Abstract: The key to the formation of a knowledge alliance lies in the suitable matching between knowledge demanders and suppliers. To solve the problem of matching knowledge alliance demanders and suppliers, this paper proposes a matching decision analysis method in which the third-party evaluation information is used. First, expectation information given by knowledge demanders or suppliers to the opposite sides, as well as evaluation information given by the third-party with the consideration of matching attribute satisfaction level of knowledge demanders or suppliers to the opposite sides, is transformed into the one in the form of cumulative distribution functions, respectively. Then, overall matching degrees of knowledge demanders or suppliers to the opposite sides are measured. On the basis of this, a multi-objective optimization model is formulated to maximize the overall matching degree of the knowledge demanders and suppliers and to select the optimal matching pairs. Further, the linear weighting method is employed to transform the multi-objective optimization model into a single-objective optimization model. The optimal matching pairs can be determined by solving the single-objective optimization model. Finally, a case study is given to illustrate the feasibility and validity of the method proposed in this paper.

Key words: knowledge alliance, knowledge demanders, knowledge suppliers, third-party, matching