Matching demanders and suppliers in knowledge service: A method based on fuzzy axiomatic design

The advancement of knowledge service has enabled the demanders and suppliers to find satisfied cooperation results. An optimal match between demanders and suppliers can facilitate continuous improvement and efficiency in knowledge services. While selecting suitable matching knowledge demander and supplier pairs is of significance for effective knowledge services, an area that has been generally neglected in previous studies. This paper reports on a method for effectively matching suitable knowledge service demanders and suppliers in which the expectation levels of attributes given by demanders and suppliers are considered. Linguistic information is used to describe the demanders and suppliers' expectation levels and their actual levels. A new matching degree calculation method is proposed which takes account of the fuzzy linguistic information. First, the matching relationship between the demanders and suppliers is defined. Then, from the principle of axiomatic design (AD), a method based on fuzzy axiomatic design (FAD) is developed to identify the matching degree between the knowledge demanders and suppliers. Further, a multi-objective optimization model is formulated to maximize the overall matching degree of the pairs and to select the optimal matching pairs. Finally, an example illustrates the potential applications of the proposed method. The obtained computational process and results clearly demonstrate how optimal matching pairs can be identified for knowledge services' demanders and suppliers.