ABSTRACT:
A recurring theme in knowledge management literature is the role played by the social interaction among organisation members. This is because social interaction has been recognised as an importance process through which new knowledge is created from the sharing of existing knowledge. Social interaction among organisation members involves two main components, namely, the types of knowledge shared and the types of communication channels used. This article provides an approach for examining the types of knowledge shared and the types of communication channels used. It also develops a framework on which empirical work was conducted to validate the relationship between the types of knowledge shared and the types of communication channels used. The findings serve as a guide for identifying appropriate communication channels when knowledge is shared among organisation members.
Introduction
In an organisation, the typical activities that foster the sharing and creation of knowledge include hiring new staff with expertise, attending training programmes, setting up a Research and Development Department, and interacting with internal and external parties (Brooking, 1999; Davenport and Prusak, 1998). When the newly acquired knowledge possessed by an individual, a group or a department is shared with the rest of the staff, it is challenged, defended, refined and eventually becomes organisational knowledge. In other words, the sharing of existing knowledge leads to the creation of new knowledge. Since this process is highly social in nature (Havens and Knapp, 1999, Garvin, 1994; Nerney, 1997), most knowledge management literature invariably alludes to the importance of social interaction among organisation members.
Social interaction involves two main components, namely, the types of knowledge shared and the types of communication channels used. Each of these components will be examined in detail.
Types of Knowledge Shared
The knowledge shared among organisation members include expertise on product development, best practices (Trussler, 1998), process improvement discoveries (Scheraga, 1998), knowledge about customers' needs (Hiebeler, 1996), customers' habits and attitudes (Krogh, 1998). Apparently, when the interaction of the organisation members are aligned to strategic objectives of the organisation, the actual content of the knowledge shared will be very much influenced by the nature of business of the organisation (Trussler, 1998).
One fundamental approach to examining the types of knowledge shared is to classify it according to the tacit-explicit dimension (Brown and Duguid, 1991; Nonaka and Takeuchi, 1995). Explicit knowledge is considered to be objective and can be expressed unambiguously in words, numbers and specifications. Hence, it can be transferred via formal and systematic methods in the form of official statements, rules and procedures (Nonaka and Takeuchi, 1995; Polanyi, 1966). On the other hand, tacit knowledge is subjective, situational and intimately tied to the knower’s experience (Kidd, 1998). Thus, it cannot be formalised, documented or communicated easily to others. Insights, intuition beliefs, personal skills and craft and using rule-of-thumb to solve a complex problem are examples of tacit knowledge.
While such dichotomy is useful to understanding knowledge, it provides little clue for one to ascertain whether a given knowledge is actually tacit or explicit. In some cases, knowledge is not strictly polarised between the explicit-tacit dichotomy, but exists along a continuum of tacitness and explicitness (Kogut and Zander, 1993). Hence, when examining the types of knowledge shared, the notion of the “degree of explicitness” is more meaningful than the tacit-explicit dichotomy.
Measuring the Degree of Explicitness
Three sub-constructs can be used to measure the degree of explicitness of a given knowledge. They are: codificability, teachability and complexity (Kogut and Zander, 1993).
Codificability is the extent to which the knowledge can be articulated or represented in documents and words. This knowledge may be substantive, for example, in blueprints, or it may be procedural, for example, in a recipe for carrying out a task (Kogut and Zander, 1992). The more explicit the knowledge is, the greater is its codificability. Teachability is the ease by which the knowledge can be taught to another person. By definition, the more tacit the knowledge, the harder it is to teach it. Complexity refers to the number of critical and interacting elements of the knowledge needed to accomplish a given task. The more elements needed to complete a task, the greater is the complexity of the knowledge.
Table 1 provides a six-question instrument to determine the degree of explicitness for a given knowledge. Questions 1 and 2 correspond to the codificability sub-construct. Questions 3 and 4 correspond to the teachability sub-construct while Question 5 and 6 correspond to the complexity sub-construct.
