IS Atlas
isr·2023년 2월 28일

When Images Backfire: The Effect of Customer-Generated Images on Product Rating Dynamics

Yue Guan, Yong Tan, Qiang Wei, Guoqing Chen

Information Systems Research

40
피인용
8.8
FWCI
7
IS/마케팅/OM 탑저널 피인용
66
IS/마케팅/OM 탑저널 참고문헌
01Abstract

Customer-generated images (CGIs) are images posted by customers on e-commerce platforms, and they usually appear in the review sections together with review text and ratings provided by customers having purchase experiences. Despite their prevalent adoption by e-commerce platforms, the effect of CGIs on customers’ postpurchase satisfaction remains unclear. We find that CGIs lead to a decline in subsequent ratings compared with product ratings not exposed to CGIs. Furthermore, high CGI review ratings and high aesthetic quality exacerbate the negative effect, whereas reviewers’ face disclosure in CGIs can alleviate the negative effect. Through cross-product analyses, we find that the negative effect is more prominent for experience goods (e.g., women’s dresses) than for search goods (e.g., lightning cables). Results from a laboratory experiment show that participants experience significantly higher expectation and negative disconfirmation when reading CGI reviews with high ratings, whereas the uncertainty reduction effect is insignificant, which collectively explains the decline of subsequent product ratings from a theoretical perspective. These findings suggest that platforms and retailers should be aware of the potential negative effect of CGIs on the rating dynamics and take appropriate measures to circumvent it.

02연구 흐름

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03비슷한 논문

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04이후 연구

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05선행 연구

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06서지 정보