Evaluating the Effectiveness of Recommendation Engines on Customer Experience Across Product Categories

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Author(s): Katsunobu Sasanuma (Nagoya University of Commerce and Business, Japan)and Gyung Yeol Yang (Nagoya University of Commerce and Business, Japan)
Copyright: 2024
Volume: 20
Issue: 1
Pages: 22
Source title: International Journal of Technology and Human Interaction (IJTHI)
Editor(s)-in-Chief: Anabela Mesquita (ISCAP/IPP and Algoritmi Centre, University of Minho, Portugal)and Chia-Wen Tsai (Ming Chuan University, Taiwan)
DOI: 10.4018/IJTHI.345928

Keywords: Human Aspects of Technology / Information Science Reference / Social Sciences & Humanities

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Abstract

Artificial intelligence (AI)-powered tools such as recommendation engines are widely used in online marketing and e-commerce; however, online retailers often deploy these tools without understanding which human factors play a role in which products and at which stage of the customer journey. Understanding the interaction between AI-powered tools and humans can help practitioners create more effective online marketing platforms and improve human interaction with e-commerce tools. This paper examines customers' reliance on recommendation engines when purchasing fashion goods, electronics, and media content such as video and music. This paper also discusses the potential for improvement in recommendation engines in online marketing and e-commerce.

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Evaluating the Effectiveness of Recommendation Engines on Customer Experience Across Product Categories

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