on the best fit. Quick and correct KC at the right time aids in further improving the development
lead-time and product quality.
Such successful innovation is often associated with adoption and execution of all SECI modes
within any PD phase. This dissertation attempts to argue with this general notion and to
distinguish different PD phases’ affinity corresponding to distinct SECI mode. In this regard, an
extended Fuzzy Analytic Hierarchy Process (EFAHP) approach to determine the ranking in
which any PD phase is influenced from SECI modes is proposed. In the EFAHP approach, the
complex problem of KC is first itemized into a simple hierarchical structure for pairwise
comparisons. Next, a triangular fuzzy number concept is applied to capture the inherent
vagueness in linguistic terms of a decision-maker. This dissertation recommends mapping the
triangular fuzzy numbers (TFNs) with normal distributions about X-axis when the pessimistic
value of one TFN is less than the optimistic value of other TFN (t23 ≤ t11). This allows us to
develop a mathematical formulation to estimate the degree of possibility of two criteria as
opposed to zero resulted by the use of the current technique in the literature. In order to
demonstrate the applicability and usefulness of the proposed EFAHP in ranking the SECI modes,
an empirical study of development phase is considered. After stringent analysis, we found that
the combination mode was the mode that highly influenced the development phase.