Currently smart retail and e-commence have been experiencing an exponential growth and becoming an irresistible trend worldwide. This calls for sophisticated technologies from a wide spectrum of areas including the Internet of Things, big data, information retrieval, artificial intelligence, statistics to explore how to effectively take advantage of such high-volume data such as price, ratings, title, description, user preference, location, payment, and logistics, to drive sales and improve shopping experience. For example, with mobile payment, retail enterprises comprehensively gain insight into consumer demands in a digitized way and have reshaped the user interactions with the online platforms, which eventually improve sale volumes from both online and offline retails. Retailers should be taking advantage of the smart cities around the world to connect with the shopper of the future.

This Special Issue focuses on data driven business analytics approaches and related system development for understanding consumer behaviour, including intelligent retail operation, intelligent CRM, marketing, advertising, promotion, user interface, and so on. This Special Issue is open for submission of up-to-date and high-quality research and application contributions from wide range of professions including scholars, researchers, academicians and Industry people. Original R&D papers, case studies and state-of-the-art reviews will be accepted. We anticipate that the Special Issue will set new ground for further research and technological improvements in this important area.

Topics of interest include, but are not limited to:

• Challenges in Smart Retail
• Smart supermarkets, smart stores
• Food source and quality tracking
• Cashless checkouts
• Smart inventory control
• Mobile-enabled shopping
• Facial recognition and wireless for food
• Customers profiling
• Smart advertising
• Consumer analytics
• Consumption behaviour in smart cities
• Click models for E-commerce domain
• Personalization and contextualization
• Use of personal facets such as age, gender, location etc.
• Reviews and ratings in ranking
• User interfaces (mobile, desktop, voice, etc.) and personalization –
• Reviews and sentiment analysis
• Social signals in ranking and beyond
• Revenue vs relevance
• Trust and security issues
• Live experimentation
• Fashion E-Commerce
• Resources and data sets Retail analytics in E-commerce
• Advertising decisions and strategy optimization
• Display, sponsored-search, keyword and social advertising Real-time bidding
• Search and recommender systems
• Advertising personalisation
• Questions and answering, chat bots for Ecommerce


Guest Editors:
Dr Zhao Li (lead)
Dr Peng Zhang
Dr Tianyu Cao,
Prof. Jun Gao,
Prof. Ji Zhang,
Prof. Yuchen Li