Enhancing Apparel Size and Fit Prediction for E-Commerce: A Mixed Methods Approach with 3D Body Scanning

Abstract

The study aims to introduce web 3.0 technology features such as virtual fitting room tools in Pakistani fashion e-commerce platforms to introduce virtual mass customisation business using the unstitched fabric category of Pakistan. The study contributed to creating a sustainable virtual commerce business model that enhances the assessment of garment fit, size and style in a virtual environment similar to consumers' experience in the natural in-store environment. To present the business model, the study follows the framework proposed by Lemon and Verhoef (2016) to study the consumer shopping journey in three stages: pre-purchase, purchase, and post-purchase. The main idea of the study is to explore the virtual fitting room and 3D body scanning tools, to understand how these tools can be used in virtual commerce to deliver the right fitted garment and how mass customisation can be introduced Fashion e-commerce platforms. The unsatisfied consumers are kept in mind due to poor fitting of garments constructed with the standard sizing systems used for mass production. In addition, munual tape measurement method is established as time consuming method with a requirement of having a landmarking professional knowledge in the extraction of body dimensions. Therefore, this research is divided into three studies to explore virtual fitting room tools. Study 1 investigates the responses of 357 Pakistani and British Pakistani females aged 18-65+ to virtual size and fitting interfaces (Fit analytics (size recommendation) and virtual outfits (size and fit recommendation and visualisation)). Study 2 explores the booth 3D body scanner Size Stream SS20 and MeThreeSixty mobile applications. Both are products of the same company, Size Stream. Both 3D body scanners and body dimensions have been comparatively analysed to determine the reliability and validity of mobile app scanners for incorporation in the virtual fitting room tools of fashion e-commerce interfaces. Twenty female participants of different ethnic groups aged 18-65+ were recruited for scanning at the University of Manchester. Study 3 (mixed-methods) explores the three 3D mobile application scanners (3Dlook, Size Stream at home, and Nettelo) to investigate the consumer responses to the bespoke garments constructed using the digital measurements acquired from the mobile app scanners. Ten female Pakistani participants were recruited to conduct the study. Initially (Stage 3) mobile applications body dimensions were comparatively analysed. In second stage, participants responses were calculated using the TAM theoratical framework. In Stage 3, each participant was interviewed three times after evaluating the three bespoke garments constructed from the three mobile applications acquired body dimensions. Recent researchers have studied virtual fitting rooms and established them as the future tools of virtual marketing and virtual size and fitting assessments for apparel shopping (Sajib et al., 2018; De Silva et al., 2019; Tawira and Ivanov, 2022). Moreover, recent studies have comparatively analysed the booth and mobile scanners and determined that 3D body scanners can be used for personalised garment development and selection in virtual platforms (Smith et al., 2021; Thi Nguyen et al., 2022). By evaluating the existing platforms, the study provides the notion of using the strengths of virtual fitting room tools such as virtual trying-on to acquire the rich information of the product in 3D simulation and 3D body scanning to be used as a central tool that can serve the purpose of garment production and selection. Further, an extensive literature review is presented on the unstitched apparel product used in Pakistan, used explicitly for bespoke garment construction. To evaluate the existing virtual size and fitting interfaces, the study adopts the Technology Acceptance Model (TAM) by Davis (1989). The consumers' evaluations of the pre-purchase stage have been studied using the size and fit recom

Date of Award	31 Dec 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Gianpaolo Vignali (Supervisor) & Simeon Gill (Supervisor)