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1 |
The evidence of possessing
this knowledge can be observed easily |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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2 |
A useful manual can
be written about this knowledge |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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3 |
A new staff can be
trained to understand this knowledge after attending a course |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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4 |
A new staff can
easily understand this knowledge after talking to a senior staff |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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5 |
This knowledge does
not built on other simpler, fundamental requisite knowledge |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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6 |
This knowledge is
simple to understand |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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Table1: Instrument to Measure Degree of Explicitness of Knowledge
Types of Communication Channels Used
The second component related to social interaction is the type of communication channels used. Communication channels are the media through which organisation members interact and share knowledge among themselves. Different channels of communication available in the organisation include those conventional ones as well as those which are technology-enabled. Examples of some common communication channels include face-to-face conversation, written-documents (such as memos and manuals), telephone, electronic mail, electronic discussion forum and video conferencing. The appropriateness and effectiveness of a channel to convey a message are related to its media richness (Madhavan and Grover, 1998).
Measuring the Media Richness
The media richness of a channel can be examined by its capacity for immediate feedback, its ability to support natural language, the number of cues it provides and the extent to which the channel creates social presence for the receiver.
The channel’s capacity for immediate feedback is determined by the amount and the promptness of the feedback the receiver can give to the sender (Timm and Detienne 1995). For example, written media and asynchronous discussion elicit no immediate feedback from the reader. On the other hand, a face-to-face discussion or an online video conferencing is highly interactive and feedback can be provided in the form of questions or comments.
A channel is regarded to have the ability to support natural language if the sender can structure and send the message in the most intuitive manner or as if it were in a conversation. Hence, face-to-face communication supports natural language more strongly than written messages.
The number of cues or senses provided by the channel includes both verbal and non-verbal cues such as tone of voice, hesitation, facial expressions, vocal cues, dress and posture (Short et al., 1976). These cues help the individuals to interact more effectively (Parks and Floyd, 1996). People perceive channels with more non-verbal cues as warmer and more personal. When these cues are missing, communication becomes impersonal.
The extent to which the channel can be used to create social presence is closely related to the number of cues provided. When a message receiver feels that the sender, rather than the medium, is actually delivering the message, the channel is said to afford a high social presence. The social presence provided by a channel influences individuals’ motivation to engage in interpersonal communication (Williams and Rice, 1983).
Table 2 provides an eight-question instrument to determine the media richness of a given communication channel.
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1 |
When using the
channel to communicate, you are able to raise a question and receive an
immediate response |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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2 |
When using the
channel to communicate, you are able to provide a huge amount of feedback to
the sender |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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3 |
You are able to
communicate through the channel in a language you find natural and intuitive |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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4 |
You are able to
communicate through the channel as if you are speaking |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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5 |
You are able to use
body language to express yourself through the channel |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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6 |
You are able to
vary the tone and volume of your voice through the channel |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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7 |
When using the
channel to communicate to your colleague, you feel you have been brought
closer to him/her |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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8 |
When using the
channel to communicate to your colleague, you feel your social ties have been
strengthened |
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(1) Strongly |
(2) Disagree |
(3) Neutral |
(4) Agree |
(5) Strongly |
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Disagree |
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Agree |
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Table 2: Instrument to Measure Media Richness
Propositions
Mentioned earlier, knowledge sharing requires organisation members to engage in social interaction with each other (Nonaka and Takeuchi, 1995; Davenport and Prusak, 1998). The media through which knowledge sharing takes place are the various communication channels available in the organisations (Daft et al, 1993; Krone et. al., 1987). Hence, knowledge shared has to be compatible with the media richness of the channel. For example, knowledge such as belief and insight (which are more tacit in nature) can be shared more easily through a communication channel with high media richness (such as face-to-face conversation) than through that with low media richness (such as a text-only document) (Madhavan and Grover, 1998). Conversely, the sharing of explicit knowledge tends to involve the use of document-based channels (Nonaka and Takeuchi, 1995; Nonaka and Konno, 1998; Morten et. al 1999). The following proposition is thus submitted:
The degree of explicitness of knowledge shared is negatively correlated to the media richness of the communication channel used
Methodology
The proposition can be empirically tested in an organisational context using a two-phase data collection method. The first phase involves focus group meetings while the second involves a questionnaire.
