Keywords

Digital Technologies, innovation, knowledge, knowledge work, knowledge workers, knowledge conversion, SECI model.

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Acknowledgements

Considering that this master thesis study was conducted during the corona virus pandemic which added to the effort needed for its completion, I would like to thank the following people; without your support and help, this master thesis study could not be completed.

First of all, I would like to thank Niki Chatzipanagiotou for being my supervisor. She is a responsible and resourceful scholar who has provided me with valuable guidance. We had many inspiring discussions where she offered me suggestions that enabled the process of my master thesis work step-by-step. Without her encouragement and her weekly detailed comments, this master thesis study could hardly be finished.

Also, I would like to acknowledge my examiner Päivi Jokela, who set the basis of the master thesis work and commented on my work in the seminars, so that I was able to successfully complete the master thesis. Another person that I would like to acknowledge is my module leader Anita Mirijamdotter, who kindly allowed me to conduct my master thesis in the Chinese context and also gave me many advices for improving parts of my work. Furthermore, I would like to thank Ali Hamidi, who facilitated the connection between students and teachers and provided useful suggestions during the master thesis writing process.

I would like to also express my special thanks to all the people working at the environmental testing enterprise, where the master thesis research was conducted, who generously offered me their time to collect the empirical material for my research. Even though we had to wear surgical masks as a protection during the interviews, due to the corona virus situation, it did not interfere with our interesting discussions.

Last but not least I would like to express my love and gratitude to my family in China for their patience, support and encouragement.

Zihan Song

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List of figures and tables

Figure 1: Master thesis organization...5

Figure 2: The DIKW hierarchy...8

Figure 3: Knowledge conversion...19

Figure 4: Thematic analysis process...26

Figure 5: A summary graphic of digital technologies’ supportive role in regards to managing innovation in their knowledge work………...36

Figure 6: The employees’ perceptions regarding innovation in knowledge work………59

Figure 7: The supportive role of digital technology for ‘make the contact’……….59

Figure 8: The supportive role of digital technology for ‘associate by metaphors’...59

Figure 9: The supportive role of digital technology for ‘analyze and synthesize’...60

Figure 10: The supportive role of digital technology for ‘learn from practice’...60

Table 1: Knowledge typologies and examples...12

Table 2: Examples of digital technologies used in the Chinese SME and their basic functions used in knowledge work...15

Table 3: Research participants...25

Table 4: The interview arrangement...25

Table 5: The answer to the 1^stresearch sub-question...35

Table 6: The answer to the 2^ndresearch sub-question...35

Table 7: The answer of the main research question...36

List of abbreviations

IS Information Systems SMEs Small-Medium Enterprises

KM Knowledge Management

KMS Knowledge Management System DIKW Data-Information-Knowledge-Wisdom

SECI Socialization, Externalization, Combination and Internalization

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CHAPTER 1 Introduction

Chapter 1 provides the introduction for this master thesis by presenting the background of the research and its main concepts. After this, the purpose of the research study and the research questions are presented. The previous studies and topic justification are discussed to state the reason of selecting this topic. The chapter concludes with the scope and limitations of the study, along with a presentation of its disposition.

1.1 Introduction and research setting

The extended use of digital technologies has created new avenues in knowledge management that could play a significant role in meeting the prevailing challenges related to sharing, exchanging, and disseminating knowledge (Abdulsalam et al., 2016). Digital technologies are tools that allow information and knowledge exchange, as well as work execution by integrating information, documents and employees (Lopez-Nicolas and Soto-Acosta, 2010).

The potentials of digital technologies, including the multimodal, communicative, and revisable nature of digital artefacts, support knowledge innovation activities (Chai et al., 2014). The need for innovation has become important for enterprises’ longevity in the market and innovation has been recognized as an engine for growth (Simao and Franco, 2018).

Knowledge is defined as a justified belief that increases an entity’s capacity for effective action (Nonaka, 1994). It is seen as a possession of the human mind and is treated as mental capacity or resource that can be developed, applied and used to improve effectiveness in the workplace (Newell et al., 2009). Knowledge work is characterized by certain knowledge actions and different roles that knowledge workers take on (Nonaka and Takeushi, 1995).

Knowledge work is defined as the combination of the understandings that are possessed by individuals or collectives, including knowledge possessed not simply in the brain and body of the individual but also in organizational routines, and the actual interactions with other actors in a particular knowledge work situation (Newell, 2015). Knowledge work, in this master thesis, refers to work based on certain knowledge and the situated work practice that produces knowledgeability. Knowledge workers are those employees who play the main role in managing knowledge work. Hence, knowledge in organizations can be understood as a learned set of norms, shared understandings and practices that integrate actors and artefacts to produce valued outcomes within a specific social and organizational context (Scarbrough, 2008).

Nowadays, not only management work of the enterprises has become a knowledge-intensive work, but also the production work has become a knowledge-intensive work. The work assigned to employees by the enterprises is no longer the task itself, but better integration of work tasks, individual knowledge, and information technology. In developing countries, small-medium enterprises (SMEs) have a larger share than in developed countries. SMEs are also said to be responsible for driving innovation and competition in many economic sectors (Aga et al., 2015). The strength of small and medium-sized enterprises (SMEs) lies in motivation, good network, tacit knowledge in unique skills, shorter informal communication, less bureaucracy, greater proximity to market and to be innovative (Ngah and Jusoff, 2009).

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Innovation consists of the generation of a new idea and its implementation into a new product, process or service, leading to the dynamic growth of the innovative business enterprise (Popadiuk et al, 2006). Thompson (1965) defined innovation in a simple way as ―the generation, acceptance and implementation of new ideas, processes, products or services. The essential element of innovation is the creation of new knowledge according to Drucker (1993).

Knowledge is very significant in the innovation process since it represents not only important input but also the output of the transformation process (Urbancova, 2013). Innovation is mainly based upon the continuous dynamic exchange between tacit and explicit knowledge (Nonaka and Takeuchi, 1995) and it requires the conversion of knowledge into new products, processes, and services as well as the successful diffusion of these inventions into society and/or market. Hence, innovation in knowledge work, in this master thesis, implies the process of creating new knowledge through knowledge worker’s interaction in knowledge conversion (Nonaka and Takeuchi, 1995; Newell, 2009). Continuous innovation requires a well-planned system of managing knowledge and an appropriate organisational environment that enables an enterprise to excel in technological, market and administrative knowledge creation (Easa, 2012). This is particularly relevant for SMEs; managing knowledge for innovation can be a challenge for SMEs due to their smallness, limited resources and capabilities (Bouncken and Kraus, 2013).

