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On product exposure and clicks: gender differences in using product cues

Guang Meng Ji et al.

Electronic Commerce Research2026https://doi.org/10.1007/s10660-025-10082-4article
AJG 2ABDC A
Weight
0.50

Abstract

In a competitive e-commerce environment, where product cues shape consumer decisions, understanding gender differences in response to these cues offers important insights for improving marketing effectiveness. Considering gender differences is potentially important, as men and women may differ systematically in their attention to specific product information, influencing how effectively product cues drive search and selection behaviors. Drawing on 800 real transaction records from TikTok Shop, this study investigates how product cues in titles (i.e., category, brand, sensory attribute, and experiential attribute) influence product exposure, how cues in cover images (i.e., brand, attribute, and facial) affect click behavior, and whether gender differences moderate the use of these cues in product search and selection. Results show that category, brand, and experiential attribute cues in titles significantly boost exposure, with brand and experiential attribute cues more effective among female consumers. Similarly, brand, attribute, and facial cues in cover images increase clicks, with women responding more strongly to brand and facial cues. These findings offer practical insights for retailers seeking to optimize product presentation based on gender-specific preferences.

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https://doi.org/https://doi.org/10.1007/s10660-025-10082-4

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@article{guang2026,
  title        = {{On product exposure and clicks: gender differences in using product cues}},
  author       = {Guang Meng Ji et al.},
  journal      = {Electronic Commerce Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10660-025-10082-4},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.