| 摘要: |
| 目的 针对大数据分析下网络消费体验设计的内容要素与度量方法展开研究， 归纳并构建大数据分析下网络消费体验设计的理论模型。方法 通过文献分析， 得出大数据分析的特点与优势及对用户体验的促进作用。以客户体验旅程和比较分析方法为基础， 对大数据分析下网络消费体验设计要素与度量方法进行探索， 并结合对亚马逊网站购物体验的典型个案分析， 推导出其理论模型结构。结论 阐明了大数据分析对产品与服务的整体用户体验优化具有重要的推动作用， 归纳出了客户网络消费体验旅程的7个要素内容和5个度量指标体系， 结合情境分析得其理论模型的内容、 方法和技术的3个层面。 |
| 关键词: 大数据分析 用户体验 网络消费体验 |
| DOI： |
| 分类号:TB472 |
| 基金项目: |
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| Design Elements and Measurement Methods of Online Consumption under the Big Data Analysis |
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CHEN Xing-hai, HE Ren-ke
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Hunan University，Changsha 410082，China
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| Abstract: |
| It aims to unfold researches into the contents factors and measurement methods of the design of online consumption experience under big data analysis，summarize and construct a theoretical model for online consumption experience under big data analysis.Through literature analysis， it draws out the features and advantages of big data analysis and its promoting effect on user experience. Based on the customer experience process and comparative analysis， it explores into the design content factors and measurement method of online consumption experience under big data analysis and combines a typical case analysis on online shopping experience of Amazon to derive its theoretical model structure. It illustrates the important promoting effect of bid data analysis on the optimization of overall user experience of products and services， concluding seven elements and five measurement index systems in the process of online customer consumption experience.Combined with scenario analysis， it further reveals three aspects of the theoretical model： its contents， methods and technologies. |
| Key words: big data analysis user experience online consumption experience |
