The adoption of digital fashion as an end product: A systematic literature review of research foci and future research agenda

Figures & data

Table 1. Summary of 6W framework (Adapted from Callahan, 2014; Xie et al., 2017).

6W Framework
Who	Who conducted the research for “data”	Research team named on paper.
		To ensure consistency majority of data collection conducted by lead-author.
		Research conducted across 5 databases
When	When were the data collected	Review conducted over 6 month period from August 2022 to January 2023
Where	Where were the data collected	Across 5 databases (Google Scholar, Emerald, Scops, SAGE Journals, and ScienceDirect).
		Further searches were conducted in database of major marketing and fashion conferences (Association for Consumer Research, the International Foundation of Fashion Technology Institutes, and the Global Marketing Conference).
How	How were the data found	Inclusion and exclusion criteria as well as search strategies followed in line with existing reviews (e.g. Athwal et al., 2019; Baek et al., 2022; Noris et al., 2020) defining a clear keyword search string.
		Inclusion and exclusion criteria were carefully designed and in line with past research.
What	What did you keep and what did you discard	Due to the interest of different fields in the topic of “digital fashion” the focus was on a marketing/management perspective, which allowed us to narrow down the scope.
Why	Final selection criteria	The final article selection went through multiple cycles that all researchers involved performed a traffic light system review (red=not applicable, amber=matches some of the inclusion criteria; green=matches all inclusion criteria).
		Any discrepancies were carefully discussed.

Figure 2. The distribution of the publication per year (Source: Author’s elaboration).

Figure 1. Structured keywords (Source: Author’s elaboration).

Figure 3. The methodology of the publication (Source: Author’s elaboration).

Figure 4. The result of thematic analysis (Source: Author’s elaboration).

Table 2. Identified research areas based on TCCM framework (Source: Author’s elaboration based on TCCM framework from Paul & Rosado-Serrano, 2019).

TCCM Framework components	Codes	Descriptions	Indicative articles
Theory (T)	Concept	Include papers that discuss the key concepts and theoretical foundations related to digital fashion	Baek et al. (2022), Lee and Xu (2019), Noris et al. (2020), and Nobile et al. (2021).
Context (C)	Consumer	Include papers that discuss the contextual factors of consumer that influence the development and adoption of digital fashion as an end product, including the customer perception and behavioural responses to digital fashion as end products.	Baytar and Ashdown (2015), Beck and Crié (2018), Cho and Schwarz (2012), D. E. Kim (2016), J. Kim and Forsythe (2008), D. E. Kim and LaBat (2012), Miell et al. (2018), Moroz (2019), Nam et al. (2016), Noordin et al. (2018), Pantano et al. (2017), Perry (2016), Plotkina and Saurel (2019), Porterfield and Lamar (2017), Qasem (2021), Ross and Harrison (2016), Shin and Baytar (2014), Yu and Damhorst (2015), Zhang et al. (2017), and Yim and Park (2019).
	Industry	Include papers that discuss contextual factors of industry that influence the development and adoption of digital fashion as an end product, including the drivers and challenges of adoption	Park and DeLong (2009), Papahristou and Bilalis (2017), McQuillan (2020), Hwang Shin and Lee (2020), and Sarmarkari (2021).
Characteristics (C)	Concept	Include papers that discuss different types of digital fashion end products, their features and properties.	McQuillan (2020), Papahristou and Bilalis (2017), Park and DeLong (2009), Särmäkari (2021), and Hwang Shin and Lee (2020).
Methodology (M)	No code, discussed in section 3.1.3	Include all papers’ research methodology and methods used to investigate digital fashion.	All articles

Figure 5. Definition of digital fashion in the 3D virtual technologies field (Source: Author’s elaboration).

Table 3. Characteristics of the six forms of digital fashion end products (Source: Author’s elaboration).

