Paper ID
2789
Paper Type
full
Description
Drawing on a well-accepted classification of brand experience, this study attempts to unravel how service vendors could harness images to profile their service experience and in turn, differentiate themselves from competitors. Specifically, we advance four distinct visual cues as focal disseminators of brand experience consumers would come to expect during service consumption. We then employ deep learning techniques to extract these experience-related stimuli from the portal images of over 282,000 service offerings from a leading service e-tailing platform by training various deep residual networks on a variety of annotated image datasets. We further explore the impact of the derived image features in amassing market share through multinomial logit market-share modeling. By attesting to the power of visual cues in branding service experience, this study not only adds to contemporary knowledge on the criticality of communicating service experience, but it also yields actionable prescriptions for achieving service branding online.
Recommended Citation
Li, Yijing; Lim, Eric; Liu, Hefu; and Liu, Yong, "Seizing Your Market Share: Deciphering the Role of Visual Branding with Deep Residual Networks" (2019). ICIS 2019 Proceedings. 9.
https://aisel.aisnet.org/icis2019/human_computer_interact/human_computer_interact/9
Seizing Your Market Share: Deciphering the Role of Visual Branding with Deep Residual Networks
Drawing on a well-accepted classification of brand experience, this study attempts to unravel how service vendors could harness images to profile their service experience and in turn, differentiate themselves from competitors. Specifically, we advance four distinct visual cues as focal disseminators of brand experience consumers would come to expect during service consumption. We then employ deep learning techniques to extract these experience-related stimuli from the portal images of over 282,000 service offerings from a leading service e-tailing platform by training various deep residual networks on a variety of annotated image datasets. We further explore the impact of the derived image features in amassing market share through multinomial logit market-share modeling. By attesting to the power of visual cues in branding service experience, this study not only adds to contemporary knowledge on the criticality of communicating service experience, but it also yields actionable prescriptions for achieving service branding online.