The research setting is that of a small-medium enterprise (SME) located in China which has a long tradition in environmental testing. The specific enterprise has forty-two employees. The employees are considered knowledge workers since their work evolves around managing knowledge work. The enterprise has implemented digital technologies to support their work.

Hence, the employees’ work primarily takes place with aid of technology. The research problem relates to how the employees of the Chinese SME manage innovation in their knowledge work and what is the role that digital technologies play in this.

Previous research focuses mainly on the role of digital technologies in knowledge creation as a monolithic concept, for example, as “communities”, “knowledge storage” and “sharing implicit and explicit knowledge” (Lee and Kelkar, 2013). This master thesis research, thus, aims to extend existing work by conducting a qualitative research to uncover employees’

perceptions in regards to managing innovation in their knowledge work and how this is supported by digital technologies.

1.2 Purpose statement and research questions

The purpose of this master thesis is to explore how employees in small-medium enterprises (SMEs) in the Chinese context manage innovation in their knowledge work with the support of digital technologies. Therefore, the master thesis aims to explore and interpret the perceptions of employees in Chinese SMEs in regards to managing innovation in their knowledge work and how this is supported by digital technologies. By exploring the role that digital technologies play in managing innovation in knowledge work, this master thesis research aims, subsequently, at providing suggestions on how to use digital technologies for such purpose more effectively.

The focus is on knowledge, knowledge work and knowledge workers, digital technologies, innovation and SMEs. The SECI (Socialization, Externalization, Combination and Internalization) model, initially proposed by Nonaka (1994) and expanded by Nonaka and Takeuchi (1995), is used as a theoretical framework for exploring the role of digital technologies in the innovation process in knowledge work. Digital technologies, in this master thesis, refers to tools that support employees’ knowledge work within the above four

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processes of socialization, externalization, combination and internalization, such as database system (semantic organization tools), office drawing software (graphical representation tools), mind mapping (thinking representation tools) and multimedia conference system (sync collaboration tools). The research will be conducted among employees/knowledge workers of a Chinese environmental testing SME that uses digital technologies to support their knowledge work.

From the above, the following main research question and some sub-questions are formulated:

1. How do employees in Chinese SMEs perceive the role of digital technologies in regards to managing innovation in their knowledge work?

1a. How do employees in Chinese SMEs perceive innovation in their knowledge work?

1b. What role do digital technologies play in managing innovation in the employees of Chinese SMEs knowledge work?

1.3 Previous studies

There is a large body of literature in the field of informatics with studies on: (a) digital technologies, especially research about the effects on SMEs (e.g. Lopez-Nicolas and Soto- Acosta, 2010), (b) knowledge work, where research includes all stages of knowledge, i.e.

knowledge creation, knowledge sharing, knowledge dissemination (e.g. Lee and Kelkar, 2013;

Berraies and Chaher, 2014) and (c) innovation, with research that analyzes the connection between knowledge work and innovation (e.g. Swan et al., 2000; Majchrzak et al., 2004;

López-Nicolás and Meroño-Cerdán, 2011; Parida et al., 2012; Valdez-Juárez et al., 2016 ).

Digital technologies investment in SMEs continues to grow because these technologies are being applied more and more to conducting business activities within the enterprise’s boundaries and with external business agents such as customers, suppliers, and business partners (Lopez-Nicolas and Soto-Acosta, 2010). However, with the continuous development of technology, various types of digital technologies have emerged that integrate various functions. Lopez-Nicolas and Soto-Acosta (2010) investigated the influence of the adoption and use of digital technologies on organizational learning. Their focus is on knowledge creation, as an articulated construct for organizational learning, and the SECI (Socialization, Externalization, Combination and Internalization) model is used as a reference for knowledge creation (Lopez-Nicolas and Soto-Acosta, 2010). Their results, based on a sample of around 300 Spanish SMEs, indicate that digital technologies have a positive influence on the four processes for creating knowledge (Lopez-Nicolas and Soto-Acosta, 2010). Their research also suggests some future research directions, such as studying the role of digital technologies in knowledge creation of SMEs in different countries, researching companies from different industries, and exploring the interplay of different types of digital technologies and those other resources supporting knowledge creation.

Berraies and Chaher (2014) focused on knowledge creation process by referring to the SECI model. Their literature review reveals that researchers who examined the relationship between the four modes of knowledge creation and firms’ innovation integrating the SECI model found controversial empirical results (Berraies and Chaher, 2014). The limitation of their research is that it only examines digital technology companies, which can be extended to companies in different industries. Additionally, Lee and Kelkar (2013) through their research in which they also applied the SECI model, they found that digital technologies use was prevalent in the various phases of the SECI model besides the more traditional uses such as storing and retrieving data.

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Valdez-Juárez et al. (2016) explore the ability of knowledge management to achieve SME innovation and business performance. They argued that, although SMEs have certain practices for the acquisition of knowledge, it is important that new actions and strategies are considered, such as the use of digital technologies (Valdez-Juárez et al., 2016). Also, they suggested that the level of influence of innovation on performance in SMEs is relatively low, most of these companies have serious limitations in their organizational and financial management, causing a poor capacity to innovate (Valdez-Juárez et al., 2016).

In López-Nicolás and Meroño-Cerdán (2011) research, it was found that innovation process highly depends on knowledge, especially on tacit knowledge. New and valuable knowledge is created and converted into products, services and processes by transforming general knowledge into specific knowledge. Swan et al. (2000) state that exploration through knowledge sharing allows the development of innovation, whereas Majchrzak et al. (2004) concluded to a positive impact of explicit knowledge reuse for radical innovation.

The study of Parida et al. (2012) has made an effort at contributing to the literature in technology and innovation management and small business by advancing our knowledge regarding the effects of open innovation activities in the context of SMEs. Their research provides a wider thinking direction about managing innovation with the support of technology.

