Dataset - Enhancing Brick-and-Mortar Shopping Experience Through Explainable Artificial Intelligence in a Smartphone-based Augmented Reality Shopping Assistant Application

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Dataset information

Country of origin
Updated
2021.04.28 00:00
Created
2021.04.27
Available languages
English
Keywords
Digital Shopping Assistant, Recommender Systems, Explainable Artificial Intelligence, Retail Sales, Digital Retail, Data
Quality scoring

Dataset description

This is a dataset obtained from an online survey conducted in August 2020.  In the survey, participants were introduced to the concept of a smartphone-based shopping assistant application with the help of pictures and videos when shopping with and without the application. Participants were presented with three different shopping scenarios. In each scenario, we showed products on a shelf (groceries, luxury chocolate, shoes, books). The first shopping scenario was a regular shopping scenario (RSS), the second was an augmented reality shopping scenario (ARSS), and the third was an augmented reality shopping scenario with explainable AI features (XARSS). For each scenario participants had to answer questions about how they perceived the scenario and how it influenced their overall purchase intention. The present work was conducted within the Innovative Training Network project PERFORM funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765395. The EU Research Executive Agency is not responsible for any use that may be made of the information it contains.      
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32
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2019
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