面向多服务价值链的业务资源双边匹配模型

Bilateral matching model of business resources for multi-service value chain

在第三方云平台环境下,为了帮助多服务价值链上的企业从海量信息资源中精准地获取高质量有价值的业务资源,提出一种面向多服务价值链的业务资源双边匹配模型。该模型首先根据多服务价值链上不同企业实际的业务需求构建供需双方的满意度评价指标体系,然后结合模糊理论处理供需双方的满意度评价矩阵,最后将业务资源双边匹配模型转换为多目标优化模型,并采用线性加权的方法求解多目标优化模型,从而获得令供需双方最满意的业务资源。以汽车售后服务业务的配件数据资源为例验证了所提模型的合理性和有效性。

In the third-party cloud platform environment,to help enterprises in the multi-service value chain accurately obtain high-quality and valuable business resources from the massive information resources,a bilateral matching model of business resources for multi-service value chain was proposed.A satisfaction evaluation index system for both supplier and demander was constructed based on the actual business needs of different companies in the multi-service value chain,then the satisfaction evaluation matrix of the supplier and the demander was processed by combining with fuzzy theory,and finally the business resource bilateral matching model was converted into multi-objective optimization model,and the linear weighting method was used to solve the multi-objective optimization model,so as to obtain the most satisfactory business resources for both supply and demand.Taking the parts data resources of automobile after-sales service business as an example,the rationality and effectiveness of the proposed model were verified.