1.4 Topic justification

This topic is relevant for informatics research theory and informatics practice, as well as for the knowledge management field. The exploration of digital technologies as a means of supporting knowledge work has proven an interesting research topic (Lopez-Nicolas and Soto-Acosta, 2010; Lee and Kelkar, 2013; Berraies and Chaher, 2014). At the same time, there has been a strong focus on how enterprises can learn from knowledge (Swan et al., 2000;

Majchrzak et al., 2004; López-Nicolás and Meroño-Cerdán, 2011; Parida et al., 2012; Valdez- Juárez et al., 2016).

However, there are a few studies that examine innovation in knowledge work with the support of digital technologies from the SMEs employees’ point of view. According to López-Nicolás and Meroño-Cerdán (2011), there is strong relation between managing knowledge and innovation. In knowledge work, no matter what kind of post innovation, no matter what form of innovation, its essence is the creation of new knowledge. It originates from the interaction between different elements and the mutual conversion between different types of knowledge.

The origin of its generation lies in the interaction of knowledge conversion. Through knowledge innovation, an enterprise can develop its core competence by integrating explicit knowledge and tacit knowledge acquired in and out of the enterprise (Fan, 2017). However, the employees/knowledge workers’ ‘voice’ in previous research has not been adequately heard. So, this master thesis aims at exploring and interpreting the perceptions of employees in Chinese SMEs in regards to managing innovation in their knowledge work and how this is supported by digital technologies.

1.5 Scope and limitations

The purpose of this master thesis is to explore and interpret the employees of Chinese SMEs perceptions in regards to managing innovation in their knowledge work with the support of digital technologies. The master thesis study concerns employees within a specific organization in China, an environmental testing enterprise. The selected employees are mainly dealing with knowledge work with the support of digital technologies. These knowledge

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workers have different work attributes and, consequently, they use various digital technologies.

The research study will be conducted in the Chinese language. That is, the interviews of the participants will be conducted in the Chinese language as to offer the participants the freedom to express themselves in their native language. In addition, the documents that may be provided by the participants or the enterprise will also be in Chinese. Finally, my -the researcher’s- interview notes will be in the Chinese language as well as this is my native language too. Thus, all the aforementioned empirical material will be translated in English.

This process should be careful to prevent ambiguity due to different language contexts. Since the master thesis will be written in English, this is considered a complication because the translation into the English language will delay the process of conducting and reporting the findings.

Another limitation is related to the theoretical framework adopted. Every theoretical model suffers from limitations to its generalizability; for that, I have presented a brief summary of the SECI critiques in the literature review chapter.

There is considerable variety among Chinese SMEs, depending on their size and organizational culture. Therefore, generalizations from the research results cannot be made about all Chinese SMEs, but the research results could be applied to Chinese and other SMEs with similar size, regulations and organizational culture.

1.6 Thesis organization

This master thesis is organised in six chapters. A graphical representation of the master thesis disposition can be seen in the following Figure 1:

Figure 1. Master thesis organization

Chapter one introduced the research topic, the purpose, aim and research questions of the research study. The choice of the selected topic was justified and the limitations of this research study were presented.

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Chapter two consists of a literature review that serves as a presentation of the main concepts of this master thesis. That is, knowledge, knowledge work, innovation in knowledge work, and digital technologies used for the support of knowledge work. The theoretical framework, which is adopted from Nonaka’s knowledge creation theory, the SECI model is presented.

Chapter three presents the methodology of this research study. This constitutes of the adopted philosophical tradition (paradigm), the methodological approach and the methods used for data collection and data analysis. Reliability, validity and ethical considerations of the research are also presented in this chapter.

Chapter four presents the findings of the thematic analysis that was applied on the collected data. This includes each of these findings in greater detail supported with quotations from the participants’ interviews that serve as proof of the analysis correctness.

Chapter five constitutes a discussion of the empirical findings presented in previous chapter.

This involves the findings grouped together with the research question that they are set to answer and discussed with the help of the adopted theoretical framework. A summary graphic of all findings seen as a whole is also presented in this chapter.

Chapter six presents the conclusions of the master thesis research including the researcher’s own reflections about who will benefit from this research study as well as suggestions for future research.

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CHAPTER 2 Review of the literature

Chapter 2 consists of the literature review that serves as a presentation of the main concepts of this master thesis. That is, knowledge, knowledge work, innovation in knowledge work, and digital technologies used for the support of knowledge work. The theoretical framework, which is adopted from Nonaka’s knowledge creation theory, SECI model is presented. The way SECI model is used for analyzing the conversion between tacit knowledge and explicit knowledge is discussed, in order to provide a model for investigating the role of digital technologies in managing innovation in knowledge work.

2.1 Search strategy

The literature review included a variety of literature resources from Linnaeus University Library such as scientific books, scientific journals, conference proceedings and dissertations.

That is, databases such as ACM and Springer, were used to find material for this master thesis literature review. In the specific databases, I searched for scientific journals included in the basket of eight of informatics field. More specifically, the following journal titles were used:

MIS Quarterly, Information systems research, Journal of Management Information Systems, Information systems journal, European journal of information systems, European journal of association for information systems, Journal of information technology, Journal of strategic information systems. Other online search engines including Google and Google Scholar were also used for the same purpose.

For my search, I used the following keywords which aided in the retrieval of literature material for this master thesis’ literature review: Knowledge, knowledge work, knowledge workers, knowledge creation, innovation, small medium enterprises (SMEs), digital technologies, information tools, information systems. For the aforementioned keywords, I used Boolean ^1T1Tsearch, which allowed me to combine keywords with operators such as AND, NOT and OR to further produce more relevant results. For example, “knowledge work” AND

“innovation”.

The following inclusion-exclusion criteria were used for the literature search. Only literature where the full text version is available was included. Within the time available, not all search results could be read in detail and literature was then selected based on abstract content that was mainly focused on the relevancy to the field of informatics and the topic of the specific research.

2.2 What is knowledge, knowledge work and knowledge workers?

The question of defining knowledge has occupied the minds of philosophers since the classical Greek era and has led to many epistemological debates (Alavi and Leidner, 2001). A commonly held view with minor variants is that data is raw numbers and facts, information is processed data, and knowledge is authenticated information (Machlup 1980). The Data- Information-Knowledge-Wisdom (DIKW) Hierarchy (Ackoff, 1989; Rowley, 2007) is the most common hierarchy in the informatics literature, which is presented in Figure 2 below.

