**2. The knowledge**

*Knowledge definition.* In the context of knowledge management this term can be defined in different ways in such a way that it reflects the different research perspectives. Most of the

Knowledge Management Maturity Model in the Interpretativist Perspective 289

Because of that growth it was possible to redesign company processes, which modified the way in which worked the companies. Such "reengineering" of business processes provide a valuable profitability on investment, but in Europe and USA it had bad press because the changes, often, were too much for the company culture to manage it (Neef, 1999); this lead to Snowden (2000) to describe it like the "*last breath of the Tailorism*". The fast increase of technology in the workplace requires new skills from employees, therefore the companies became aware that it was necessary the management of information and knowledge in different ways. This implies to help the employees to react before changes, to promote creativity and innovation, and to learn and to boost productivity (Neef, 1999). Companies

Davenport & Prusak (1998) suggest that companies having more than two hundred or three hundred employees are too big for people can have a comprehension of company collective knowledge, for this reason this becomes a need "*to know what is known*" (Sieloff, 1999). If knowledge turns into a valuable company asset, therefore it must be accessed, developed and used (Davenport & Prusak, 1998). Knowledge management started because of the wish to improve company knowledge; however, it occurred without a definition of this widely accepted. Nonaka & Takeuchi (1995) define the company-knowledge through its ability to adapt itself to the environmental changes by creating new knowledge, effective spreading and put into practice; the only task of a "*knowledge creating*" company is continuous

*Knowledge Managemente*. Describing this term is usually difficult because there is little agreement about its definition (Neef, 1999; Bhatt, 2001). Raub & Ruling (2001) point out in their study that there is not a unique area accepted for the discourse in the academic or management-related literature. Many authors simply avoid the term, and prefer to focus on specific issues of the subject like knowledge, innovation or learning (Costello, 1996). Others argue that knowledge management is deeply related with concepts like company learning,

As we have seen, there is no consensus about a definition of knowledge management, and many authors avoid the epistemological discussion about its definition by comparing knowledge with information and data (Alavi & Leidner, 2001). A generalized opinion is that data consists of facts and raw numbers, that information are processed data and that knowledge is the authenticated information (Alavi & Leidner 2001). Through a review of the literature on knowledge management, Scarbrough *et al.* (1999) define knowledge management like "*any process or practice of creating, acquiring, capturing, sharing and using knowledge, wherever it lies, to improve the performance and learning of the companies*". Hedlund (1994) suggests that knowledge management refers itself to the generation, representation, storage, transfer, transformation, application, insertion and protection of company's knowledge. Such definitions, apart from incorporate many aspects of the "process" around the knowledge management, implies an essentially objectivist vision of the subject. Even the vendors of technology emphasize more on the influence of technology in the knowledge management, for instance, the following definition of knowledge management was quoted

Knowledge management is the use of technology to make that information become important and accessible wherever is located. To perform this efficiently it is required the appropriated application of the proper technology for the specific situation. The knowledge management incorporates systematic processes to find, select, organize and present the information in such a way that it improves both the employee comprehension and the use of company's assets.

company memory, information exchange and collaborative work (Schultze, 1998).

need to turn into "*knowledge companies*".

innovation (Nonaka *et al.*, 2000; Nonaka, 2008).

in the web page of Microsoft (Brown & Duguid, 1998):

definitions belong to one of the following categories: 1) it can be defined by means of comparison or relation with data and information (Marshall, 1997; Burton-Jones, 1999; Kanter, 1999); and 2) it can be defined as knowledge *per se,* that is, without any direct relation with data and information (Nonaka & Takeuchi, 1995; OECD, 1996; Rennie, 1999; Davenport & Prusak, 2000).

In the first category it is considered as an entity which is located in an authority level higher than data and information (Stewart, 1997). Data is a set of discrete facts about events (Davenport & Prusak, 2000), while information is *"data provided of relevance and with a purpose"* (Drucker, 1988) that can be created by adding value to data through contextualization, categorization, calculation, correction and condensation (Davenport & Prusak, 2000). Therefore knowledge is described like *"information suitable to be processed"*  (O'Dell et al., 1998; Tiwana, 2000), which provides *"the power to act and to take decisions that produces value"* (Kanter, 1999). On the one hand, however, in the real world, it is not always possible to distinguish among knowledge, information and data, because the differences between these terms are simply a matter of degree (Davenport & Prusak, 2000). On the other hand, in accordance with the importance of the knowledge and the knowledge base of individuals, that which is considered as information for some people is interpreted as knowledge by others and vice versa (Bhatt, 2001).

