A Deep Learning Approach for Brand Store Image and Positioning

Yoojin Han, Hyunsoo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a deep learning approach to measuring brand store image and generating positioning maps. The rise of signature brand stores can be explained in terms of brand identity. Store design and architecture have been highlighted as effective communicators of brand identity and position but, in terms of spatial environment, have been studied solely using qualitative approaches. This study adopted a deep learning-based image classification model as an alternative methodology for measuring brand image and positioning, which are conventionally considered highly subjective. The results demonstrate that a consistent, coherent, and strong brand identity can be trained and recognized using deep learning technology. A brand positioning map can also be created based on predicted scores derived by deep learning. This paper also suggests wider uses for this approach to branding and architectural design.

Original languageEnglish
Title of host publicationRE
Subtitle of host publicationAnthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
EditorsDominik Holzer, Walaiporn Nakapan, Anastasia Globa, Immanuel Koh
PublisherThe Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
Pages691-698
Number of pages8
ISBN (Electronic)9789887891741
Publication statusPublished - 2020
Event25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 - Bangkok, Thailand
Duration: 2020 Aug 52020 Aug 6

Publication series

NameRE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
Volume2

Conference

Conference25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
Country/TerritoryThailand
CityBangkok
Period20/8/520/8/6

Bibliographical note

Funding Information:
This work was supported by the BK21 Plus funded by the Ministry of Education of Korea.

Publisher Copyright:
© 2020 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Building and Construction

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