The hierarchy, which refers to variously as the ‘Knowledge Hierarchy’, the ‘Information Hierarchy’ and the ‘Knowledge Pyramid’, is one of the fundamental, widely recognized models in the information and knowledge literature (Rowley, 2007). Ackoff (1989) argues that, although there is a tendency to use the concepts of data, information, knowledge and

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wisdom interchangeably, not only they are different but they also form a hierarchy of increasing value. In this context, the DIKW concepts are defined as following: Data are symbols that represent properties of objects, events and their environments (Ackoff, 1989;

Rowley, 2007). Information is processed data (Ackoff, 1989; Rowley, 2007) endowed with meaning, relevance and purpose. Knowledge is know-how, and application of data and information to answer how questions. Knowledge can be obtained either by transmission from another who has it, by instruction, or by extracting it from experience (Ackoff, 1989; Rowley, 2007). In this context Davenport and Prusak (1998) view knowledge as a mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. Wisdom is defined as the experience-based capability to derive a deep and profound level of understanding of patterns or key relationships critical to an activity (Nonaka, et al., 1994). Wisdom is the ability to increase effectiveness (Ackoff, 1989). While, Tuomi (1999) makes the argument that the often-assumed hierarchy from data to knowledge is actually inverse: knowledge must exist before information can be formulated and before data can be measured to form information.

Figure 2. The DIKW hierarchy (Rowley, 2007)

Knowledge is supported by the flow of information between individuals and develops through experience (McDermott, 1999). Information patterns or knowledge can be explicit, codified, and recorded or they remain tacit to individuals (Nonaka, et al., 1994). Application of knowledge allows us to recognize situations that are similar to past situational patterns through remembered, stored, compared, and retrieved information (McDermott, 1999;

Nonaka, et al., 1994). In an organizational setting, knowledge is the province of most individuals during the normal course of their jobs. They develop a referential experience base that they apply to repeated situations (Davenport, et al., 1998). Knowledge workers call upon this experience base to solve challenges. The organizational challenge is to take data gathered from process conduct, digitize patterns of solutions to create information, and then learn to transform information into knowledge in some way, eventually institutionalizing, internalizing and automating the learned experience in job aids applicable to future work (Lee and Choi, 2003). Thus, the focus of this master thesis is knowledge. In the following paragraph, I present various researchers’ views about knowledge.

According to Plato, knowledge is a “justified true belief”. This objective detached view is a generally accepted assumption in organizational theory developed by Nonaka and Takeuchi (1995), and many other researchers. Nonaka (1994) and Nonaka and Takeuchi (1995) argue that knowledge is a justified belief that increases an entity’s capacity for effective action. In a sense, Plato argued that learning was the process of uncovering what we already know, though at some preconscious level, which is similar to the conversion from tacit to explicit

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knowledge (Spender, 1996, pp. 64-77). Knowledge is defined as a justified belief that increases an entity’s capacity for effective action (Nonaka 1994). Knowledge has been described as a state or fact of knowing with the knowledge to be a condition of understanding gained through experience or study; the sum or range of what has been perceived, discovered, or learned (Schubert et al. 1998).

Polanyi (1969) disagrees that there is an “objective” knowledge, self-contained, detached, and independent of human action. “Knowledge is an activity which would better be described as a process of knowing” (Polanyi, 1969, p.132). Alavi and Leidner (2001) conclude to three major points of knowledge perspective: (1) A great deal of emphasis is given to understanding the difference among data, information, and knowledge and drawing implications from the difference. (2) Taken as a starting point that knowledge is personalized, in order for knowledge to be useful to an individual or a group, it must be expressed in such a manner as to be interpretable by the receivers. (3) Hoards of information are of little value; only information, which is actively processed in the mind of an individual through a process of reflection, enlightenment, or learning can be useful.

Knowledge work is characterized by certain knowledge actions and different roles that knowledge workers take on (Nonaka and Takeushi, 1995; Davenport and Prusak, 1998).

Ruhleder (1994) refers to knowledge work as consisting of tasks in which the dominant activities include: the generation of useful information, dependence by the individual on accessible knowledge, the use of a mental model of process and output, and the need for significant attentional information processing.

According to Newell (2015) knowledge work is defined as the combination of the understandings that are possessed by individuals or collectives, including knowledge possessed not simply in the brain and body of the individual but also in organizational routines, and the actual interactions with other actors in a particular knowledge work situation (Newell, 2015). Knowledge work, in this master thesis, refers to work characterized by certain knowledge and the situated work practice that produces knowledgeability (Nonaka and Takeushi, 1995; Newell, 2015). Knowledge workers are those employees who play the main role in managing knowledge work.

The aforementioned section aims to provide definitions of knowledge, knowledge work and knowledge workers in order to form a basis for this master thesis. For knowledge, several approaches of various researchers were presented to create an overview of the concept. The definition of knowledge by Nonaka (1994) is adopted as the most suitable for the master thesis. For knowledge work, a combined definition of Nonaka and Takeuchi (1995) and Newell (2015) is adopted to show the important role knowledge plays in people’s work of contemporary organizations; to conclude with own definition of knowledge workers.

2.3 Knowledge typologies

In the old Greek times, Hirschheim (1985) pointed knowledge can be divided into doxa and episteme. Doxa refers to that which was believed to be true, and episteme refers to that which was known to be true. Greeks believed that science comprises the process of inquiry which transformed doxa into episteme (Hirschheim, 1985). Deer (2012) argued that doxa also refers to pre-reflexive intuitive knowledge shaped by experience, to unconscious inherited physical and relational pre-dispositions and episteme is the infallible knowledge of reason.

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Aristotle (2000) particularly emphasized three forms of knowledge: episteme, techne and phronesis. Episteme refers to theoretical scientific knowledge that is universal and independent of time and space—in other words, nomothetic. Researchers with a nomothetic ambition search for general causal laws. Techne on the other hand, is a heteronomous and instrumental form of knowledge that is focused on delivering solutions to concrete issues.

Phronesis refers to practical knowledge that is imperative for context-specific judgements (Barker-Ruchti et al., 2014). Phronesis involves the ability to judge how to achieve a certain end and the ability to reflect upon and determine good ends (Petersén and Olsson, 2015).

Ryle (1949, p. 25) makes a distinction between “knowing how” and “knowing what”.

