Under the influence of global competition, innovative products and
services of certain enterprises have eliminated many of the conventional
industries in a very short time. To cope with the stiff global competition,
enterprises must keep on innovating products and services to stay ahead of the
competitors. However, the consecutive innovations must rely on knowledge
creation, especially, high-technology products. Thus, knowledge creation is a
vital activity for an enterprise to thrive in the competition, and it can be
achieved via teamwork and collective learning.
However, the way the enterprise selects the perfect team for knowledge
creation is the key to success. This study proposes a mathematical model for
enterprises to select the best team by evaluating the teamís performance of
knowledge creation. Three variables are used in the models, i.e. knowledge
complexity, knowledge correlation, and knowledge level. Via the model, the time
needed and the amount of knowledge gained for each member after the knowledge
creation can be obtained, and the processes continue until the creation of the
target knowledge is achieved. The results of the cases show that the proposed
model can help enterprises select the best possible candidates to form a team
for knowledge creation.
JEL classification numbers: C61, M10.
Keywords: Knowledge management, Mathematical programming, Knowledge
complexity, Knowledge level, Knowledge correlation.