Virtual Fit Interfaces - NVivo 12 Codebook

Published: 18 Jul 2019 | Version 1 | DOI: 10.17632/63zv6r42nm.1

Description of this data

We collected 79 screenshots exploring the customer journeys through the different VFIs; nine journey steps per platform on average. To make sure reliability, we used a standardised, set of body measurements while exploring options for each Virtual Fit platform; uncovering size and fit recommendations.

For this paper, the standardised body is an Alvanon™ body form .
Dress Form size code UMR-WMSK12H-1504, dress form code AVF58535.

To make sure the body form’s measurements are correct, we scanned the body form using a size stream 3D Body Scanner (SizeStream, 2017); a technology shown to be reliable for scientific research (Parker et al., 2017).

Experiment data files

Steps to reproduce

To address Objective 1 (understanding the information required from consumers by VFIs) content analysis focused on the consumer’s self-reported assessment on body dimensions; providing key measurements and circumferences used by VFIs to establish size recommendations. Coding focuses on how VFIs collect garment data. Virtual fit references extensive database of branded products, using the specific details of the garment dimensions governed by its style.

To address Objective 2 (understanding the outputs as presented by VFIs) content analysis focuses on how platforms present size and fit recommendations to the customer. This provides a variety of ways to engage with the consumer during the online shopping experience with the different interfaces requiring differing levels of detail to offer the size prediction.

To address Objective 3 (testing how VFIs determine size and fit recommendations) content analysis focuses on Gill’s classification models (2015a). This basic framework provides a tool for interpretation and contextualisation of different ways the consumer positions themselves in the garment selection process.

Latest version

  • Version 1


    Published: 2019-07-18

    DOI: 10.17632/63zv6r42nm.1

    Cite this dataset

    Januszkiewicz, Monika; Parker, Chris; Hayes, Steven; Gill, Simeon (2019), “Virtual Fit Interfaces - NVivo 12 Codebook”, Mendeley Data, v1


Views: 23
Downloads: 3


The University of Manchester, Loughborough University


e-Commerce Retail, Fashion Industry


CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?
You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.