Knowing how is the knowledge which intellectualists fail to reckon with, and their disregard of it ensures that they treat exercises of qualities of mind as “occult episodes”. On the other hand, knowing what refers to certain bits of knowledge in one’s mind. As the vast majority of knowledge creation literature considers knowledge as being of two types explicit and tacit, this master thesis study will provide a background of these two concepts.

Nonaka and Takeuchi (1995) point that explicit knowledge is expressed in the form of words, numbers, sounds, and so on. It is shared in the form of data, scientific formulas, visual graphics, sound tapes, product manuals or manuals. Often explicit knowledge is viewed as being the same as information (Busch, 2008). On the other hand, tacit knowledge is defined as being the opposite of explicit knowledge, the knowledge that cannot be articulated and codified (Nonaka and Takeuchi, 1995).

According to Polanyi (2009), tacit knowledge forms the background necessary for assigning the structure to develop and interpret explicit knowledge. ‘Tacit knowledge’ cannot be expressed in explicit form but can only in some unexplained sense be secreted within the words making up ‘a piece of explicit knowledge’. As he puts it: “… While tacit knowledge can be possessed by itself, explicit knowledge must rely on being tacitly understood …”

(Polanyi, 1969, p.144). This implies that for Polanyi there is always an irreducibly tacit aspect to any explicit knowledge/knowing (Duguid, 2012).

“The ideal of a strictly explicit knowledge is indeed self-contradictory; deprived of their tacit coefficients, all spoken words, all formulae, all maps and graphs, are strictly meaningless.” (Polanyi, 1969, p.195).

For Polanyi tacit knowledge is a dimension of knowledge that is located in the mind of an individual. One starting point for Polanyi (2009, p. 4) is: “...we can know more than we can tell” and, along the same lines, “...nothing that we know can be said precisely” (Polanyi, 1962, pp. 87-88). Accordingly, the basis for Polanyi’s concept of tacit knowledge is that we know more than we are able to communicate to others in the form of information. When tacit knowledge is to be transferred from one person to another, this cannot be done completely by means of either language or images (Cannon, 2002). The transmission of tacit knowledge to an apprentice is an active creative process; it is not one of passive transmission from master to apprentice (Polanyi, 2009). The process of apprenticeship is dependent in part on the apprentice themselves gradually finding out knowledge that the master is unable to transmit, but which becomes apparent through the situation/context at any particular time (Cannon, 2002). According to Polanyi (2009), this method of defining something by pointing out a particular thing or situation is referred to as ostensive definition. For Polanyi (2009), the tacit dimension to knowledge is inaccessible to the conscious mind. He used examples such as a skillful performer to illustrate this, arguing that the knowledge that underlies their

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performance is largely tacit in the sense that they would find it difficult or impossible to articulate what they were doing or why (Kimble, 2013).

Drawing on the work of Polanyi (1962, 1969), Nonaka (1994) explicated two dimensions of knowledge in organizations: tacit and explicit. Tacit knowledge is subjective, bodily, of the here and now, and practice-based, while explicit knowledge is objective, of the mind, and the there and then, and concerned with theory (Nonaka, 1994, p. 16; Nonaka and Takeuchi, 1995, pp. 59, 61). According to Nonaka (1994, p.16), tacit knowledge is difficult to communicate or share, but it is a “rich untapped source of new knowledge”. Rooted in action, experience, and involvement in a specific context, the tacit dimension of knowledge (henceforth referred to as tacit knowledge) is comprised of both cognitive and technical elements (Nonaka 1994).

Polanyi’s observation that ‘we can know more than we can tell’ has been eclipsed by Nonaka’s claim that tacit knowledge could be converted into ‘explicit knowledge’, depicted as ‘words or numbers that anyone can understand’ (Nonaka and Takeuchi, 1995, p.9). Nonaka distinguished technical from cognitive tacit knowledge giving Polanyi’s ideas a more

“practical” aspect (Nonaka, 1994, p. 16; Nonaka and Takeuchi, 1995, p. 60). Knowledge can also be viewed as existing in the individual or the collective (Nonaka 1994). Individual knowledge is created by and exists in the individual whereas social knowledge is created by and inherent in the collective actions of a group (Alavi and Leidner, 2001) to suggest that explicit knowledge is more valuable than tacit knowledge, a viewpoint that, if accepted, might favour a technology enabled knowledge management process (technology being used to aid in explicating, storing, and disseminating knowledge).

Collins (2001) argued that the “forms of life” by and through which we conduct our social practices cannot be made explicit, and thus remain an underlying tacitly known component.

At an organizational level, tacit knowledge is present not only in an individual but is also available in processes, culture and values (Joia and Lemos, 2010). Tacit knowledge is not easy to aggregate or disseminate. It embodies knowledge that creates sustainable competitive advantage in part through innovation. That is why managing this type of knowledge is of utmost strategic importance for an organization (Grant, 2013). According to Jashapara (2004), the terms of knowledge, know-how, implicit knowledge, knowing-doing (the processual perspective) is used as synonyms for tacit knowledge. Whereas knowing-that, information (the structural perspective) are used as synonymous to explicit knowledge. According to Busch (2008), tacit knowledge is expertise, skill or ‘know how’, as opposed to codified knowledge. Alternatively, “tacit knowledge is the personal knowledge resident within the mind, behaviour and perceptions of individuals. Tacit knowledge includes skills, experiences, insight, intuition and judgment, it is typically shared through discussion, stories, analogies and person-to-person interaction; therefore, it is difficult to capture or represent in explicit form (Busch, 2008).

An understanding of the concept of knowledge and knowledge typologies is important because theoretical developments in the informatics field and specifically in the knowledge management area are influenced by the distinction among the different types of knowledge (Alavi and Leidner, 2001). The tacit-explicit knowledge classification is widely cited, although several other knowledge classifications exist that avoid the distinction between the tacit-explicit dimension (Alavi and Leidner, 2001). They refer to knowledge as declarative (know-about or knowledge by acquaintance), Zack (1998) refer to knowledge as procedural (know-how), causal (know-why), conditional (know-when), and relational (know-with). A pragmatic approach to classifying knowledge simply attempts to identify types of knowledge that are useful to organizations (Alavi and Leidner, 2001). The following table presented in

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Table 1 summarizes the knowledge typologies and provides some examples of it. However, this master thesis study will focus on the conversion between tacit knowledge and explicit knowledge.