Types	Description	Purchase Process	Interface	Purpose	Price Range	Industry Examples	Image References
Digital Skin for Gamified Environment	Digital fashion companies create skins that are either virtual only skin or an identical virtual replica of an actual fashion item for gamers to purchase (FashionUnited, 2022b).	Vary from spending actual money to virtual money on the game server or completing gamified tasks to gain digital fashion (FashionUnited, 2022b).	Avatar body	Use in gamified environment	Free - £10k+	Louis Vuitton designed skins for League of Legends (Fashion united, 2022b)	Skin designed in collaboration with Louis Vuitton. Source: Riot Games (FashionUnited, 2022b)
Digital Skin for virtual Influencers	Digital skin is designed for computer-generated social media influencers. They worked with fashion businesses by wearing their digital fashion skins and posting on social media. Some retailers also designed their own virtual influencers for marketing purpose (Vogue, 2021, 2022).	Virtual influencers seldom buy digital fashion; instead, businesses partner with them to build a skin for social media.	Avatar body	Social media content creation/advertisements	N/A	Virtual influencer Miquela is partnering with teen retailer Pacsun (Vogue Business, 2022).	Courtesy of Miquela (Vogue Business, 2022)
Superimposed Image Based	This type of digital fashion is mainly for social media, it is usually sold as a video or photo with virtual fashion products superimposed on the consumer’s photographed body for social media content creation (Forbes, 2020a; Kiplinger, 2022; Särmäkari, 2021)	Consumers may pick the digital fashion they wish to “wear”. After buying the item, customers will submit a picture of themselves and get a photo with the digital clothing on them (Forbes, 2020a; Kiplinger, 2022; Särmäkari, 2021).	Human photographed body	Social media content creation	£2-£200	Carling’s Neo Ex collection;The fabricant’s digital fashion collection. Forbes (2020a), Kiplinger (2022) and Särmäkari (2021)	Fido Pants by Tribute Brand. Photograph: Tribute Brand (The Guardian, 2021)
AR-filter Based	AR-based digital fashion is typically accessible for customers to purchase They can capture images or videos to post on social media. (Dezeen, 2021). AR-based digital fashion is also utilised for virtual try-ons.	Consumers simply download a specific AR app for AR filter-based digital fashion, purchase the digital fashion filter, then apply it to the in-app camera to create images or videos. (Dezeen, 2021).	Human photographed body	Social media content creation	Free-£20	Gucci’s virtual sneaker (The Guardian, 2021), DressX AR wardrobe (DressX, 2022), Bershka x DressX digital fashion collection (FashionUnited, 2022a)	Bershka x DressX digital fashion collection, Going Out. Image: Bershka (FashionUnited, 2022a)
Fashion NFTs	Fashion Non-Fungible-Tokens (NFTs) are limited collectibles that may be resold. Some comprise the digital file of a digital fashion that can be worn in the metaverse. Fashion NFT may be included in a digital artwork, worn or not worn by a human or avatar in a picture or video (Vogue, 2021)	On blockchain platforms, buyers swap their money for crypto currency and then acquire the NFT from an existing owner or on a fashion NFT retailer’s mint day (launch day). Coinbase (2022)	Avatar/Human photographed body	Collectibles/Digital skin for gamified environment	Free - £370000+	World’s first digital only Haute-Couture dress Iridescence (Forbe, 2020a; Sarmakari, 2021); The Impossible Tiara”,from Dolce & Gabbana (The New York Times, 2021; UNXD, 2021)	The Impossible Tiara, a digital creation, was built by UNXD, based on Dolce & Gabbana sketches (The New York Times, 2021).
Digital Twins	Digital twins are duplicates of genuine clothing that customers receive in addition. Some digital twins are NFTs and may be used in metaverse or gamified scenarios. (Vogue Business, 2022a; Vogue Business, 2022b)	The digital twin is normally included with the physical garment/digital twin combo, however vendors vary. (Vogue Business, 2022b). Metaverse digital counterpart can be purchased in metaverse and transported to the buyer’s house (Vogue business, 2022c)	Avatar	Collectibles/Digital skin for gamified environment	Free - £370000+	Nike’s Crypto kicks digital twin sneakers; Gucci’s bags in Roblox metaverse (Vogue business, 2022c), Burberry Launches Exclusive Virtual Handbag Collection On Roblox (Elle, 2022)	Courtesy of Buberry (2022)

Table 4. Characteristics of the six forms of digital fashion end products (Source: Author’s elaboration).

Authors	Model Used	Variables
J. Kim and Forsythe (2008)	TAM	Technology anxiety; Innovativeness; Ease of use; Usefulness; Atitude; Behavioural intention
Perry (2016)	TAM	Social influence variable (Subjective norm); Personality trait (Technology optimism); Product feature (Aesthetics); Ease of use; Usefulness; Atitude; Behavioural intention
Ross and Harrison (2016)	TAM	Design features; Perceived usefulness; Peived ease of use; Atitude toward me; Actual system use
Pantano et al. (2017)	TAM	Quality of information; Aesthetic quality; Interactivity; Response time; Ease of use; Usefulness; Attitude; Behavioural intention
Plotkina and Saurel (2019)	TAM	Perceived hedonic value (Enjoyment); Utilitarian value (Convenience, Ease of use; Usefulness); Attitude and Behavioural intention

Table 5. Future research agenda (Source: Author’s elaboration based on TCCM framework from Paul & Rosado-Serrano, 2019).

TCCM Framework Components	Research Area	Research Questions	Research Agenda
Theory (T)	Definition of digital fashion	How effective is the proposed framework in defining and categorizing different aspects of digital fashion?	Explore the effectiveness of the proposed framework (Figure 5) in defining and categorizing digital fashion
		Do the definition of digital fashion align with the industry-accepted definition?	Further refined the framework by incorporating feedback from industry experts, designers, and consumers.
Context (C)	Consumer acceptance	What are the consumer acceptance towards digital fashion as end products?	Examine the consumer acceptance of digital fashion as end products by applying TAM adoption based variables: Perceived enjoyment, Perceived usefulness and Perceived ease of use.
		How does the body fitting realism levels of digital fashion end products affect consumer acceptance towards it	Investigate the relationship between the level of body fitting realism in digital fashion end products and consumer acceptance towards it.
		To what extend the consumer body satisfaction affect the consumer acceptance of digital fashion as end products	Examine the effect of the consumer body satisfaction on their acceptance of digital fashion as end product
	Industry acceptance	What are the fashion industry perceptions towards implementing digital fashion end products as a new product category?	Investigate the industry acceptance of digital fashion as end product as a new product category.
		Investigate the industry acceptance of digital fashion as end product as a new product category. How can digital fashion end product be integrated into the broader fashion industry, and what are the implications for traditional manufacturing and retail models?	Examine what digital fashion implies to traditional fashion industry by identifying potential challenges and opportunities that may arise from the integration of digital fashion into production, distribution, and sales of the traditional fashion industry.
Characteristics (C)	Characteristics of the Six forms of digital fashion end products	What are the consumer perceptions towards superimposed image based and AR filter based digital fashion that are mainly for social media content creation?	Identify the factors that influence consumers’ acceptance and adoption of superimposed image based and AR filter based digital fashion in social media content creation.
Methodology (M)	Research Methodology	What are the recommended research methodology and research methods for studying digital fashion as end product?	Qualitative research is recommended at this stage to explore digital fashion as end products to ground the theory for future quantitative research, such as in-depth interview, focus group, case studies, participant observation and content analysis.

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