Abstract:
The main focus is to know about impact of organizational cultural environment on knowledge transfer When we talk about organizational environment it is consists of
1: Cultural factors
2: Legal/Political factors
3: Technological factors
A web-based Delphi survey is conducted to collect the top ten technologies used to assist knowledge leaders in completing their knowledge transfer initiatives. Referring to Nonaka and Takeuchi's knowledge creation model, results show that top priority is given to technologies used for extracting tacit knowledge, whereas most of the tools are currently used for supporting explicit knowledge.
Is there a correlation between types of organizational environment i.e. culture of organization and factors influencing knowledge transfer? It hypothesized that organizations scoring high on openness to change/innovation, and task-oriented organizational growth would be fertile to knowledge transfer. Second, it hypothesized that organizations scoring high on the factors of bureaucratic and competition/confrontation would be infertile to knowledge transfer. The research looked at Air Force squadrons, surveying a representative sample of the 1,495 active-duty squadrons included in the study with a 62-item, 5-point Likert-type instrument. Overall, 51 squadrons were surveyed, and 22 produced usable results. Both squadron and individual results were analyzed and both were similar. Squadron results showed that organizations scoring high on the factors of openness to change/innovation and task-oriented organizational growth appeared to score consistently high on three of the four measures of fertility to knowledge transfer. Organizations scoring high on the factors of competition/confrontation appeared to score consistently low on three of the four measures of fertility to knowledge transfer. The factor bureaucratic produced no significant correlations. In every case, the measure of fertility to knowledge transfer known as partner similarity did not behave as expected. The research concluded that there appears to be a correlation between organizational culture and factors influencing the transfer of knowledge, but concludes that the factors influencing the transfer of knowledge should be further explored, and a longitudinal study performed, before inferring any causal relationship.
Introduction:
With the realization of the importance of knowledge and learning, organizations have begun looking at how to increase organizational knowledge to gain a strategic advantage [Bresmann, Henrik, Julian Birkinshaw and Robert Nobel (1999), Davenport, Thomas H and Laurence Prusak (2000), Nonaka, Ikujiro and Hirotaka Takeuchi (1995)]. Much interest has centered on knowledge creation (Rueve and Ryan J, 2001). However, recent interest has increased in exploring knowledge transfer, because it provides a lower cost alternative to the creation and codification of new knowledge. One practitioner put it this way; "We used to say knowledge is power. Now we say sharing is power." (Pederson and Cynthia Ross 1998). Increased sharing of knowledge might create the benefits of increased organizational knowledge without having to expand the energy or cost associated with creating, codifying, or capturing more knowledge.
Increasing the amount of knowledge transferred within an organization has the potential to save an organization's money while positioning it better to face future challenges; however organizational culture is a strong force - one that may hinder the implementation of knowledge management in an organization. Specifically, organizational culture may affect an organization's ability to transfer knowledge because that culture may encourage individuals either to resist searching out and receiving knowledge or to resist effort to move knowledge out of their head. To the extent that this is true, it would be helpful to know what organizational cultures are more likely to be supportive of knowledge transfer. To explore this issue, this study asks the following question. Is there a significant relation between types of organizational environment and factors influencing knowledge transfer?
Background:
Knowledge is power. Organizations possess many kinds of resources, but only the resources, that are unique, inimitable, and valuable, are central to competitive advantage (Barney,1991; Prahalad and Hamel, 1990). Knowledge is one such meaningful resource (Matusik and Hill, 1998; Drucker, 1993; Nonaka, 1991). The explosive growth of information technology and the concomitant rapid rise of the knowledge economy have led to growing recognition of the importance of knowledge as a critical resource for competitive advantage of the firms (Quinn, 1992; Sveiby, 1997; Teece, 1998). Successful companies are those that can consistently create or acquire knowledge, disseminate it widely throughout the organization, and embody it in the products, when markets shift, technologies proliferate, competitors multiply, and products outdate in such an unprecedented rapid way. (Nonaka, 1991).
