Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments | Zendy

Jella Pfeiffer | Zendy; Thies Pfeiffer | Zendy; Martin Meißner | Zendy; Elisa Weiß | Zendy

Open Access

Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments

Author(s) -

Jella Pfeiffer,

Thies Pfeiffer,

Martin Meißner,

Elisa Weiß

Publication year - 2020

Publication title -

information systems research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.507

H-Index - 159

eISSN - 1526-5536

pISSN - 1047-7047

DOI - 10.1287/isre.2019.0907

Subject(s) - computer science , profiling (computer programming) , eye tracking , human–computer interaction , relevance (law) , recommender system , virtual reality , process (computing) , consumer behaviour , world wide web , artificial intelligence , advertising , political science , law , business , operating system

How can we tailor assistance systems, such as recommender systems or decision support systems, to consumers’ individual shopping motives? How can companies unobtrusively identify shopping motives w...

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