The purpose of the focus groups is to identify one important business process and a list of related knowledge to the business process. In addition, available communication channels used by organisational members are identified and listed. The focus group members are chosen on the basis of their seniority in the organisation. Their inputs give validity to the list of related knowledge and the communication channels used.
In the second phase of the data collection, a questionnaire having three sections has to be developed and administered to all organisational members. The questionnaire is built from Table 1 and Table 2.
Section 1 seeks to measure the degree of explicitness of each knowledge identified earlier. A 5-point Likert scale is used to capture the responses. As presented in Table 1, for each piece of knowledge, there would be six related questionnaire items.
Section 2 seeks to measure the media richness of the communication channel identified earlier. Similar to Section 1, A 5-point Likert scale is used to capture the responses. As presented in Table 2, for each communication channel identified, there would be eight related questionnaire items.
In Section 3 seeks to ascertain the communication channel most commonly used by the respondent to share or acquire knowledge. Each item in Section 3 represents a distinct piece of knowledge identified in the focus group. A nominal scale of the list of communication channels identified in the focus group is used to capture the responses. The respondent is required to select one communication channel which he or she used most commonly to share or acquire a given piece of knowledge. If the respondent did not share or acquire the knowledge with fellow colleagues, he or she could select "Not Applicable".
Based on the responses obtained, the research may use a regression model to ascertain the relationship between degree of explicitness of knowledge and the media richness of the communication channel used.
Organisational Application of Research
An empirical study based on the methodology specified was carried out in a local Institute of Higher Education. Three focus group meetings involving some twenty senior academic staff were conducted during the first phase of the data collection. Thereafter, a questionnaire built from Table 1 and Table 2 was administered to some fifty-one academic staff who had engaged in curriculum development duties.
From the focus group meetings, it was found that curriculum development was an important function to the organisation. Twelve distinct knowledge topics related to the process of curriculum development were identified. They were (t1) analysing students’ feedback, (t2) designing module objectives, (t3) keeping abreast on the current knowledge of the subject matter, (t4) identifying students’ characteristics, (t5) determining class size, (t6) determining depth and coverage of topics, (t7) designing sequence of topics, (t8) developing lecture notes and students' handouts, (t9) designing the supporting delivery methods (for example, Lectures, practicals, tutorials, e-learning), (t10) determining availability of resources and facilities , (t11) developing the assessment scheme and setting assessment questions, and (t12) designing the timing and frequency of assessment.
The focus group meetings also revealed seven communication channels that were commonly used by staff engaged in curriculum development tasks. They were (c1) email, (c2) staff meeting, (c3) impromptu face-to-face interaction, (c4) telephone, (c5) lunch/coffee-break chat, (c6) shared database and (c7) written Memo.
In the second phase of the data collection, a questionnaire developed from Table 1 and Table 2 was administered. The data collected from the questionnaire yielded the following: (1) the degree of explicitness of the each distinct knowledge identified (2) the media richness of the communication channels commonly used (3) the correlation between the degree of explicitness of the knowledge and the media richness of the communication channels used.
The degree of explicitness of the knowledge related to curriculum development is shown in Table 3, while the media richness of the communication channels commonly used is shown in Table 4.