The second category presents the features of knowledge, quality and components, instead of contrasting it with information and data. Therefore, avoid the particular distinction between knowledge and information. An example within this category is Davenport & Prusak (2000), who define knowledge like *"a smoothly mixture with a backdrop which consists of experiences, values, context information and expert's visions, who provide a framework to evaluate and to incorporate new experiences and information"*. Apart from this, knowledge also is defined like a series of *know-what*, *know-how and know-who* (OECD, 1996; Rennie, 1999), a *"dynamic human process to justify the personal beliefs about truth"* (Nonaka & Takeuchi, 1995) and the result of learning process (Orange *et al*., 2000).

*Knowledge economy*. To understand knowledge management is necessary to see the subject within the whole context of the big changes which occur in the global economic framework (Neef, 1999). It is argued that western society entered since the last part of the 20th century in a deep revolution, a second industrial revolution based on the information and does not on the energy, related with the development of the computational sciences (UNESCO, 2005). The economist Fritz Machlup (Checkland & Holwell, 1998) declares that already in 1960 there was an increasing proportion of knowledge workers, and coined in his discussions the sentences "*knowledge industries*".

Marshall (2008), an ancestor of the neo-classic economy, was one of the first authors that recognized explicitly the importance of the knowledge in the economic issues: *"Capital is formed mostly by knowledge and organization … and knowledge is our more powerful production tool"*. However, like point out Nonaka & Takeuchi (1995), the neo-classic economists were concerned only about the usage of existent knowledge, not for the creation of new knowledge.

In 1993 Peter Drucker, talking about manufacture, services and information said: "*We are entering –or we have already entered- in the society of knowledge, in which the basic economic resource…is knowledge… and where the knowledge worker will perform a central role*". The changes in the computing technology of middle 80's were the key for this change and, because of the exponential growing of computer science in speed, cost reduction and availability of applications, for the first time the companies were able to capture, to code and to spread in a fast way big amounts of information all over the world (Tapscott, 1997).

definitions belong to one of the following categories: 1) it can be defined by means of comparison or relation with data and information (Marshall, 1997; Burton-Jones, 1999; Kanter, 1999); and 2) it can be defined as knowledge *per se,* that is, without any direct relation with data and information (Nonaka & Takeuchi, 1995; OECD, 1996; Rennie, 1999;

In the first category it is considered as an entity which is located in an authority level higher than data and information (Stewart, 1997). Data is a set of discrete facts about events (Davenport & Prusak, 2000), while information is *"data provided of relevance and with a purpose"* (Drucker, 1988) that can be created by adding value to data through contextualization, categorization, calculation, correction and condensation (Davenport & Prusak, 2000). Therefore knowledge is described like *"information suitable to be processed"*  (O'Dell et al., 1998; Tiwana, 2000), which provides *"the power to act and to take decisions that produces value"* (Kanter, 1999). On the one hand, however, in the real world, it is not always possible to distinguish among knowledge, information and data, because the differences between these terms are simply a matter of degree (Davenport & Prusak, 2000). On the other hand, in accordance with the importance of the knowledge and the knowledge base of individuals, that which is considered as information for some people is interpreted as

The second category presents the features of knowledge, quality and components, instead of contrasting it with information and data. Therefore, avoid the particular distinction between knowledge and information. An example within this category is Davenport & Prusak (2000), who define knowledge like *"a smoothly mixture with a backdrop which consists of experiences, values, context information and expert's visions, who provide a framework to evaluate and to incorporate new experiences and information"*. Apart from this, knowledge also is defined like a series of *know-what*, *know-how and know-who* (OECD, 1996; Rennie, 1999), a *"dynamic human process to justify the personal beliefs about truth"* (Nonaka & Takeuchi, 1995) and the result of

*Knowledge economy*. To understand knowledge management is necessary to see the subject within the whole context of the big changes which occur in the global economic framework (Neef, 1999). It is argued that western society entered since the last part of the 20th century in a deep revolution, a second industrial revolution based on the information and does not on the energy, related with the development of the computational sciences (UNESCO, 2005). The economist Fritz Machlup (Checkland & Holwell, 1998) declares that already in 1960 there was an increasing proportion of knowledge workers, and coined in his discussions the

Marshall (2008), an ancestor of the neo-classic economy, was one of the first authors that recognized explicitly the importance of the knowledge in the economic issues: *"Capital is formed mostly by knowledge and organization … and knowledge is our more powerful production tool"*. However, like point out Nonaka & Takeuchi (1995), the neo-classic economists were concerned

In 1993 Peter Drucker, talking about manufacture, services and information said: "*We are entering –or we have already entered- in the society of knowledge, in which the basic economic resource…is knowledge… and where the knowledge worker will perform a central role*". The changes in the computing technology of middle 80's were the key for this change and, because of the exponential growing of computer science in speed, cost reduction and availability of applications, for the first time the companies were able to capture, to code and to spread in a fast way big amounts of information all over the world (Tapscott, 1997).

only about the usage of existent knowledge, not for the creation of new knowledge.

