The completeness of features provided by each E-Commerce is one of the criteria for buyers in determining where to make transactions. One of the features that attract the attention of buyers is the product recommendation feature. The difficulty of E-Commerce in implementing a product recommendation system is due to the large amount of information that is processed when filtering data in the recommendation process, especially recommendations for cultural products. This problem affects the cultural product recommendations given to be incompatible with the interests of each buyer. In this study, an analysis was carried out to develop a conceptual model to provide recommendations for cultural products using hyper-personalization. Systematic mapping and literature review were carried out to develop the model. The result of this study was the conceptual model that had been developed, that was expected to illustrate cultural product recommendation to increase buyer interest. This study was expected to help other research to gain insight, especially researchers who focused on examining the impact of product recommendation on buyer interest.
|Number of pages
|Procedia Computer Science
|Published - 2021
|6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy
Duration: 7 Aug 2021 → 8 Aug 2021
- Buyer interest
- Product recommendation