Table 1. Knowledge typologies and examples (adapted from Alavi and Leidner, 2001)

This part aimed to present the various knowledge typologies and, at the same time, focused on tacit and explicit knowledge. The views of Polanyi’s and Nonaka’s were discussed as the most dominant. Polanyi’s (1962; 1969; 2009) view of tacit knowledge provides a theoretical basis for Nonaka’s (1994) knowledge conversion. Nonaka (1994) follows a more practical approach for studying knowledge work in organizations. The aforementioned also adds to the theoretical basis for this master thesis.

2.4 What is innovation in knowledge work?

Innovation consists of the generation of a new idea and its implementation into a new product, process or service, leading to the dynamic growth of the innovative business enterprise (Popadiuk et al, 2006). Thompson (1965) defined innovation in a simple way as ―the generation, acceptance and implementation of new ideas, processes, products or services. The essential element of innovation is the creation of new knowledge according to Drucker (1993).

Knowledge is very significant in the innovation process since it represents not only important input but also the output of the transformation process (Urbancova, 2013).

Innovation is mainly based upon the continuous dynamic exchange between tacit and explicit knowledge (Nonaka and Takeuchi, 1995) and it requires the conversion of knowledge into new products, processes, and services as well as the successful diffusion of these inventions into society and/or market. Nonaka and Takeuchi (1995) presented a model of innovation processes, central to which is the distinction between two types of knowledge, tacit and explicit. In Nonaka and Takeuchi’s model (1995), the basic source of innovation is tacit

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knowledge, which needs to be explicated in order to be transformed into knowledge that is useful at the levels of the group and the whole organization (explicit knowledge). Tacit knowledge includes the subjective insights, intuitions, hunches, and ideals that are the crucial basis for innovative processes (Nonaka and Takeuchi, 1995, pp. 8–10).

In other words, the conversion of tacit to explicit creates new knowledge. According to Nonaka and Kono (1998), knowledge creation is a spiralling process of interactions between explicit and tacit knowledge. These interactions lead to the creation of new knowledge (Nonaka and Konno, 1998). Knowledge comes from individuals (Nonaka and Takeuchi, 1995) and organizations consist of individuals. According to Nonaka (1994), innovation can be understood as a process in which individuals of the organization constantly creating new knowledge and, therefore, innovation to develop their organization. This suggests that the organization should be studied from the viewpoint of its people and how they create knowledge (Nonaka, 1994). In addition, Nonaka and Takeuchi (1995) argued that every organization has the credibility in connecting the internal and external organizational knowledge in the form of innovating new products and services. Since innovation comes as a result of the dynamic exchange between tacit and explicit knowledge and since from this exchange new knowledge is created, we can say that the creation of new knowledge is an essential element of innovation. This is particularly relevant for SMEs. Being innovative can be a significant challenge for SMEs due to their smallness, limited resources and capabilities (Gnyawali & Park, 2009).

Hence, innovation in knowledge work, in this master thesis, implies the process of creating new knowledge through knowledge worker’s interaction in knowledge conversion (Nonaka and Takeuchi, 1995; Newell, 2009). Continuous innovation requires a well-planned system of managing knowledge and an appropriate organisational environment that enables an enterprise to excel in technological, market and administrative knowledge creation (Easa, 2012).

2.5 Digital technologies in support of knowledge work

A well-planned system of managing knowledge also implies digital technologies that are used for knowledge management. Knowledge management is considered a key factor for organizations, which try to get a competitive advantage (Navimipour and Charband, 2016).

Knowledge management is a process that through creating, accumulating, organizing and utilizing knowledge helps achieve objectives and enhance organizational performance (Valmohammadi and Ahmadi, 2015) and is purported to increase innovativeness and responsiveness (Kör and Maden, 2013).

According to Davenport and Prusak (1998), knowledge management has the following three aims: (1) to make knowledge visible and show the role of knowledge in an organization; (2) to develop a knowledge-intensive culture by encouraging behaviours such as knowledge sharing, as opposed to hoarding, and proactively seeking and offering knowledge; (3) to build a knowledge infrastructure, not only a technical system. But a web of connections among people given space, time, tools, and encouragement to interact with the aim of sharing knowledge and creating new knowledge.

The role of digital technologies for the support and management of knowledge that flows within and between organizations is increasing in importance (Gressgård et al., 2014). Digital technologies are tools that allow information and knowledge exchange, as well as work execution by bringing together people, processes and technology (Lopez-Nicolas and Soto-

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Acosta, 2010). Knowledge management practices are supported by digital technologies that help facilitate knowledge acquisition/creation, knowledge dissemination, knowledge conversion and knowledge utilization (Soto-Acosta and Cegarra-Navarro, 2016). More specifically, the role of digital technologies in knowledge work focuses on exploring the relationship between digital technologies and knowledge management, including knowledge retrieval, knowledge storage, knowledge sharing, knowledge transfer, knowledge innovation and knowledge application.

Digital Technologies for the support of knowledge management is increasingly important for the competitiveness of large companies and SMEs (Cerchione et al., 2016). Pérez‐Luño et al.

(2016) highlight that knowledge generated in SMEs is tacit in nature. In addition, Desouza and Awazu (2006) underline that in SMEs there is a sort of common knowledge known to all members of the organization, and point out the dominance of the process of socialization in the knowledge-creating cycle. This master thesis research is conducted in the context of Chinese SMEs. Not all Chinese SMEs reach the level of using sophisticated knowledge management systems. However, most of them use some kind of digital technologies for the support of knowledge work. Nevertheless, presenting and explaining how digital technologies are used to support knowledge work is considered important for the master thesis.

2.5.1 Digital technologies for knowledge storage and retrieval

Knowledge storage involves both the soft or hardstyle recording and retention of both individual and organizational knowledge in a way so as to be easily retrieved (Caroline et al., 2015). In the process of applying knowledge to solve problems and accomplish tasks, individuals will gain new knowledge. The acquisition of this new knowledge may be accidental or conscious thinking. Knowledge storage utilizes technical infrastructure such as modern informational hardware and software and human processes to identify the knowledge in an organization, then to code and index the knowledge for later retrieval (Caroline et al., 2015). Digital technologies can help individuals to obtain a large amount of rich information, as long as they remember the main points of the information, they do not need to remember all the information. The extraction of knowledge is either to solve a particular problem or to create new knowledge.