Davenport & Prusak, 2000).

knowledge by others and vice versa (Bhatt, 2001).

learning process (Orange *et al*., 2000).

sentences "*knowledge industries*".

Because of that growth it was possible to redesign company processes, which modified the way in which worked the companies. Such "reengineering" of business processes provide a valuable profitability on investment, but in Europe and USA it had bad press because the changes, often, were too much for the company culture to manage it (Neef, 1999); this lead to Snowden (2000) to describe it like the "*last breath of the Tailorism*". The fast increase of technology in the workplace requires new skills from employees, therefore the companies became aware that it was necessary the management of information and knowledge in different ways. This implies to help the employees to react before changes, to promote creativity and innovation, and to learn and to boost productivity (Neef, 1999). Companies need to turn into "*knowledge companies*".

Davenport & Prusak (1998) suggest that companies having more than two hundred or three hundred employees are too big for people can have a comprehension of company collective knowledge, for this reason this becomes a need "*to know what is known*" (Sieloff, 1999). If knowledge turns into a valuable company asset, therefore it must be accessed, developed and used (Davenport & Prusak, 1998). Knowledge management started because of the wish to improve company knowledge; however, it occurred without a definition of this widely accepted. Nonaka & Takeuchi (1995) define the company-knowledge through its ability to adapt itself to the environmental changes by creating new knowledge, effective spreading and put into practice; the only task of a "*knowledge creating*" company is continuous innovation (Nonaka *et al.*, 2000; Nonaka, 2008).

*Knowledge Managemente*. Describing this term is usually difficult because there is little agreement about its definition (Neef, 1999; Bhatt, 2001). Raub & Ruling (2001) point out in their study that there is not a unique area accepted for the discourse in the academic or management-related literature. Many authors simply avoid the term, and prefer to focus on specific issues of the subject like knowledge, innovation or learning (Costello, 1996). Others argue that knowledge management is deeply related with concepts like company learning, company memory, information exchange and collaborative work (Schultze, 1998).

As we have seen, there is no consensus about a definition of knowledge management, and many authors avoid the epistemological discussion about its definition by comparing knowledge with information and data (Alavi & Leidner, 2001). A generalized opinion is that data consists of facts and raw numbers, that information are processed data and that knowledge is the authenticated information (Alavi & Leidner 2001). Through a review of the literature on knowledge management, Scarbrough *et al.* (1999) define knowledge management like "*any process or practice of creating, acquiring, capturing, sharing and using knowledge, wherever it lies, to improve the performance and learning of the companies*". Hedlund (1994) suggests that knowledge management refers itself to the generation, representation, storage, transfer, transformation, application, insertion and protection of company's knowledge. Such definitions, apart from incorporate many aspects of the "process" around the knowledge management, implies an essentially objectivist vision of the subject. Even the vendors of technology emphasize more on the influence of technology in the knowledge management, for instance, the following definition of knowledge management was quoted in the web page of Microsoft (Brown & Duguid, 1998):

Knowledge management is the use of technology to make that information become important and accessible wherever is located. To perform this efficiently it is required the appropriated application of the proper technology for the specific situation. The knowledge management incorporates systematic processes to find, select, organize and present the information in such a way that it improves both the employee comprehension and the use of company's assets.

Knowledge Management Maturity Model in the Interpretativist Perspective 291

knowledge social interaction is more complex than this (McAdam & McCreedy, 1999-a;

McAdam & McCreedy (1999; 1999-a) provide an alternative structure for the comprehension of knowledge management and they propose three model categories for it: 1) the intellectual capital, in which the knowledge is like a material good; 2) the knowledge category models, in which the knowledge is identified by categories; and 3) the social constructivism models,

Knowledge management usually treats on systematize, organize and use the knowledge inside a company for transforming it and storing it with the objective of improving the performance (KPMG, 1998); additionally, exists, as we have already pointed out, a big number of available definition for KM, all of these trying to encapsulate what it is and how it must be done (Quintas *et al.*, 1997; O'Leary, 2001; Diakoulakis*et al.*, 2004; Nicolas, 2004),

On the one hand tacit knowledge is personal, context-specific and for this reason it is difficult to formalize and to communicate. The explicit knowledge is "codified", on the other hand, has to do with knowledge that can be transmitted in a formal and systematic language…Therefore, scientific objectivity is not the only source of knowledge. Much of our knowledge is the result of our determined effort to relate ourselves with the world…

The explicit knowledge requires being not subjective and can lie on databases, written reports, among others. In addition to this tacit knowledge subdivides itself in two categories

Tacit knowledge includes cognitive and technical elements… mental models, cognitive elements, like schemes, paradigms, perspectives, beliefs and points of view, which help individuals to perceive and define its world. Opposite to that, knowledge technical elements include concrete know-how, jobs and abilities. This is important because cognitive elements of tacit knowledge are referred to single pictures of reality and to visions for the future; this