1: WHAT IS KNOWLEDGE?
In order to define knowledge we should define the components that lead toward knowledge formation. These factors are,
Data: Knowledge starts its life as data, unrelated facts, that that have little value on their own.
Information: As data is combined and placed in a context, it becomes information.
Knowledge: Information becomes knowledge through critical and creative thought processes. These processes generate meaning for the user that is verifiable.
Wisdom: When insight is added to the accumulating knowledge then a person has moved to being educated, i.e., they have an understanding of how they know. Wisdom grows from the process of education where philosophical insight and moral judgments can be made though the skills of thinking, evaluation and decision making, and self-actualization is evident.
2: TYPES OF KNOWLEDGE:
Knowledge has been classified as being tacit and explicit (Polanyi 1966).
Tacit knowledge: Have two dimensions both personal and practical. It is embedded in people's ideas, values and emotions and is expressed more in people's actions. It is their 'know-how' and shapes the way they perceive the world. In the knowledge economy interest is growing in a person's tacit knowledge because "it is deeply rooted in action and individual commitment and to a specific context" (Nonaka, 1991 quoted in Furlong 2001).
Explicit knowledge: is formal knowledge that is structured and recorded both in
numbers and words. It is readily transmitted between people and "defines the intellectual assets of an organization independently of its employees" (Stewart 1999 quoted in Furlong 2001).
Four basic patterns for creating knowledge in organizations emerge from the distinction between tacit and explicit knowledge (Figure 1): socialization (from tacit to tacit), externalization (from tacit to explicit), combination (from explicit to explicit), and internalization (from explicit to tacit) (Nonaka, 1994). Once the cycle is completed, each pattern can dynamically interact with any of the others, leading to a constant shift between tacit and explicit knowledge as well as to a more refined knowledge-generation process (Figure 1). Socialization (Quadrant 1) can be compared to a casual discussion, where individuals share some information without trying to produce explicit knowledge. Externalization (Quadrant 2) occurs when tacit knowledge is converted into explicit knowledge. This pattern happens when an individual explains what s/he knows for the first time. Combination (Quadrant 3) is the most obvious pattern of knowledge creation, because the documents already exist and can be used or restructured in a different manner. Internalization (Quadrant 4) takes place when one consults some documents and conceives her/his own knowledge out of what s/he has learned.
Figure 1. Knowledge creation and transfer framework (Nonaka and Takeuchi, 1995)
3: Knowledge Management (KM):
The concept of KM has been in practice for a long time, and mostly in an informal manner. The lack of consensus in defining what is meant by the term has led to major confusion reflected in various studies in the field. Therefore to understand KM concept, distinctions have to be made first between data, information, and knowledge to clear up confusion on the differences and relationships in this continuum. However, there has been much discussion of the topic in the literature, only simple and concise concepts have been given.
Davenport and Prusak (Davenport et al., 2000) suggest that there are three main component of knowledge management: knowledge generation, knowledge codification and coordination, and knowledge transfer. While knowledge transfer is just one of three aspects of knowledge management, it is a very important aspect, because the wider use of information already inside the organization can be highly profitable use of resources (Alchian et al., 1972) One of the phenomena related to knowledge is that, "unlike material assets, which decrease as they are used, knowledge assets increase with use: ideas breed new ideas, and shared knowledge stays with the giver while it enriches the receiver (Davenport et al., 2000).
4: KNOWLEDGE TRANSFER:
Generally when we use the word "transfer" we are talking about conveying or moving something from one person or place to another, or to hand over something. Knowledge transfer would then indicate conveying or moving knowledge from one person or place to another. In the world of business, knowledge transfer relates to how we move knowledge from one point of the organization to another (Rutkowski, 1999). Organizations are taking a serious look at how they can transfer the knowledge of their employees throughout their organizational structure. The pressure to more efficiently transfer knowledge to obtain highly qualified people that stay at the edge of the state of the art throughout life, and that can acquire new knowledge (=learn) whenever the need arises.
