ABSTRACT:
Business managers and academic researchers are seeking to discover processes by which organisations can leverage knowledge for improved performance. It is difficult to discover general principles in this area since knowledge processes vary from industry to industry and from organisation to organisation. It is suggested that a way forward is to categorise these processes within knowledge management styles and then to identify these styles in particular organisations. The question will be asked whether these styles are different in different industries, and if they are different, which one of these styles or a set of them is significantly deployed by the industry. Four dominant knowledge management styles have been identified, namely: adoption, standardisation, systemisation and articulation. Three industries are used to compare the results: system-based, material-based and service-based industries. Using the one-way ANOVA analysis and post-hoc test analysis, it is found that the four knowledge management styles are significantly different according to these industries. In addition, the deployment of these styles is also different according to these industries.
Keywords: Knowledge Management,
1. Introduction
Al-hawari and Hasan (2002) have developed a knowledge space model (K-space) that has subsequently been used as the basis for research through which four dominant knowledge management styles have been identified, namely: adoption, standardisation, systemisation and articulation (Hasan & Al-hawari 2003). These styles involve a set of drivers derived from the enabler cycles of Von Krogh et al (2000). Knowledge enablers work in cycles to create and transfer knowledge, and are related to how particular managers’ deal with the knowledge assets of the firm (ibid).
The adoption and articulation styles were found to positively affect organisational performance since these styles were usually
deployed to good effect by organisations in
material–based industries, as is the case in countries such as
The previous research has not yet tested which style, or a set of styles is significantly deployed by the industry. This paper will investigate these styles within the three industries using the one-way ANOVA analysis and post-hoc test.
The paper begins with a brief overview of the knowledge management styles in the literature. It then presents the results of an empirical study that addresses the research question and concludes with a brief discussion and conclusion of these results.
2. Knowledge
Management Styles Addressed in the Literature
Knowledge management style is related to how particular managers deal with the knowledge assets of the firm (Birkinshaw 2002) and what approaches they deploy for KM (Jordan & Jones 1997). Style is a personal attribute and so knowledge management style varies from one manager to another, and may be influenced by the culture of their organisation. Some managers recognise knowledge management as a purely technology issue while others recognise it as a strictly human concern. In the technological approach, knowledge is treated as more explicit, and therefore it is usually codified; in the belief that this guarantees efficiency. However, this is rarely the case (Jordan & Jones 1997). Other approaches rely heavily on human knowledge, but are also unlikely to be successful if they are not integrated with approaches linked to modern technology (ibid). The majority of managers recognise knowledge management as a mixture of the human and technical with an emphasis depending on how they classify knowledge itself.
Jordan & Jones (1997) have suggested five dominant knowledge management styles as follows, arguing, as we do, that with one style it is not possible to conduct efficient and effective knowledge management:
1. The knowledge acquisition style with two dimensions: focus and search.
2. The problem solving style with four dimensions; ‘location’, ‘procedure’, ‘activity’ and ‘scope’.
3. The dissemination style with two dimensions: ‘processes’, ‘breadth’. Process describes whether knowledge is shared formally or informally. Breadth describes knowledge sharing as wide or narrow.
4. The ownership style with two dimensions: identity and resources. Identity refers to the extent to which individuals regard their knowledge base as being part of their own personal identity. On the other hand resource ownership relates to the way in which knowledge is dispersed.
5. The memory style refers to the orientation adopted within the company for storing knowledge and consists of one dimension, which is representation.
Kusonaki et al (1998) have studied organisational performance through organisational capabilities. Organisational capabilities consist of multilayered knowledge and, based on these layers, are classified into two types, local and process capabilities, along two dimensions: modularity and designability. Using a large-scale data-set on product development organisations of Japanese manufacturing firms, it was found that the dynamic interaction of many knowledge practices plays a crucial role as core capabilities for product development. It was significant that these organisations were relatively competitive and the dynamic interaction of knowledge required individual knowledge to be transferred across the organisation. Typical examples included communication as a technology-oriented practice and coordination as a human-oriented practice across different functional groups.
Choi & Lee (2003) classified four knowledge management styles based on tacit and explicit dimensions. These styles were found to vary from industry to industry. Furthermore, organisations which adopted more dynamic styles had higher performance than others. In the dynamic style, organisations tended to have a mixed approach between human and technology activities.
In a study of nine Korean companies, Lee and Suh (2003) found that seven out of nine companies placed greatest importance on combinations in terms of the SECI knowledge conversion types. The next important process was externalisation. The third one was socialisation and the last one was internalisation. They argued that some companies placed equal amounts of importance on the four types of knowledge conversion. But mostly companies placed different stresses on different types because of different corporate size and situation. They also found that use of the four knowledge-conversion types are different from industry to industry, but did not confirm this by empirical testing.
