管理评论 ›› 2021, Vol. 33 ›› Issue (4): 124-135.

• 技术与创新管理 • 上一篇    下一篇

考虑第三方评价信息的知识联盟供需双方匹配决策方法研究

李永海1, 樊治平2, 张惠民1   

  1. 1. 河南工业大学管理学院, 郑州 450001;
    2. 东北大学工商管理学院, 沈阳 110167
  • 收稿日期:2018-03-22 出版日期:2021-04-28 发布日期:2021-05-06
  • 通讯作者: 樊治平(通讯作者),东北大学工商管理学院教授,博士
  • 作者简介:李永海,河南工业大学管理学院副教授,博士;张惠民,河南工业大学管理学院副教授,博士。
  • 基金资助:
    国家自然科学基金项目(71501063;71871049);河南省哲学社会科学规划项目(2018CJJ078);河南省高校科技创新人才(人文社科类)项目(2016-CX-021);河南省高校人文社科重点研究基地物流研究中心项目(2015-JD-04)。

Decision Method for Matching Knowledge Alliance Demanders and Suppliers Considering the Third-party Evaluation Information

Li Yonghai1, Fan Zhiping2, Zhang Huimin1   

  1. 1. School of Management, Henan University of Technology, Zhengzhou 450001;
    2. School of Business Administration, Northeastern University, Shenyang 110167
  • Received:2018-03-22 Online:2021-04-28 Published:2021-05-06

摘要: 知识供需双方能否得到最佳匹配对于知识联盟的形成至关重要。本文针对知识联盟供需双方匹配决策问题,提出了一种考虑第三方评价信息的匹配决策分析方法。首先,将知识供需双方提出的关于对方的期望要求信息,以及第三方评价主体给出的关于知识供需双方满足对方关注匹配属性的测评信息分别转化为累积分布函数形式的信息。其次,通过测度知识供需双方分别针对对方的综合匹配满意度,并考虑将知识供需双方的综合匹配满意度最大化作为目标,构建了多目标优化模型,进一步地,通过线性加权方法将其转化为单目标优化模型,通过求解得到最优的匹配结果。最后,通过一个实例分析来说明本文提出方法的可行性与有效性。

关键词: 知识联盟, 知识需求方, 知识供给方, 第三方评价主体, 匹配

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