5: The Components of Knowledge Transfer:
In principle, knowledge transfer can be broken down into distinct stages. We've chosen five steps to describe the process: idea creation, sharing, evaluation, dissemination, and adoption. These stages often overlap, are combined, or are skipped; they also have important feedbacks.
1) Idea creation:
A massive literature exists on how to promote creativity. Robert Sutton has studied creativity in groups and offers the following list of questions to ask when assessing a group's potential for creativity.
Is the knowledge in the group varied enough?
Is the group's attitude about its knowledge include respect for what it knows and searching for what it does not know?
Does the group know how to fight so that new ideas are encouraged?
Does the group engage in constant experimentation?
Does the group's status order support innovation, or do a few bosses control ideas?
2) Idea sharing:
In practice, sharing (step 2) is often combined with validation and dissemination (steps 3 & 4). For example, a work group might share its ideas in a meeting, where their merits are discussed and relevant potential adopters hear the new methods. Here, sharing refers to the need to expose others to the idea in order for it to be evaluated. Dissemination takes place once the idea has passed some minimum level of evaluation.
For information sharing to occur, two conditions must be satisfied.
First, ideas must be in a form that others in the organization can interpret. Dissemination is easier when the knowledge can be made explicit or formal. For many skills and ideas, this involves transforming the idea into a codified, often written, format. Tacit, or informal, knowledge can be shared as well but the means of sharing are different, requiring face-to-face contact and opportunities for experiential learning. Apprenticeships often follow this time-intensive and sensory-rich means of transmitting knowledge. Nonaka has emphasized the rich interactions between tacit and explicit knowledge (1994). While conventional wisdom on why knowledge is difficult to transfer within firms has focused on motivational barriers, Szulanski (1996) found that features of the knowledge itself and the receiver's inability to interpret it were two of the most important factors in inhibiting knowledge transfer.
The second condition required for sharing to occur is that employees with ideas must be willing to share them. Sharing takes place at multiple levels, with overlapping but distinct concerns: from a worker to a workgroup, between workgroups, between departments, between business units, and between organizations. Unsurprisingly, Szulanski (1996) found that when the relationship between the source and recipient was distant or problematic, knowledge transfer was more difficult.
3) Idea evaluation:
Far more ideas exist than good ideas. Thus, organizations must evaluate their new ideas -- see whether they have worked in the past, are likely to work at new places, and actually work at new places. Employees must have the capability, incentives, and structures to perform the validation studies. At Xerox, for example, skilled technicians evaluate new ideas; the best are added into a best practices database for others to learn from.
4) Idea dissemination:
In principles, more information is better than less. At the same time, too much information creates overload. The Internet is a classic example, where nobody can read even a fraction of what is there. The key to disseminating knowledge is that people receive it who can use it. Several solutions exist to targeting information, ranging from the primarily technological to the purely organizational.
5) Idea adoption:
In the best of all worlds, if people knew the right thing to do, they would do it. However, we are not in such a world. Scholars of organizational inertia have developed complex theories of why, even after knowledge has been transmitted to the right people, it may not have been transferred to the organization. These theories fall into the categories of inadequate capability (known as "absorptive capacity" in the literature), poor incentives (the famous "not invented here" syndrome), and inadequate structures (for example, rigid operating procedures that are difficult to update).
6: How Management Can Promote Knowledge Transfer:
This section outlines how managers can encourage knowledge transfer within an organization through the use of training, incentives, organizational structures, and technology. Under each section, we outline steps that will promote each of the stages of knowledge transfer outlined above.
