English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper presents the result of a controlled experiment studying how mood state can affect the usage of ecommerce recommender system. The authors develop a mood recognition tool to classify online shoppers into stressed or relaxed mood state unobtrusively. By analyzing their reactions to recommended products when surfing on an e-commerce website, the authors make two conclusions. Firstly, stress negatively impacts the usage of recommender system. Secondly, relaxed users are more receptive to recommendations. These findings suggest that mood recognition tool can help recommender systems find the “right time” to intervene. And mood-aware recommender systems can enhance marketer-consumer interaction.

Can e-Commerce Recommender Systems be More Popular with Online Shoppers if they are Mood-aware?