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

Katsunobu Sasanuma and Gyung Yeol Yang
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Katsunobu Sasanuma: Department of Management, Nagoya University of Commerce and Business, Japan & Graduate School of Economics and Management, Tohoku University, Japan
Gyung Yeol Yang: Department of Marketing, Nagoya University of Commerce and Business, Japan

International Journal of Technology and Human Interaction (IJTHI), 2024, vol. 20, issue 1, 1-22

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.

Date: 2024
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