Knowledge |
Degree
of Explicitness
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Mean |
StdDev |
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t1 |
3.78
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0.52 |
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t2 |
3.67 |
0.47 |
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t3 |
2.68 |
0.48 |
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t4 |
3.74 |
0.49 |
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t5 |
4.04 |
0.25 |
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t6 |
2.89 |
0.46 |
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t7 |
2.82 |
0.67 |
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t8 |
2.64 |
0.98 |
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t9 |
3.76 |
0.33 |
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t10 |
4.06 |
0.15 |
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t11 |
3.25 |
0.66 |
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t12 |
3.85 |
0.35 |
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Mean
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3.43 |
0.54 |
Table 3: Degree of Explicitness of Knowledge Related to Curriculum Development
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Communication
Channels |
Media Richness |
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Mean |
StdDev |
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MC-c1 |
4.35 |
0.67 |
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MC-c2 |
2.49 |
0.78 |
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MC-c3 |
3.89 |
0.73 |
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MC-c4 |
2.87 |
0.78 |
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MC-c5 |
4.38 |
0.60 |
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MC-c6 |
1.98 |
0.65 |
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MC-c7 |
1.64 |
0.65 |
Table 4: Media Richness of Communication Channels Commonly Used
The correlation between the degree of explicitness and the communication channel used was analysed using a regression model. The results are shown in Table 5, Table 6 and Table 7.
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Model |
R |
R
Square |
Adjusted
R Square |
Std
.Error of the Estimate |
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1 |
.818a |
.669 |
.669 |
.6007 |
a.
Predictors:
(Constant), EK
In Table 5, the dependent variable is media richness of the communication channels used (MC), while independent variable is the degree of explicitness of knowledge shared (EK). R2 measures the percentage of variability in the dependent variable (MC) which can be explained by the regression model. It can be seen that the EK has a 66.9% influence on the dependent variable MC (R2 = 0.669).
|
Model |
|
Sum
of Squares |
df |
Mean
Square |
F |
Sig. |
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1 |
Regression |
409.175 |
1 |
409.175 |
1133.987 |
.000a |
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Residual |
202.064 |
560 |
.361 |
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Total |
611.239 |
561 |
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a.
Predictors:
(Constant), EK
b.
Dependent
Variable: MC
Shown in Table 6, there is statistical evidence to support the existence of a relationship between the degree of explicitness of existing knowledge shared (EK) among academic staff developing curriculum and the media richness of the communication channels used, F(1,560) = 1133.987, p < .05.
|
Model |
|
Unstandardized Coefficients |
Standardized
Coefficients |
T |
Sig. |
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B |
Std.
Error |
Beta |
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1 |
(Constant) |
8.767 |
.170 |
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51.435 |
.000 |
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EK |
-1.656 |
.049 |
-.818 |
-33.675 |
.000 |
a.
Dependent
Variable: MC
From Table 7, it can be seen that the standardised coefficient of EK is negative (b = -0.818). This implies that the independent variable, EK, negatively correlates with the dependent variable, MC.
In summary, the results show that the degree of explicitness of knowledge shared is negatively correlated to the media richness of the communication channels used. In the empirical study, the knowledge of developing lecture notes and students handout (t8) was considered to be of low degree of explicitness (2.64 ± 0.98). Hence, when a staff needs to share this knowledge, the communication channels having a relatively high media richness, for example, lunch/coffee-break chat (c5) was used.
In promoting knowledge sharing in organisations, managers therefore need to examine the degree of explicitness of knowledge, and encourage organisation members to select appropriate communication channels based on its media richness. For example, if insights and intuition (knowledge which are regarded to be of low degree of explicitness) were to be shared, managers should not expect organisation members to share such knowledge through a communication channel having low media richness, such as the shared database. Instead, face-to-face interaction ought to be promoted. Communication channels having low media richness should only be used to share knowledge having high degree of explicitness.
Conclusion
This article argues that the process of knowledge sharing and creation heavily involves social interaction. Two components related to social interaction are the types of knowledge shared and the communication channels used. The types of knowledge shared can be analysed using its degree of explicitness while the communications channels used can be analysed using its media richness. This article further posits that the degree of explicitness of knowledge shared is negatively correlated to the media richness of the communication channels used. Based on this proposition, an empirical study was conducted in an Institute of Higher Education. The results confirmed the proposition.
The findings from the empirical work help managers choose appropriate communication channels to share the types of knowledge with other organisations members.
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