1: Training:
To effectively generate new ideas, employees need to be trained in problem solving, including an ability to think "outside the box." A typical program includes how to identify problems, prioritize, analyze root causes, identify possible counter-measures, implement the solution, and check whether the solution actually works. Companies must also provide people information on the business and its environment so their ideas are appropriate. In addition, employees need modern organizational skills such as how to work effectively as a team.
To share articulated or explicit knowledge, workers need to be literate in the languages in which ideas are expressed in their work. In addition to spoken and written language such as English, this may involve high-order "literacy" in more technical languages such as blue prints or statistics.
Managers and workers must be trained to evaluate new ideas. Just as importantly, they must be trained in systematically understanding what evidence should be convincing -- for example, the difference between correlation and causality, and the problems of small samples. As everyone who has ever studied statistics knows (and especially everyone who has ever taught it), these basic concepts are often difficult to apply in practice. Once these basics have been mastered, formal procedures such as statistical process control and the design of experiments can be useful in creating new knowledge. Importantly, for most employees and managers, statistical and problem-solving training will usually be more effective if it is coupled with resolving an actual problem, instead of classroom training in statistics.
Training workers to both disseminate and adopt new ideas may revolve around making them aware of where else in the organization their ideas may be useful and where else ideas may arrive from. Workers must also know how to use technology to post and search for new ideas. A receiver's ability to understand an idea, "absorptive capacity", can be a barrier. This can only be resolved through increasing the worker's own knowledge base, requiring an increased emphasis on substantive ongoing education and training.
One difficulty with existing training efforts is their lack of integration. To be most effective, training on creativity should include designing solutions that include opportunities for validation and dissemination of ideas.
2: Incentives:
To create an environment that encourages the generation of new ideas, managers should consider the following policies: incentive pay for ideas generated by groups or individuals; no layoffs for productivity improvements that follow from new ideas; job duties that include tinkering; permitting or encouraging experiments that are well-conceived but fail; and giving credit to employees who generate new ideas.
Employees are most likely to spend energy sharing what they know if they are in a single workplace with group incentives. Thus, extra incentives can be helpful when employees are in different units without common objectives. Both monetary rewards and recognition can prompt people to be more open with information and can create corporate cultures in which sharing of information is valued.
For example, at Buckman Laboratories (See www.buckman.com), everyone sees who answers problems on the open bulletin boards. Those who contribute to solving company problems in public are praised, those who do not become conspicuous. Bob Buckman emphasizes the benefits of there being "no place to hide". Similarly, when Jack Welch, CEO of General Electric, sees a new idea, he always asks: "Who else knows about this?" People know that their reward for cleverness depends on being able to explain how their idea has been shared.
Managers can also be rewarded for subordinates' participation. For example, at NUMMI first-level supervisors' job evaluation depends in part on their subordinates' participation in the suggestion program.
In order to encourage not only sharing but also evaluation and dissemination of ideas, knowledge-creating divisions must be rewarded for creating knowledge that other divisions use. Corporate headquarters cannot monitor the value of the knowledge transfer between units, or even whether any knowledge is shared. Knowledge-creating divisions face costs of creating an idea, posting it to the corporate computer network, posting it carefully (for example, avoiding division-specific jargon, being complete, creating helpful keywords, providing appropriate pointers to people who can supplement the report), and helping the knowledge-using unit implement the idea.
One idea is to pay for each posted idea. This promotes quantity but not quality of ideas and provides no incentive for idea creators to help adopters in implementation. A more complex alternative is to pay for the measured quality of each idea. This provides better incentives for quality ideas but is expensive due to the costs of evaluation. In addition, there is still no incentive for idea generators to help adopters. A third alternative is to pay bonuses based on knowledge-using units' claimed results. Variants on this process include having knowledge-using units nominate knowledge-creating units for internal awards, or giving each knowledge-using unit a fixed number of prizes it can award to knowledge-creating units that help it out.