2.5.2 Digital technologies for knowledge sharing

The development in digital technologies may be effective in lowering some natural, cultural, social and hierarchical barriers involved in knowledge sharing, and the increasing popularity of the use of digital technologies in organizations has reinforced the openness of knowledge sharing (Pei-Lee et al., 2017). Digital technologies can not only provide individuals with a way to understand the knowledge of others, but also enable individuals to share their knowledge with others. Digital technologies such as computer networks, electronic bulletin boards, and computer-based communications (such as e-mail) help individuals sharing what they know with others. In addition, digital technologies can facilitate the sharing of personal explicit and tacit knowledge, for example the knowledge shared from the supervisor to the employees or among employees.

2.5.3 Digital technologies for knowledge transfer

Knowledge transfer may occur at different levels between individual knowledge transfer, individual knowledge transfer to external resources, individual-to-team knowledge transfer, knowledge transfer between teams, and team-to-organization knowledge transfer. The communication process and information flow drive the knowledge transfer process within the organization. An example of the moderating role of digital technologies in knowledge transfer

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in organizations is the organization’s intranet, which provides a technological infrastructure for distributed knowledge sharing, knowledge transfer, and collaborative innovation. Other examples are data mining, knowledge mining, artificial intelligence and other technologies that provide good technical conditions for computer-aided knowledge transfer (Cavaliere et al., 2015).

The aforementioned three sub-sections aimed at introducing the role of digital technologies in knowledge work; knowledge storage and retrieval, knowledge sharing, and knowledge transfer were discussed in order to create a concrete theoretical basis for this master thesis.

Following, more examples of digital technologies that are used in knowledge work are presented in details, focusing mainly on the digital technologies used in the specific SME that the research is conducted.

2.5.4 Examples of digital technologies used in knowledge work

Digital technologies refer to various information and communication tools, software and database software systems that the employees of the Chinese SME use to support their knowledge work. It is useful for understanding the purpose of the master thesis research to also present and exemplify the digital technologies used in the specific Chinese SME.

Therefore, based on the characteristics of the specific tools, I sort out and summarize their applications and main functions in knowledge work as shown in the following Table 2.

Table 2. Examples of digital technologies used in the Chinese SME and their basic functions used in knowledge work

Digital

technologies Specific examples used in the SME

Basic functions in knowledge work

Semantic

organization tool Database system Store and classify various types of knowledge based on semantics and rules; expand the capacity of long-term memory of knowledge

Graphical

representation tool Office drawing

software Express knowledge in a certain form by using images Mind representation

tool Mind mapping

software Use specific method to present thinking process; assist the capacity of short-term memory of knowledge Synchronous

collaboration tool Multimedia

conference system Provide virtual face-to-face communication; multiple ways of presenting knowledge

Asynchronous

collaboration tool Chat software,

Forums Provide records for reviewing knowledge again;

promote the sharing of knowledge among individuals Complex

calculation tool Professional

software Rule-based calculation, analysis, and reasoning;

visualize the relationships implied by knowledge points

Following, the aforementioned applications of digital technology tools and their main functions in knowledge work are presented.

Semantic organization tool- database system

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The basic characteristics of the database include the following aspects: The data in the database are logically related to each other and have a defined meaning, that is, the data in the data set is stored in the database based on certain rules; the design, establishment, and use of the database revolves around the specific goal. Therefore, each database has a relatively stable group of users. At the same time, the database itself also has the functional applications that these fixed users care about. In the database, the information represented by the data set is a reflection of the real world, as long as things in the real world have changed, the data in the database should also reflect these changes in a timely manner.

In the knowledge work, the establishment and maintenance of the database by the manager and the user's access to the data in the database are all realized through the database management system. A database management system is software dedicated to data management. It provides a convenient, fast, and effective environment for establishing, maintaining, retrieving, accessing, and processing data (Brodie and Mylopoulos, 2012).

In knowledge work, the basic function of database technology is to expand the long-term memory capacity of employees, store various types of knowledge such as text, images, audio, video, and extract the required knowledge through search functions when employees need it.

In addition, employees can also build their own database system to assist in understanding and sorting out the acquired information and knowledge.

Graphical representation tool- office drawing software

Office drawing software, such as Visio, is a tool to help people graphically represent knowledge outcomes. Graphical representation is to represent specific attributes or characteristics of a transaction in the form of images, drawings, diagrams, etc. Although the graphical representation forms cannot directly and generally express information about a certain basic attribute as described, these can provide a large amount of general information about the multi-faceted characteristics of things.

The use of office drawing software has two purposes in knowledge work: interpretation and expression as interpretation tools, which can be used to assist employees in viewing and manipulating images in order to obtain meaning from visual information (Pan et al., 2017).

Images can help employees understand difficult text materials and abstract concepts as an expression tool. On the one hand, it can support employees to express knowledge in a certain form and explain the subject's thoughts in different images. On the other hand, it can also help employees to exchange ideas and opinions visually, making it easier for other observers to understand their ideas.

Mind representation tool- mind mapping software

The mind map starts from a core concept, and as employees' thinking continues to deepen, an orderly map is gradually established. The use of mind representation tool facilitates the organization of information and makes the information visible, thus facilitating the processing of information (Meier, 2007). The mind map is used for information processing, that is, to summarize and synthesize information to assist employees in thinking about complex problems and characterizing information.

The knowledge processing function of the mind mapping tool is similar to the knowledge processing function inside the employee's brain and thus helps to store and extract information and knowledge during the association process. Mind maps can help employees

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organize ideas, and inspire employees' inspiration during use, thereby further promoting the generation of new knowledge.

Synchronous collaboration tool- multimedia conference system

The multimedia conference system is a multimedia communication technology that allows people in different places to realize "real-time, visual, and interactive" through some kind of transmission medium. It can distribute a variety of information such as text, pictures, voices, and static moving images of people to the terminal devices of various users, so that geographically dispersed users can come together and communicate through graphics, voice, and other methods. It can increase the ability of both parties to understand the content, and make people feel as if they are attending a meeting in the same venue.

