摘要
论文根据客户协同产品创新特点,提出基于任务分组的产品创新任务与协同客户匹配策略。在此基础上,提出度量客户与任务之间匹配程度的模糊匹配度概念,并以最大化模糊匹配度为目标,建立匹配模型,采用排序方法进行求解,从而解决在一定的时间、成本等约束下,如何制定任务与客户匹配方案,以最大化客户与任务之间匹配度这一问题。最后进行实例研究,结果表明文中提出的模型和方法合理可行,易于操作,分析的结论能够为企业决策者为产品创新任务指派合适的客户提供参考和依据。
This paper first proposes a matching strategy according to the characteristics of customer collaborative product innovation. Then, the concept of fuzzy matching degree is put forward to measure the matching degree between customers and tasks. On this basis, we take the maximum of fuzzy matching degree between them as target to build matching model. By using ranking method, we can solve this model and determine the optimal matching scheme. In this way, this study deals with the matching problem between product innovation tasks and collaborative customers under the cost and time constraints. The empirical results illustrates that the proposed model and method is reasonable, achievable and easy to operate, the conclusion of analysis is capable of helping decision maker to assign customers to product innovation tasks.
出处
《科学学研究》
CSSCI
北大核心
2016年第1期142-150,共9页
Studies in Science of Science
基金
国家自然科学基金资助项目(71571023
71301176)
关键词
产品创新任务
协同客户
模糊匹配度
排序方法
product innovation task
collaborative customer
fuzzy matching degree
ranking method
