How Do Different Types of Merchant Pictures Affect Online Market Performance? Investigating from the Picture Content and Composition Perspective

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review

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Author(s)

  • Zhenbin Yan
  • Uttara Madurai Ananthakrishnan
  • Yingfei Wang
  • Yong Tan

Related Research Unit(s)

Detail(s)

Original languageEnglish
Publication statusPublished - Nov 2020

Conference

TitleINFORMS Conference on Information Systems and Technology (CIST 2020)
LocationVirtual
Period7 - 8 November 2020

Abstract

Pictures are essential website elements in digital platforms. In this paper, we find that online merchants with different types of merchant pictures have heterogeneous performance on sales. Using a brand type picture demonstrates more voucher sales than a product type picture or an environment type picture. We explain the sales variation from the perspective of picture content and picture composition (the arrangement of objects to make it compelling). To account for the effect of picture composition, we construct measures based on figure-ground perception theories. Besides, we discriminate the value of picture content with merchant attributes. Results show that both content and composition can affect merchant sales performance. The impact of composition tends to be the joint effect of all intercorrelated cues rather than independently. The pure effect of brand content can lead to more sales if the merchant belongs to a franchise group, indicating higher brand awareness.

Research Area(s)

  • Merchant Pictures, Picture Content, Picture Composition, Market Performance, Figure-ground Perception

Bibliographic Note

Information for this record is supplemented by the author(s) concerned.

Citation Format(s)

How Do Different Types of Merchant Pictures Affect Online Market Performance? Investigating from the Picture Content and Composition Perspective. / Yan, Zhenbin; Ananthakrishnan, Uttara Madurai; Wang, Yingfei et al.

2020. Paper presented at INFORMS Conference on Information Systems and Technology (CIST 2020).

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review