Adoption depends in part on validation because ideas that are clearly effective are more likely to be adopted. But even effective ideas are sometimes not adopted and there are several psychological reasons for this. Potential adopters may find it hard to believe that one's own ideas are not better than those from elsewhere. In addition, many people find it difficult to see the applicability of ideas from elsewhere because understanding how ideas can work in new contexts can be difficult to perceive. Finally, it can be embarrassing to say others did it better since rewards typically go to "can do" people. These tendencies may be reduced if people are exposed to lots of stories of stolen, adopted, and adapted ideas, and of those using these techniques are acknowledged and rewarded.
7: Factors Affecting Knowledge Transfer:
Four factors were found that appear to influence knowledge transfer. They include:
Relational channels … frequency and depth of two-way human-to-human contact (Rulke, Zaheer, & Anderson, 2000).
Partner similarity … degree of similarity (e.g., interests, background, or education) between individuals (Almeida & Kogut, 1999; Darr & Kurtzberg, 2000)
Depreciation … loss of knowledge after transfer (Argote, Beckman, & Epple, 1990; Darr, Argote, & Epple, 1995)
Organizational self-knowledge … what do individuals know (Rulke, Zaheer, & Anderson, 2000)
Divergence of interests … congruency of individual and organizational goals (Alchian & Demsetz, 1972; Jensen & Meckling, 1976; Donaldson, 1990).
The quality of knowledge to be transferred (tacit versus explicit) affects knowledge transfer (Nonaka et al., 1995). Specifically, the more tacit the knowledge is, the more difficult it will be to transfer that knowledge. However, if all knowledge has a tacit component, as Polanyi argues it does, then some form of relational channel, defined broadly as two-way human-to-human contact, is necessary to transfer knowledge effectively.
An organization with many relational channels for transferring knowledge might expect more knowledge to be transferred than one that has few. Relational channels provide the human-to-human connection necessary to support the transfer of tacit knowledge. In this case, it is likely that more relational channels represent more and varied sources of shared information. For this reason, an organization that fosters many relational channels for transferring knowledge might be considered knowledge transfer fertile organization.
An organization with many similar partners might expect more knowledge to be transferred than one that has few similar partners, because it reduces the complexity of achieving understanding of complex concepts. In an organization in which all members have similar backgrounds, levels, and experiences, it is likely they will have the same understanding of a mission and share a strategic similarity (Darr et al., 2000). Strategic similarity among all members of an organization is likely to reduce barrier to sharing and therefore increase knowledge transfer. For these reason, an organization encouraging membership by many similar (strategically aligned) partners might be considered knowledge transfer fertile organization.
The concept of organizational self-knowledge refers to the degree to which individuals have knowledge of what they, as individuals have knowledge of what they, as individuals, know, and likewise for those individuals surrounding them. It is a key prerequisite to knowledge transfer because without this self-knowledge, the knowledge sender and receiver will most likely never meet to make a transfer (Rulke et al., 2000). An organization whose members have organizational self-knowledge might expect more knowledge to be transferred than one whose members have little organizational self-knowledge. Their shared understanding of what each knows, and what the others knows, facilitates the connections necessary for knowledge transfer. For this reason, an organization that encourages members to maintain or increase their organizational self-knowledge might be considered a knowledge transfer fertile organization.
An organization whose member's interests divergence can expert less knowledge to be transferred than one whose members have converging interests. A divergence of interest seems to increase the likelihood of self-serving behavior at the expense of overall organizational performance-because individuals either do not understand how organizational performance benefits them personally, or do not care. For these reasons, an organization that does not encourage members to recognize and compensate for the costs of transferring knowledge might be considered a knowledge-transfer infertile organization.
8: Organization Cultural Environment:
From an organizational perspective, the collective values and beliefs of the individual members of that organization represent a phenomenon called, "organizational culture". It constitutes a pattern of basic assumptions held by the people in the organization that it uses to address its problem of adaptation and integration (Schein and Edgar, 1990)/ Xenikou and Furnham (Xenikou, Anthena and Adrian Furnham, 1996) identified a number of factors related to organizational culture.
