A smart assistant toward product-awareness shopping

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• 作者：Chia-Chen Chen (1)
  Tien-Chi Huang (2)
  James J. Park (3)
  Huang-Hua Tseng (4)
  Neil Y. Yen (5)
  
• 关键词：Smart shopping assistant ; Sensor technique ; Smart phone ; Home shopping
• 刊名：Personal and Ubiquitous Computing
• 出版年：2014
• 出版时间：February 2014
• 年：2014
• 卷：18
• 期：2
• 页码：339-349
• 全文大小：741 KB
• 作者单位：Chia-Chen Chen (1)
  Tien-Chi Huang (2)
  James J. Park (3)
  Huang-Hua Tseng (4)
  Neil Y. Yen (5)
  
  1. Department Management Information Systems, National Chung Hsing University, Taichung, Taiwan
  2. Department of Information Management, National Taichung University of Science and Technology, Taichung, Taiwan
  3. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea
  4. Department of Information Management, Tunghai University, Taichung, Taiwan
  5. School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan
  
• ISSN：1617-4917

文摘

This research employs sensor techniques (i.e., radio-frequency identification system) in developing a smart assistant for home furniture shopping. The implemented assistant provides friendly accessed interface that allows consumers to easily locate the product, confirm the detail information of it, and moreover, provide real-time recommendation(s) in accordance with interests of consumers. Unlike conventional online stores, the system offers the retailer extra spaces for varieties of merchandize, eliminated duplicated products display, etc. In addition, the assistant can avoid an unnecessary crashing of huge shopping carts in a crowded situation. This research discusses a new shopping pattern implemented by a smart assistant with the integration of consumer, retailer, and warehouse sides. In addition, an application is provided on smart phones in conjunction with the system to improve the competiveness in the market and increase the loyalty of their consumers. The experiment results demonstrate that collected data from end users (e.g., consumer, warehouse, and retailer itself) may provide essential information to revise business models.