Knowledge management styles; articulation, adoption, standardisation, systemisation involve a set of activity and knowledge elements that influence the availability (diffusion), codifiability and applicability (abstraction) dimensions of organisational knowledge (Hasan & Al-hawari 2003, 2004). The influence of each style can be determined by different values of these dimensions as follows:
¨
In Articulation, the choice of knowledge elements results in variable
levels of the codification dimension and applicability of knowledge (the
abstraction dimension) but the availability of knowledge (the diffusion
dimension) is constantly high because the activities provide knowledge that is
highly accessible and stored in systems that make it easy to access. The
articulation of knowledge constitutes a context for justification (Tell, 1997,
2000; Grand & Von Krogh 2000) and enables the creation of agreed representations
and the common representations, which, in turn, allow for better task
co-ordination (Prencipe & Tell 2001). In one
sense, codification is an extension of articulation brought forward in
linguistic and symbolic representation (ibid). Further explicit knowledge is
more likely to be articulated and more often captured in the form of text,
tables and diagrams (Dayasindhn 2002). Knowledge acquisition in the articulation
style is externally focused so that the organisation
is deliberately scanning the external environment for ideas and practices.
¨
In Adoption, the choice of knowledge elements results in variable
levels of the availability and applicability of knowledge (the abstraction and diffusion
dimensions) but codification is constantly low because the activities involve
mainly human knowledge.
¨
In Standardisation, the
choice of knowledge elements results in variable levels of the codification and
applicability of knowledge but the availability is constantly low because the
activities can be accomplished by a closed team or group. Within such
teams there are experts, programmers and analyst who can facilitate the task of
knowledge conversion. Here knowledge acquisition is internally focusssed and the organization is seeking knowledge from employees and
work-based cases.
¨
In Systemisation, the choice
of knowledge elements results in variable levels of the applicability and
availability of knowledge (the abstraction and diffusion dimensions) but codification is constantly high because of the activities involve
knowledge which is highly classified and indexed in systems.
None of the previous researches have tested which style, or a set of styles
is significantly deployed by the industry. This
research will utilize the four styles; articulation, adoption, standardisation, and systemisation in order to test their difference among different
industries.
3. Research Design, Data
Collection And Analysis
3.1. Questionnaire Development
The questionnaire covers the four knowledge management styles (articulation,
adoption, standardisation, systemisation).
The development of the questionnaire began with the production of generic descriptions of a set of knowledge elements selected from the literature, particularly the work on knowledge enablers by von Krogh et al (2000), to cover all constructs proposed. Next, a set of items was developed to measure the constructs. Questionnaire items were developed in an iterative manner based on recommendations from Churchill (1979). First, the author developed a list of candidate items covering the four knowledge management styles from the literature as described above. One manager and two other people working on a knowledge management project in a local company reviewed this list of items. As a result of this some revisions were made to the number and content of the questions. The first draft of questionnaire was constructed by placing each knowledge management practice description at the top of a page, followed by the relevant set of items.
The final questionnaire was developed and the demographic information is added; the age, the sex, number of years working in the organisation, job status, total years income and the highest completed level of education. Each items featured a five-point Likert scale, with response options ranging from "strongly disagree" to" strongly agree." The questionnaire was then reviewed by other researchers and further refined.
The scale was developed based upon two stages approach (Stratman & Roth 2002) and the recommendation of (Churchill 1979). In the first stage, precise definition and requirement items for each construct were developed with the tentative indications of reliability and validity. In the second stage, these items were refined and validated using survey data collected on the scaled developed in the first stage. The reliability testing was done using Cronbach’s alpha seeking a value greater than (0.7) (Nunnally 1978).
3.2. The Administration Of The Questionnaire
In stage one, a pilot study was done to confirm the reliability and the validity of some new scales such as the four knowledge management styles . The data used to validate the scale were collected through the use of self-administrated survey questionnaire. The pilot survey was carried out with 45 managers in different organisational units in a local organisation. These units have their own budget, profit and their own employees and so for the purpose of validation of the four management styles the different departments were taken to represent the different organisations. The number of returned respondents was 30, of which four were discarded from the analysis as many questions were not answered. Therefore, 26 questionnaires were used in the pilot analysis.
In stage 2 the questionnaire was sent to 338 profitable small and medium enterprises. The respondents were executive managers, top managers and middle mangers. 25 were returned as undelivered because of faulty address and 15 cases undelivered because of the managers were no longer at their positions. 8 cases had many missing response items while the total of 152 questionnaires were returned in a form eligible for the analysis. The overall response rate for this study was 45% which was regarded as relatively high, especially as the respondents are managers who are supposed to be too busy to answer questionnaires. The SPSSä (version 11) was used for the statistical analysis of the survey data.
3.3. Results
Tables 1, 2, and 3 summarise the respondent characteristics in term of main industry type, total sale revenue and the number of employees.
