A social route recommender mechanism for store shopping support
作者:
Highlights:
• Mobile devices provides retailers with an opportunity to offer a context-aware guidance service for in-store shopping.
• We propose a contextual store shopping recommendation system for customers’ shopping path support.
• The proposed framework is developed based on extracting and analyzing shopping information and social information.
• The proposed model is effective in providing an appropriate shopping route and enhancing users’ shopping experience.
摘要
To survive in a fiercely competitive business environment, it has become increasingly important for physical retailers to provide customers with services offering a better shopping experience. Many renovate and enlarge their shopping spaces to make their stores more enjoyable places to visit. The growth in social media and the use of mobile devices provide retailers with an opportunity to offer a context-aware guidance service to enhance customers' in-store shopping experience. In this research, by extracting and analysing shopping information (shopping context, visiting trajectory) and social information (user's interest, friends' influence), a contextual store shopping recommendation system is proposed to provide an appropriate route for first-time customers or those who are unfamiliar with a retailer's shopping space. Our experimental results show that the proposed model is effective in providing an appropriate shopping route and enhancing users' shopping experience, which could significantly improve the profitability and competitive advantage of the retailers.
论文关键词:Social network analysis,Markov chain,Shopping context,User preference
论文评审过程:Received 4 November 2015, Revised 18 November 2016, Accepted 20 November 2016, Available online 22 November 2016, Version of Record 24 January 2017.
论文官网地址:https://doi.org/10.1016/j.dss.2016.11.004