Applying the Burrel & Morgan framework (1979) in a social and company-related research, Schultze (1998) identified four research paradigms in KM: radical humanism, radical

Among these paradigms exist a continuity between the subjective and objective perspectives: from the objective's point of view, knowledge is considered as an object awaiting to be discovered, that can exist in a number of forms ‒tacit or explicit‒, and in a number of places –individual, group or organization (Schultze, 1998)-; from subjective point of view it is pointed out that knowledge emerge through a continuous elaboration, it is determined by social practices of communities, and cannot be located in an specific place because it cannot exist independently of human experience and social practices of knowing

structuralism, interpretativism and functionalism, as it is showed in the Table 2.

in which knowledge is intrinsically tied to the learning and social processes.

The following is an "official" definition of its differentiation:

is "what it is" and "what should be" (Nonaka & Takeuchi, 1995, p. 60). It is important take notice that technical skills are mainly body-related skills.

**3. Perspectives of knowledge management** 

Nonaka*et al.*, 2000; Von-Krogh*et al.*, 2000).

but until now, there is no consensus.

**2.1 Tacit and explicit knowledge** 

(Nonaka & Takeuchi, 1995, pp. 59-60).

not fully different:

(Schultze, 1998).

Others argue their own points of view about knowledge and point out that it also occupies itself of creating an environment and a culture in which knowledge can evolve (Davenport & Prusak 1998; Wenger, 1998; Wenger & Snyder, 2000). For example, already in 1996 Davenport et al. criticize the technologies approaches for KM:

The emphasis of encoding in the KM literature probably reflects the predominance of the vision of information systems: many articles have been focused on the development and implementation of the KM databases, of tools –for example, decision supporting tools- and techniques despite the recognition, now very wide, that most spectacular improvements in the KM capacity in the next ten year will be in the human and managing issues.

The lack of a rigorous definition and the aggressive promotion of technologists, has lead many people to point out that knowledge management is a fashion-like subject. Although the subject clearly exhibits the features of a fashion issue (Davenport & Grover, 2001), and even can be analyzed from the fashion perspective (Raub & Ruling, 2001), the consultancy firm TFPL (1999) considers that is probable that concepts and values of the knowledge management practice are deeply-rooted in the basic managing processes of the companies.

*Knowledge management models.* Because of the divergence of points of view, opinions and ideas having the general motto of the knowledge management, it is necessary to identify a set of structures that allow that subjects make sense, a challenge that have been assumed by different researchers. An example, frequently cited, is that of Earl (2001), who proposes seven strategic schools for knowledge management, as can be seen in Table 1.


Table 1. Schools of Knowledge Management by Earl (2001)

These schools identify the types of strategies that use the companies for knowledge management, and Earl categorizes them in three large types: Technocratic, Economical and Behavioral. The approach of Technocratic ones is to manage the knowledge through the information or management of the technologies that support and condition the employees in their daily tasks; the Economical ones explicitly have the goal of produce incomes by exploiting knowledge like an asset; the approach of the Behavioral ones is to manage the knowledge from a behavior-based perspective, in which they manage and encourage to directors and managers for creating, sharing and proactively using the knowledge resources (Earl, 2001).

While these schools provide a useful classification of specific approaches, mainly in the issues related to how is used technology within a knowledge management initiative, it is considered that they do not achieve the emphasis of the epistemological base of the strategies of knowledge management, particularly because they do not efficiently classify the social aspects. Earl's social interaction model only is fully applied in the spatial school, which is centered in using the space the exchange of knowledge, like a chat in which is discussed about how to cool the water, o when builds are designed for knowledge exchange (Schultze & Boland, 2000; Ward & Holtham, 2000). However, many authors think that knowledge social interaction is more complex than this (McAdam & McCreedy, 1999-a; Nonaka*et al.*, 2000; Von-Krogh*et al.*, 2000).

McAdam & McCreedy (1999; 1999-a) provide an alternative structure for the comprehension of knowledge management and they propose three model categories for it: 1) the intellectual capital, in which the knowledge is like a material good; 2) the knowledge category models, in which the knowledge is identified by categories; and 3) the social constructivism models, in which knowledge is intrinsically tied to the learning and social processes.

Knowledge management usually treats on systematize, organize and use the knowledge inside a company for transforming it and storing it with the objective of improving the performance (KPMG, 1998); additionally, exists, as we have already pointed out, a big number of available definition for KM, all of these trying to encapsulate what it is and how it must be done (Quintas *et al.*, 1997; O'Leary, 2001; Diakoulakis*et al.*, 2004; Nicolas, 2004), but until now, there is no consensus.
