Abstract
Purpose: This study aims to investigate the impact of experience product portal page aesthetics on bounce rate. Design/methodology/approach: This research collected data from an online shop selling original design furniture on Taobao.com. It employed deep learning algorithm and manual coding to operationalize image and text aesthetics. Findings: The empirical results indicate that text aesthetics has a U-shaped relationship with bounce rate, whereas the relationship between image aesthetics and bounce rate is insignificant. Moreover, the U-shaped relationship between text aesthetics and bounce rate is weakened by image aesthetics. Originality/value: This study addresses an important but understudied topic – the bounce rate of experience products in the context of e-commerce. Although the high bounce rate has increasingly gained attention from practitioners, there remains a scarcity of research that addresses the effect of product portal page aesthetics in the specific context of experience products. The authors theorize product portal page aesthetics as the design elements of an e-commerce website and deeply analyzed the role of product portal page aesthetics by classifying it into text aesthetics and image aesthetics. The authors’ findings provide implications for online sellers and platforms to effectively design product profile pages to reduce the bounce rate.
Original language | English |
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Pages (from-to) | 1848-1870 |
Number of pages | 23 |
Journal | Industrial Management and Data Systems |
Volume | 121 |
Issue number | 8 |
DOIs | |
Publication status | Published - 10 Aug 2021 |
Keywords
- Deep learning
- Experience products
- Product portal page aesthetics
- Signaling theory
ASJC Scopus subject areas
- Management Information Systems
- Industrial relations
- Computer Science Applications
- Strategy and Management
- Industrial and Manufacturing Engineering