Four of these factors can be seen as a type of organizational environment. Following is a discussion of these factors.
1. Openness to change/innovation culture type: group the following concepts together: humanistic orientation, affiliation, achievement, self-actualization, task support, task innovation, and hands-on management (further defined as: managers should not just plan, but participate (Xenikou et al., 1996). An organization scoring high on this factor might be considered "friendly," and "open to change."
Hypothesis 1: Those organizations with openness to change/innovation cultures would be positively correlated to high knowledge transfer environments.
2. Task-oriented organizational culture type: group the following concept together: being the best, innovation, attention to detail, quality orientation, profit orientation, and shared philosophy (Xenikou et al., 1996). The authors compare this to the "Kaisen" philosophy espoused by successful Japanese companies that stress caution, incremental improvement. An organization scoring high in this factor might be considered "task-oriented" versus "people-oriented."
Hypothesis 2: An organization with a task-oriented culture would be positively correlated to a high knowledge transfer environment.
3. Bureaucratic organizational culture type: group the following concepts together: approval conventionality, dependence, avoidance, and [Lack of] personal freedom (Xenikou et al., 1996). The authors describe this culture as formal, with centralized decision -making. An organization scoring high on this factor might be considered "conservative" or "prudent".
Hypothesis 3: An organization with a bureaucratic culture would be negatively correlated to a high knowledge transfer environment.
Competition/Confrontation organizational culture type: group the following concepts together: oppositional orientation, power, competition, and perfectionism (Xenikou et al., 1996). The authors describe this culture as one where perfection is the goal, and where individuals might tend to react negatively towards the ideas of others and/or resist new ideas. An organization scoring high on this factor might be considered a "perfectionist" organization. Put negatively, one might call this organization a "dog-eat-dos" organization.
Hypothesis 4: that an organization with a competition/confrontation culture would be negatively correlated to a high knowledge transfer environment.
Having explored organizational culture, we now may ask what specific types of organizational culture might be identified as "fertile" or "infertile" with respect to knowledge transfer. It is to this task that we now turn.
Comparison:
Is there a correlation between types of organizational environment i.e. culture of organization and factors influencing knowledge transfer? It hypothesized that organizations scoring high on openness to change/innovation, and task-oriented organizational growth would be fertile to knowledge transfer. Second, it hypothesized that organizations scoring high on the factors of bureaucratic and competition/confrontation would be infertile to knowledge transfer. The research looked at Air Force squadrons, surveying a representative sample of the 1,495 active-duty squadrons included in the study with a 62-item, 5-point Likert-type instrument. Overall, 51 squadrons were surveyed, and 22 produced usable results. Both squadron and individual results were analyzed and both were similar. Squadron results showed that organizations scoring high on the factors of openness to change/innovation and task-oriented organizational growth appeared to score consistently high on three of the four measures of fertility to knowledge transfer. Organizations scoring high on the factors of competition/confrontation appeared to score consistently low on three of the four measures of fertility to knowledge transfer. The factor bureaucratic produced no significant correlations. In every case, the measure of fertility to knowledge transfer known as partner similarity did not behave as expected. The research concluded that there appears to be a correlation between organizational culture and factors influencing the transfer of knowledge, but concludes that the factors influencing the transfer of knowledge should be further explored, and a longitudinal study performed, before inferring any causal relationship.
Results:
Based on the factors affecting knowledge transfer, and the types of organizational culture discussed above, it indicates the fertility/in-fertility to knowledge transfer of each of the organizational culture types.
1. An organizational culture that is open to change, innovation, and achievement appears to be one in which,
There are likely to be more relational channels, because it is likely to support and nurture the human-to-human communications that comprise the relational channels.
It is also likely to exhibit partner similarity, leading to reduced friction in the transfer of knowledge.
