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Title: Can touch interaction predict product-related emotion? a study on mobile augmented reality
Authors: Tarafdar, Pratik
Leung, Alvin Chung Man
Yue, Wei T.
Bose, Indranil
Keywords: Augmented reality
Emotion analytics
Human-computer interaction
Predictive analytics
Issue Date: 2020
Publisher: SCOPUS
26th Americas Conference on Information Systems, AMCIS 2020
Association for Information Systems
Abstract: The advancement in immersive technologies provides online retailers the opportunity to integrate augmented reality (AR) experience for their customers. Using AR, the online product presentation is transformed from the pictorial representation to virtual interaction with the products. The virtual product interaction facilitates online retailers to detect product-related emotion through affective computing. For mobile AR, customers use touch gestures for virtual interaction. Using the theories related to immersive media and affective computing, we hypothesize that the touch movements and touch pressure in AR-based mobile applications are related to positive emotion during product interaction. Moreover, we describe a methodology to establish our hypotheses and to show that these variables can predict the produ ct-related emotion. We expect our research findings to have both theoretical and practical implications. It will explain why touch behavior can predict product-related emotion, and it will also demonstrate online retailers how to implement emotion analytics in AR shopping applications.
Description: Pratik Tarafdar, Indian Institute of Management Calcutta, India; Alvin Chung Man Leung, City University of Hong Kong, Hong Kong; Wei T. Yue, City University of Hong Kong, Hong Kong; Indranil Bose, Indian Institute of Management Calcutta, India
Appears in Collections:Management Information Systems

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