Proceedings of the 12th European Conference on Knowledge ...

Mohammad Mirkazemi Mood, Farhad Daneshga and Mona Mirkazemi Mood
Step 3: According to Bottani (2009) we can conclude <strong>the</strong> relative importance <strong>of</strong> each knowledge
creation process by Formula 1. The calculated results for <strong>the</strong> relative importance <strong>of</strong> each process are
shown in Figure 4.
RIj= i ⊗ RIij j = 1, …. , m
Wi : The weighted importance <strong>of</strong> <strong>the</strong> i-th KM Performance criterion.
Rij : The fuzzy number expressing <strong>the</strong> relationship between <strong>the</strong> j-th knowledge creation process and
<strong>the</strong> i-th KM Performance criterion.
Step 4: This step shows <strong>the</strong> correlation between knowledge creation processes (HOWs). This
correlation is rephrased by experts, in terms <strong>of</strong> one <strong>of</strong> <strong>the</strong> phrases in Table 4. The correlation
determined by experts has been illustrated in <strong>the</strong> ro<strong>of</strong> part <strong>of</strong> <strong>the</strong> House <strong>of</strong> Quality in Figure 4.
Table 4: Correlations, graphic symbols and corresponding fuzzy numbers (Bottani 2009)
Degree <strong>of</strong>
correlation
(1)
Graphic symbol Fuzzy number
Strong positive(SP) ● (0.3; 0.5; 0.7)
Positive(P) ○ (0; 0.3; 0.5)
Negative(N) □ (-0.5; -0.3; 0)
Strong
Negative(SN)
■ (-0.7; -0.5; -0.3)
Step 5: Using Formula 2, <strong>the</strong> score <strong>of</strong> each knowledge creation process is calculated.
Scorej = RI j
⊕ T jj́
⊗
RI j́
j = 1, ….. , m
Tjj́ : The correlation between <strong>the</strong> j-th and <strong>the</strong> j́-th knowledge creation process.
RIj́ : The relative importance <strong>of</strong> j́-th knowledge creation process
Step 6: Having found <strong>the</strong> obtained scores <strong>of</strong> each process in <strong>the</strong> form <strong>of</strong> TFN, we should normalize
<strong>the</strong>se numbers. The way to normalize is to divide <strong>the</strong> scores by <strong>the</strong> highest score (Bevilacqua et al.
2006). For instance, in <strong>the</strong> given example <strong>of</strong> this study, 8.51 is <strong>the</strong> highest number.
Each <strong>of</strong> <strong>the</strong> knowledge creation processes is now considered as a WHAT variable in <strong>the</strong> House <strong>of</strong>
Quality. Besides, <strong>the</strong>ir normalized weight is considered as <strong>the</strong> relative importance (Wj) in <strong>the</strong> second
House <strong>of</strong> Quality.
4.3 Part 3
Step 1: Having reviewed <strong>the</strong> literature, we used a study conducted by Chong and Lee (2003) and
referred to in figure 2. These strategies, considered as <strong>the</strong> choices for <strong>the</strong> company, are now known
as HOW variables in <strong>the</strong> second House <strong>of</strong> Quality.
Step 2: Quite similar to what we did in <strong>the</strong> second step <strong>of</strong> part 2, <strong>the</strong> corresponding relationships
between knowledge creation processes and KM strategies are established. This time, Knowledge
creation processes are considered as WHAT variables. This can be done, like <strong>the</strong> second step <strong>of</strong> part
2, by <strong>the</strong> experts who use <strong>the</strong> language variables <strong>of</strong> Table 3. The relationship between knowledge
creation processes and KM strategies is illustrated in Figure 5. The relationships determined by
experts are almost identical with <strong>the</strong> results <strong>of</strong> Choi (2002) study.
Step 3: Similar to what we did in <strong>the</strong> third step <strong>of</strong> part 2, <strong>the</strong> relative importance <strong>of</strong> knowledge creation
processes is calculated with Formula 3 (Yager 1981, Bottani 2009).
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