| 吴莹莹,肖旺群.基于因子聚类分析的儿童陪伴机器人用户细分[J].包装工程,2020,41(14):216-221. |
| 基于因子聚类分析的儿童陪伴机器人用户细分 |
| User Segmentation of Children Partner Robots Based on Factor and Clustering Analysis |
| 投稿时间：2020-04-20 修订日期：2020-07-20 |
| DOI：10.19554/j.cnki.1001-3563.2020.14.033 |
| 中文关键词: 市场细分 因子聚类分析 儿童陪伴机器人 交互设计 |
| 英文关键词: market segmentation factor and clustering analysis children partner robots interaction design |
| 基金项目:2018年度教育部人文社会科学研究项目（18YJCZH197） |
|
| 摘要点击次数: |
| 全文下载次数: |
| 中文摘要: |
| 目的 为解决目前儿童陪伴机器人设计中用户市场针对性不强、用户满意度低等问题。方法 首先分析了儿童陪伴机器人的交互系统模型，采用限定式KJ法设计了具有二十六个变量指标的儿童陪伴机器人行业用户满意度量表。其次提出在学龄儿童的用户细分中使用因子与聚类分析的复合模型方法，具体的操作为利用因子分析的方法对高维数据变量进行降维，根据因子分析得分及K均值聚类算法对数据进行分析，以细分出四个用户市场。结果 根据聚类分析样本数量区分重要性，得出了产品目标用户群之间的优先级；根据四种用户群态度，制定了相应的策略性建议。结论 提出了基于因子与聚类分析方法的用户细分方法，将有助于明确儿童陪伴机器人的市场定位；同时有助于改善儿童陪伴机器人用户的交互体验。 |
| 英文摘要: |
| The work aims to figure out the problems of weak pertinence of user market and low user satisfaction in the current design of children partner robots. Initially, the limited KJ method was employed to design a user satisfaction questionnaire in the industry of children partner robots with 26 variables by analyzing the interaction system model of children partner robots. Subsequently, the method of using the compound model of factor and clustering analysis in the user segmentation of school-age children was proposed. The specific operation was to reduce the dimension of high- dimensional data variables through factor analysis. According to factor analysis score and K-means clustering algorithm, the data were analyzed to subdivide four user markets. According to the number of cluster analysis samples, the priority among product’s target user groups was distinguished. Corresponding strategic suggestions were made by referring to the attitude of 4 user groups. A user segmentation method based on factor and clustering analysis is proposed, which will be helpful to clarify the market location of children partner robots and to improve the interaction experience of users. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
