Personalizing 3D virtual fashion stores: Exploring modularity with a typology of atmospherics based on user input

Juanjuan Wu, Sanga Song, Claire Haesung Whang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

This research develops a typology of atmospherics that contains user-identified modules and modular options for personalizing 3D virtual fashion stores. A content analysis of 46 focus group discussions (n = 170) was conducted to understand the user's perspective for personalizing 3D virtual fashion store atmospherics. Based on three atmospheric categories (pathfinding assistant, environment, and the manner of product presentation), 17 modules and 207 modular options were identified for personalizing 3D virtual stores. This research pioneers the development of an atmospherics typology for personalizing 3D virtual shopping environments as a persuasive selling tool in the emerging field of 3D virtual reality (VR) retailing.

Original languageEnglish (US)
Article number103461
JournalInformation and Management
Volume58
Issue number4
DOIs
StatePublished - Jun 2021

Bibliographical note

Funding Information:
This research was supported by the USDA National Institute of Food and Agriculture [Project No. MIN-53-035].

Publisher Copyright:
© 2021

Keywords

  • 3D virtual stores
  • Atmospherics
  • Personalization

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