工业工程 ›› 2022, Vol. 25 ›› Issue (5): 153-158.doi: 10.3969/j.issn.1007-7375.2022.05.019

• 实践与应用 • 上一篇    下一篇

个体优势导向的服务需求识别方法研究

余维田, 兰春秋, 王姝, 陈雪婷   

  1. 沈阳工业大学 管理学院,辽宁 沈阳 110870
  • 收稿日期:2021-06-02 发布日期:2022-10-20
  • 作者简介:余维田(1979—),男 (满族),辽宁省人,副教授,硕士,主要研究方向为企业战略管理与决策、组织行为与人力资源管理。
  • 基金资助:
    辽宁省社会科学规划基金资助项目(L20AGL002)

A Research on Service Demand Identification Method Based on Individual Advantage

YU Weitian, LAN Chunqiu, WANG Shu, CHEN Xueting   

  1. School of Management, Shenyang University of Technology , Shenyang 110870, China
  • Received:2021-06-02 Published:2022-10-20

摘要: 针对服务需求的科学识别与企业资源合理分配问题,提出一种个体优势导向的服务需求识别方法。采用个性化优势判别法识别每位顾客的需求指标权重结构;在此基础上进行聚类分析,并识别服务需求第一主旋律;随后以每类顾客需求参数结构与第一主旋律的相似度来刻画用户需求的个性化程度并划分等级。引用RFM模型计算群体客户价值并划分等级;进一步借助九宫格矩阵综合需求个性化程度、客户价值来展示服务需求识别的最终结果。以S高校快递末端物流服务需求识别为例,对所提方法的可行性和有效性进行验证。

关键词: 个体优势, 服务需求识别, 需求个性化程度, 群体客户价值

Abstract: Aiming at the problem of scientific identification of service demand and reasonable allocation of enterprise resources, a method for service demand identification oriented towards individual advantage is proposed. Firstly, the method of personalized advantage discrimination is used to calculate the weight structure of each customer's demand index; On this basis, cluster analysis is carried out and the first main melody of service demand identified. Then, according to the similarity between the structure of each customer demand parameter and the first main melody, the degree of personalization of customer's demand is described and graded. In addition, RFM model is used to measure customer value and divide the grade based on the result. Furthermore, it uses the nine grid matrix to display the final result of service demand identification integrating the degree of personalized demand and the grade of customer value. Finally, the feasibility and effectiveness of the method are verified by taking S university courier service demand identification as an example.

Key words: individual advantage, service demand identification, the degree of demand individuation, group customer value

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