A social route recommender mechanism for store shopping support
| Autor: | Yung-Ming Li, Chun-Chih Ho, Lien-Fa Lin |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Service (business)
Information Systems and Management 05 social sciences Context (language use) Advertising 02 engineering and technology Space (commercial competition) Recommender system Competitive advantage Management Information Systems Arts and Humanities (miscellaneous) 0502 economics and business 0202 electrical engineering electronic engineering information engineering Developmental and Educational Psychology 050211 marketing 020201 artificial intelligence & image processing Social media Business Mobile device Social network analysis Information Systems |
| Zdroj: | Decision Support Systems. 94:97-108 |
| ISSN: | 0167-9236 |
| DOI: | 10.1016/j.dss.2016.11.004 |
| Popis: | 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. 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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