The multimedia conference system provides employees with a wealth of information in different representations. In addition, the multimedia conference system also has a powerful conference recording function, which expands the long-term memory capacity of employees, greatly reduces the memory burden of employees in the communication process, and focuses on the understanding of information. Then call up the video and watch it repeatedly for learning. In the synchronous collaboration method, employees do not need to wait for speaking opportunities as they do in face-to-face communication, and can express their ideas at any time. This results in employees facing more information presentation and requires employees to have stronger knowledge processing capacity.

Asynchronous collaboration tool- chat software, forums

Asynchronous collaboration refers to the asynchronous communication and cooperation between two or more individuals, has long been established as having value in supporting the collaborative sharing of knowledge (Goodyear, 2015). Chat software, forums, and collaborative editing systems are all typical asynchronous collaboration tools. Chat software is a modern communication method for transmitting and receiving information to each other through a network. Its mediumness drives valuable knowledge work. Chat software can transfer information such as text, images, sounds in a very fast way, and connect with any individual in the world. In knowledge work, chat software is a very common communication tool. Dialogue and communication through chat software promote the sharing of knowledge among individuals, and help to obtain all kinds of required knowledge in the innovation process of knowledge work. The communication based on chat software has a corresponding conversation record, which is conducive to employees 'reflection on the content of communication afterwards. The employees' ideas are combined with existing knowledge to create new knowledge.

A forum is an electronic information service system. The system provides users with a public electronic whiteboard, and each user can post information or make opinions on it. Users can exchange various files with each other. As long as the files are simply uploaded to the system, other users can download these files very easily. The forum promotes the change of concepts by supporting employee reflection and communication with others, thereby better promoting the learning, understanding and construction of knowledge.

Complex calculation tool- professional software

In knowledge work, the process of turning ideas into specific products cannot be separated from rules-based cognitive behaviors. Today’s enterprise is increasingly dependent on the

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kind of highly skilled technical and professional communities of work (Hirsch-Kreinsen, 2016). The solution of target problems requires individuals to connect complex knowledge units into knowledge networks in accordance with specific rules. Therefore, different knowledge tasks have corresponding professional software to assist the complex cognitive activities of the subject. For example, CAD or CAM software is often used in industrial design, and financial and accounting work depends more on the professional financial software Kingdee financial system, and so on.

The basic function of professional software is to store various types of information such as data, text, graphics, audio, video, etc. The software program can be called internally, and the main body can also be easily accessed and updated. The core function of professional software is rule-based calculation and reasoning. The thinking process involved in applying professional software tools requires employees to use existing rules, create new rules describing relationships, and organize information, while leaving some basic, non-innovative information processing tasks to professional software.

In knowledge work, after employees give part of the basic complex computing tasks (calculation, analysis, reasoning, etc.) to professional software, they have more time to understand the calculation results in professional software. Therefore, professional software reduces the workload of employees, and it is a tool to enhance and restructure the analysis and synthesis process.

2.6 Theoretical framework

2.6.1 The SECI model

For the theoretical framework of the master thesis, I will consider SECI model by Nonaka and Takeuchi (1995). The SECI model, initially proposed by Nonaka in 1994 and expanded by Nonaka and Takeuchi in 1995, is a model of knowledge creation that explains how tacit and explicit knowledge are generated, shared and recreated in organizations and, therefore, converted into organizational knowledge. The model distinguishes four knowledge dimensions, socialization (tacit to tacit), externalization (tacit to explicit), combination (explicit to explicit), and internalization (explicit to tacit), that together form the acronym SECI.

The success of many firms depends on their ability to create new knowledge through a cyclic model of continuous interactions and transformation of tacit and explicit knowledge on three levels: individuals, groups and organizations. In the SECI model, tacit knowledge is converted into explicit knowledge and then back again in order for a knowledge creation cycle to be completed (Nonaka and Takeuchi, 1995). This occurs through the four processes of socialisation, externalisation, combination, and internalisation, as depicted in the SECI model (Nonaka and Takeuchi, 1995). Nonaka (1994) posited that four phases (i.e.

socialization, externalization, combination, and internalization) occur when tacit and explicit knowledge interact with each other, and that these phases are fundamental in any knowledge creation process. Nonaka and Takeuchi (1995) argued that innovation is largely based upon the continuous dynamic exchange between tacit and explicit knowledge.

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Figure 3. Knowledge conversion (adapted from Nonaka and Takeuchi, 1995) There are four modes of knowledge conversion, as illustrated in Figure 3.

1. From tacit knowledge to tacit knowledge: the process of socialization.

2. From tacit knowledge to explicit knowledge: the process of externalization.

3. From explicit knowledge to explicit knowledge: the process of combination.

4. From explicit knowledge to tacit knowledge: the process of internalization.

Socialization refers to one individual shares tacit knowledge directly with another. According to Nonaka (1984), socialization involves the conversion of tacit knowledge to tacit knowledge between individuals. Nonaka and Takeuchi (1995) argue that self-transcendence is crucial in order to make this happen, because tacit knowledge can only be shared if the self becomes the larger self that includes the tacit knowledge of the other. Externalization involves conversion of tacit knowledge to explicit knowledge. Externalization may be achieved by writing a description of work processes, through debates or self-reflections (Nonaka and Konno, 1998).

When tacit knowledge is made explicit, knowledge is crystallized thus allowing it to be shared by others and to become the basis of new knowledge (Nonaka, et al., 2000). These expressions often appear to be insufficient, but this gap can help to promote reflection and interaction between individuals (Nonaka, 1991; Nonaka and Nishiguchi, 2001). Combination is the process of converting localized tested knowledge into an organization-wide, explicitly stated resource (Nonaka and Konno, 1998). Combination provides a form of knowledge repository that serves as a resource for others to continue the knowledge management cycle (Nonaka and Takeuchi, 1995). When the auditor of a company collects information from throughout the organization and puts it together in a context to make a financial report, that report is new knowledge in the sense that it synthesizes knowledge from many different sources in one context (Nonaka et al., 2000). Internalization process embodies explicit knowledge into tacit knowledge, suggesting that we internalize the explicit knowledge to our tacit knowledge. The process of embodying unfamiliar, explicit knowledge into work routines so that it becomes a part of daily custom (Nonaka and Konno, 1998). Identifying relevant organizational knowledge and applying it in one’s own area of work so that the knowledge soon becomes habitual (Nonaka, 1994). This tacit knowledge accumulated at the individual level can then set off a new spiral of knowledge creation when it is shared with others through socialisation (Nonaka et al., 2000).