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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 team’s 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. |