Such an organization is also likely to exhibit organizational self-knowledge, which will support the seeking out and identification of those with knowledge to share.
Finally, such an organization is likely to have low divergence of interest, as the openness and communication is likely to foster the type of communication that leads to shared understanding and therefore shared goals.
Such an organizational culture is likely to be fertile to knowledge transfer.
2. An task-oriented organizational culture that is interested in being the best and being innovative appears to be one which would be likely to,
Support open relational channels, as a way to achieve its goals of excellence and innovation. Because of this, it is also likely to have partner similarity in the important area of common goals and interests.
Such an organization is likely to promote organizational self-knowledge as a means to ensuring broad understanding of the ways to achieve organizational goals of excellence and innovation.
In the broad areas of organizational goals, it is likely to have low divergence of interest, because such divergence would likely work against the achievement of organizational goals.
An organizational culture that is task-oriented in this way might be considered a knowledge-transfer fertile organizational culture.
3. An organizational culture that is bureaucratic appears to be one in which,
Relational channels are not well developed. The desire for conventional and avoidance of originality will work against the establishment of such channels.
It may also exhibit little partner similarity, particularly in the important areas of tacit knowledge development. Such development would work against the organizational culture of conformity and lack of personal point of view.
Because the focus would be on conventionality and following of rules, there would likely be little support for development of organizational self knowledge.
Finally there would likely be wider divergence of interests, because personal interests would not play a major role in organizational operations. Therefore, personal interest would be less important, and there would be less reason to ensure commonality.
Therefore, such an organization is likely to be relatively infertile to knowledge transfer.
4. An organizational culture that is marked by competition and confrontation appears to be one in which,
Relational channels will be limited and guarded, to protect the individuals in the organization from the negative effects of competition and perfectionism.
Partner similarity and organizational self-knowledge are also likely to be low for the same reason. Because of the need to guard against the confrontational approach of such and organization, there will be less development of the type of communication that develops partner similarity and organizational self-knowledge.
In such an organizational culture, divergence of interest is likely to be high, as each member of the organization seeks to achieve personal goals within a competitive, perfectionist organization.
Therefore, such an organization culture is likely to be relatively infertile to knowledge transfer.
R2: IT and Transfer of Knowledge:
A web-based Delphi survey is conducted to collect the top ten technologies used to assist knowledge leaders in completing their knowledge transfer initiatives. Referring to Nonaka and Takeuchi's knowledge creation model, results show that top priority is given to technologies used for extracting tacit knowledge, whereas most of the tools are currently used for supporting explicit knowledge.
Figure 2. Categorization of the reported technologies into
the knowledge creation and transfer framework
Conclusion:
Today task independency that workers have to perform requires a flow of information and a high level of knowledge sharing. This would imply appropriate approaches to transfer tacit knowledge such as communities of practice at a more organizational level or use of adequate technology to support the codification, storage, organization, and retrieval of knowledge. Our study has explored some of the mechanisms and issues related to knowledge sharing process. Even if the organization has implemented some knowledge management strategies, our investigation shows that knowledge management practice is still not an obvious organizational reality. Therefore, management needs to understand better the factors that facilitate knowledge sharing activities.
The concept of knowledge management continues to evolve. Regardless of its evolution, knowledge management is recognized as an important competitive factor for business worldwide [Martin, (2000), Nonaka et al., (1995)]. The literature revealed that the first organizational effort to manage knowledge focus on information technology solutions. These technology driven solutions, although important to knowledge management, often failed to achieve their objectives because they did not consider cultural factors critical to effective knowledge management (DeLong, 2000). Organizations failed to consider the relationship between knowledge management and organizational culture, and the cultural factors that impacted effective knowledge management initiatives. Just as knowledge management is critical to an organization's competitive advantage, organizational culture is critical to an organization's definition and execution of its business strategy. Hence, knowledge management cannot be effectively addressed without addressing organizational culture.
