The effects of social network properties on the acceleration of fashion information on the web

Song, Kieun; Hwang, Sun-Jin; Kim, Yunsik; Kwak, Youngsik

doi:10.1007/s11042-012-1068-2

Cited by 9 publications

(6 citation statements)

References 31 publications

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“…Usefulness refers to the extent to which the content provided by an IS is believed to be helpful and useful to the user's tasks and diversity pertains to the abundance of information in terms of quality and quantity (DeLone and McLean, 2003). Song et al (2013) has revealed that usefulness is the most salient attribute of fashion information on websites. Given that offering diverse information on fashion-related IS can enhance the users' shopping experience (S a et al, 2022), we focused on the factors of INFQ, specifically usefulness and diversity.…”

Section: Information Quality (Infq)mentioning

confidence: 99%

Online VR store as a sustainable fashion retail space

Won,

Jung,

Lee

2024

IJRDM

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PurposeThe study applied the information system success model (ISSM) to investigate the influence of information system qualities (ISQs) on consumer responses related to sustainable fashion consumption in the context of comparing 3D VR store and 2D website.Design/methodology/approachThis study designed a questionnaire to measure five ISQs (usefulness, diversity, functionality, reliability and tangibility), immersion in messages and purchase intention. 270 data from women consumers of online fashion stores were collected using Macromill Embrain. Structural equation modeling with Amos 21 and process macro model 7 with SPSS 26 were used for analysis.FindingsThis study suggested the relevance of usefulness, diversity, reliability and tangibility among ISQs in evoking immersion in sustainable fashion messages and stimulating the purchase intention. In the moderation of website technology types, the effects of usefulness and tangibility on the immersion in sustainable fashion messages were stronger in 3D VR than 2D condition.Originality/valueThe study is meaningful as an initial study that identified the ISQs of online fashion stores by dividing the type of technology into 3D VR and 2D. We offer insights about the relevance and applicability of immersive VR technology in promoting sustainable fashion consumption and show the potential of online VR store as a new kind of sustainable fashion retail space.

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Section: Information Quality (Infq)mentioning

confidence: 99%

Online VR store as a sustainable fashion retail space

Won,

Jung,

Lee

2024

IJRDM

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“…Brands continue to invest in online marketing and consumer engagement via social media, on the other hand online consumers use social media to discuss the brands and their activities (Euromonitor International, 2017a). Currently, fashion labels are constantly discussed in social media leading to massive conversation data that can be extracted for the research (Song, Hwang, Kim, & Kwak, 2013).…”

Section: Apparel Industry and Jeansmentioning

confidence: 99%

More Than Words: an Analysis of Communication on Twitter for an Apparel Heritage Brand

Afroze¹

2022

Preprint

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Advances in technology and society have changed the way people use the Internet. While customers use online platforms for interactions and information exchange, businesses strive to create brand awareness or engagement. This thesis is an exploratory study to understand online communication of a heritage brand by analyzing its Twitter brand community. Using grounded theory approach, Dann’s classification (2010) was used on branded and non-branded tweets to identify the types of messages that dominated the online community. Driven by the findings, types of users for non-branded communication was analyzed to expand understanding. The results suggest that engagement should be modified in accordance to the type of user for whom the message is addressed. The findings present new insights for marketers who are willing to explore the full potential of online communication. The study highlights the importance of online brand communities while expanding the understanding of Twitter communication through Dann’s classification.

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“…A fashion knockoff network was visualized to understand knockoff victims and offenders. Song, Hwang, Kim, and Kwak (2013) investigated the acceptance of word-of-mouth information between consumers in the Internet fashion community. SNA helped reveal the features of the network and its spread of patterns involving fashion information shared between community members.…”

Section: Literature Reviewmentioning

confidence: 99%

The Rise of Fashion Informatics: A Case of Data-Mining-Based Social Network Analysis in Fashion

Zhao

Min

2018

Clothing and Textiles Research Journal

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With the advent of modern cognitive computing technologies, fashion informatics researchers contribute to the academic and professional discussion about how a large-scale data set is able to reshape the fashion industry. Data-mining-based social network analysis is a promising area of fashion informatics to investigate relations and information flow among fashion units. By adopting this pragmatic approach, we provide dynamic network visualizations of the case of Paris Fashion Week. Three time periods were researched to monitor the formulation and mobilization of social media users' discussions of the event. Initial textual data on social media were crawled, converted, calculated, and visualized by Python and Gephi. The most influential nodes (hashtags) that function as junctions and the distinct hashtag communities were identified and represented visually as graphs. The relations between the contextual clusters and the role of junctions in linking these clusters were investigated and interpreted.

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The effects of social network properties on the acceleration of fashion information on the web

Cited by 9 publications

References 31 publications

Online VR store as a sustainable fashion retail space

Online VR store as a sustainable fashion retail space

More Than Words: an Analysis of Communication on Twitter for an Apparel Heritage Brand

The Rise of Fashion Informatics: A Case of Data-Mining-Based Social Network Analysis in Fashion

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