The three industries are mainly classified based on the product development. Some industries have a system based approach for developing their product, some have a material based approach and some have a service approach. Kusunoki et al (1998) state product development is a field with high uncertainty and complexity, typically requiring firm-specific capabilities. The capability of organizations in term of product development is a result of knowledge implementation in the individual, departmental and whole organization levels ( Ibid).
Choi and lee (2003) investigate a KM styles implementation in different industries according to different department managers’ responses. Organizational knowledge creation and sharing capabilities are underpinned by managers who are shaping the employee positive and negative emotion at work.. Furthermore, these managers set the tone for how a department, a division or the entire firm should perform( Awad & Ghaziri, 2004).
Table
1: Main Industry Types
|
Percent |
Frequency |
Industry
type |
|
12.5 |
19 |
System-based
|
|
67.1 |
102 |
Material-based |
|
20.4 |
31 |
Service-based
|
|
100 |
152 |
Total |
Table
2: Total Number of Employees
|
Range of employees number |
Frequency |
Percent |
|
100-200 |
67 |
44.1 |
|
201-300 |
17 |
11.2 |
|
301-400 |
13 |
8.6 |
|
401-500 |
53 |
36.1 |
|
Total |
152 |
100 |
Table
3: Total Sales Revenue
|
Range of revenue |
Frequency |
Percent |
|
<=100000000 |
86 |
56.6 |
|
100000001-200000000 |
35 |
23 |
|
200000001-300000000 |
10 |
6.6 |
|
>=300000001 |
21 |
13.8 |
|
Total |
152 |
100 |
4. The Effect Of Industry Type
One-way ANOVA analysis was used to test whether the industry type is making a significant difference among the four styles or not. For analysis purposes the main industries were divided into three industry groups, system-based industry, material-based industry and service-based industry. Table 4 shows that the three industry types can make significant difference (p<0.05) among the four styles.
Table 4: Industry Types vs. The
Four Knowledge Management Styles
|
Knowledge
management styles |
Sum of
Squares |
df |
Mean
Square |
F |
Sig* |
|
|
Adoption |
Between Groups |
188.410 |
2 |
94.205 |
5.100 |
.007 |
|
Within Groups |
2752.057 |
149 |
18.470 |
|
|
|
|
Total |
2940.467 |
151 |
|
|
|
|
|
Systemisation |
Between Groups |
94.591 |
2 |
47.295 |
6.493 |
.002 |
|
Within Groups |
1085.403 |
149 |
7.285 |
|
|
|
|
Total |
1179.993 |
151 |
|
|
|
|
|
Standardisation |
Between Groups |
110.505 |
2 |
55.252 |
8.715 |
.000 |
|
Within Groups |
944.594 |
149 |
6.340 |
|
|
|
|
Total |
1055.099 |
151 |
|
|
|
|
|
Articulation |
Between Groups |
1013.125 |
2 |
506.563 |
41.097 |
.000 |
|
Within Groups |
1811.915 |
147 |
12.326 |
|
|
|
|
Total |
2825.040 |
149 |
|
|
|
|
* Significant at the .05 level.
5. Post-hoc
Analyses
The post-hoc analysis used to find which a style or a set of styles is/are the most important to the industry. The most widely used post hoc test in Psychology and the behavioural sciences is Tukey's Honestly Significant Difference or HSD test (Price, 2004). Post hoc tests can only be used when the 'omnibus' ANOVA found a significant effect (Price, 2004). Table 6 shows the result of Tukey post-hoc analysis. Both the system-based and material based industries are deploying adoption style, since the adoption is significantly different in both industries (p<0.05). On other hand, the adoption style doest not make a significant difference between a service-based industry and the rest (p>.05). Consequently, it seems that the adoption style is not important to the service-industry compared with the other industries.
Because of the significant difference between a system-based and a material-based industry (p<0.05) in one side, and on another side between system- based industry and service-based industry (p<0.05). Therefore, it is not only the systemisation style seems to be important for the three industries, but also it is the most important in the system-based industry than the rest of the industries.
The standardisation style seems to be important for both a system-based and a material-based industry, since there is significant difference between them (p<. 05). Because of neither a system-based, nor a material-based industry make a significant difference (p>0.05) with the service-based industry, it is not the case for the service-based industry.
Finally, both a system-based and a material-based industry have a significant difference in the articulation style (p<0.05). Consequently, the articulation style is deployed in the both industries. Furthermore, there is a significant difference between a material-based and a service-based industry in related to the articulation style (p<0.05). Subsequently, both a material-based and a service –based industry is deploying the articulation style. In addition, the articulation style is the most important style in the material based.
Table 5: Post-hoc Analysis using the Tukey HSD
Dependent Variable (I) ( Industry (J)( ndustry Mean Difference (I-J) Sig.* Adoption 1.00 2.00 -3.4226 .005 3.00 -2.7063 .081 2.00 3.00 .7163 .696 Systimisation 1.00 2.00 -2.4236 .001 3.00 -2.1868 .017