Establishing Design Consensus toward Next-Generation Retail: Data-Enabled Design Exploration and Participatory Analysis

要旨

Integration of online and offline retail faces challenges in technology adoption, interaction style evolution and customer behavior shifts, while also being complicated by diverse perspectives from different stakeholders of consumers, retail staff, and retail business unit people. To explore how we can tackle the aforementioned challenges, this work applied the data-enabled design method and participatory data analysis to a case study, where 400 student consumers' shopping behavior data was collected, cross-analyzed, and visualized in a campus chain store. We then invited 13 stakeholders to join a co-creation workshop for a further participatory data analysis. In the workshop, the different stakeholders came to a design consensuses which we summarized into a series of practical design recommendations for improving the current store. Finally, we generalized the case study process as a contextual-informed-aware model, which can contribute to professional design practice for the retail industry.

著者
Yuan Yao
Tsinghua University, Beijing, China
Junai Cai
The Hong Kong University of Science and Technology, Hong Kong, China
Kexin Du
University of Chinese Academy of Social Sciences, Beijing, China
Yuxuan Hou
School of Visual Arts, New York, New York, United States
Haipeng Mi
Tsinghua University, Beijing, China
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3517637

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Collecting and Structuring Data

288-289
5 件の発表
2022-05-02 23:15:00
2022-05-03 00:30:00