Fast fashion brand extensions: An empirical study of consumer preferences

2010 ◽  
Vol 17 (7) ◽  
pp. 472-487 ◽  
Author(s):  
Tsan-Ming Choi ◽  
Na Liu ◽  
Shuk-Ching Liu ◽  
Joseph Mak ◽  
Yeuk-Ting To
Keyword(s):  
Empirical Study ◽  
Consumer Preferences ◽  
Brand Extensions ◽  
Fast Fashion ◽  
Fashion Brand

scholarly journals A Social Media Mining and Ensemble Learning Model: Application to Luxury and Fast Fashion Brands

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 149
Author(s):  
Yulin Chen
Keyword(s):  
Public Participation ◽  
Brand Positioning ◽  
Image Model ◽  
Web Crawler ◽  
Fast Fashion ◽  
Social Media Mining ◽  
Fashion Brand ◽  
Community Information ◽  
Brand Information ◽  
Media Mining

This research proposes a framework for the fashion brand community to explore public participation behaviors triggered by brand information and to understand the importance of key image cues and brand positioning. In addition, it reviews different participation responses (likes, comments, and shares) to build systematic image and theme modules that detail planning requirements for community information. The sample includes luxury fashion brands (Chanel, Hermès, and Louis Vuitton) and fast fashion brands (Adidas, Nike, and Zara). Using a web crawler, a total of 21,670 posts made from 2011 to 2019 are obtained. A fashion brand image model is constructed to determine key image cues in posts by each brand. Drawing on the findings of the ensemble analysis, this research divides cues used by the six major fashion brands into two modules, image cue module and image and theme cue module, to understand participation responses in the form of likes, comments, and shares. The results of the systematic image and theme module serve as a critical reference for admins exploring the characteristics of public participation for each brand and the main factors motivating public participation.

Benefit appeals and perceived corporate hypocrisy: implications for the CSR performance of fast fashion brands

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaoyong Wei ◽  
Sojin Jung
Keyword(s):  
Online Survey ◽  
Interactive Effect ◽  
Critical Role ◽  
Experimental Manipulation ◽  
Chinese Consumers ◽  
Significant Interaction Effect ◽  
Fast Fashion ◽  
Content Type ◽  
Fashion Brand ◽  
Corporate Social

Purpose When fast fashion brands launch corporate social responsibility (CSR) programs, consumers may consider these brands to behave hypocritically as their business model is generally perceived as being inconsistent with sustainable practices. Built on construal level theory (CLT), this study aims to examine how the benefit appeals that are widely used in CSR initiatives affect perceived corporate hypocrisy and the CSR performance of fast fashion brands. Design/methodology/approach This study designed an online experiment with a 2 (fashion brand: fast fashion vs. unknown) × 2 (benefit appeal: self-benefit vs other-benefit) stimulus, using a virtual label named “Eco Care” for experimental manipulation. A total number of 298 Chinese consumers participated in the experiment and they answered an online survey. Findings It was found that the brand types (fast fashion vs unknown) and benefit appeals (self-benefit vs other benefit) did not elicit perceived corporate hypocrisy nor did them directly affect perceptions of CSR performance. However, there was a significant interaction effect of them. That is, fast fashion brand’s CSR performance was judged based on how the brand framed its sustainability claims. A fast fashion brand’s CSR label significantly increased hypocrisy perceptions when the label used a self-benefit appeal and the interactive effect of the fast fashion brand and the self-benefit appeal hindered the formation of a green brand image and brand purchase intentions. Originality/value This study adds a body of knowledge to the literature by examining the relationship between benefit appeals and perceived corporate hypocrisy from the perspective of CLT. The findings can help fast fashion marketers better understand the critical role of benefit appeals by acknowledging that the misuse of communication strategies may result in unfavorable consequences, thus ruining their efforts to improve their brand’s image.

scholarly journals Which Consumer Associations Can Build a Sustainable Fashion Brand Image? Evidence from Fast Fashion Brands

2020 ◽  
Vol 12 (5) ◽  
pp. 1703 ◽  
Author(s):  
Yunjeong Kim ◽  
Kyung Wha Oh
Keyword(s):  
Network Analysis ◽  
Brand Image ◽  
Brand Associations ◽  
Fast Fashion ◽  
Female Consumers ◽  
Fashion Brand ◽  
Depth Analysis ◽  
Sustainable Fashion ◽  
Depth Interviews

Since fast fashion is often considered the opposite of sustainable fashion, this study was conducted to clarify the consumer brand associations with sustainable fashion by analyzing three fast fashion brands. Our research included two studies. First, we conducted in-depth interviews with 20 female consumers in Korea who had purchase experience with the sustainable fashion of three selected brands, H&M, Zara, and Uniqlo, to identify sustainable keyword associations. We then structured the keyword data using network analysis. The keyword associations for the three brands resulted in a network of 60 nodes and 629 links with the term “eco-friendly” as the most meaningful keyword. Second, we surveyed 200 women and quantitatively confirmed the association of “eco-friendly fabric” among the keywords suggestive of “eco-friendly” as the most important factor in building a sustainable fashion brand image. In addition, keywords, such as “marketing” and “campaign”, were ranked in the top ten in H&M and Zara, which may imply the opportunistic use of greenwash. This study contributes to the literature by applying in-depth analysis of consumer associations of fast fashion brands from a sustainability perspective through network analysis. We expect our findings to help fashion companies strategically build a sustainable fashion brand image.

A demand forecasting model based on the improved Bass model for fast fashion clothing

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaoxi Zhou ◽  
Jianfei Meng ◽  
Guosheng Wang ◽  
Qin Xiaoxuan
Keyword(s):  
Historical Data ◽  
Consumer Preferences ◽  
Demand Forecasting ◽  
Impact Factors ◽  
Bass Model ◽  
Demand Forecast ◽  
Fast Fashion ◽  
Content Type ◽  
Sales Data ◽  
Demand Forecasting Model

PurposeThis paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.Design/methodology/approachFrom the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.FindingsThe objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.Originality/valueThe paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

scholarly journals Cultivating the brand-customer relationship in Facebook fan pages

2017 ◽  
Vol 45 (3) ◽  
pp. 253-270 ◽  
Author(s):  
Shing-Wan Chang ◽  
Shih-Heng Fan
Keyword(s):  
Social Networking Sites ◽  
Structural Equation ◽  
Quantitative Research ◽  
Affective Commitment ◽  
Asian Country ◽  
Customer Relationship ◽  
Continuance Intention ◽  
Fast Fashion ◽  
Content Type ◽  
Fashion Brand

Purpose The purpose of this paper is to examine the determinants of continuous brand-customer relationship via company-hosted social networking sites (SNSs). Factors that influence fans to continue using fast-fashion brands’ Facebook fan pages and to maintain the brand-customer relationship are discussed first. Subsequently, the predictors of fans’ engagement and affective commitment to a fast-fashion brand are examined with the aim to explore the key elements that nurture the brand-customer relationship via brands’ SNSs. Design/methodology/approach A quantitative research was conducted and the structural equation modelling was used to test the hypotheses on a sample of 202 fast-fashion Facebook fan page users in Taiwan. Findings The results demonstrate that engagement, affective commitment and continued intention to use are predominantly influenced by, in turn, social interaction tie, content value and affective commitment. Research limitations/implications The study is limited because it investigated the fast-fashion fan page users in an Asian country, so the findings cannot be generalised to other contexts. Practical implications The findings suggest that fan page managers’ initiation and involvement in conversations, frequent responses, listening to fans’ opinions and improving fans’ experiential value may facilitate them to engage in the brand’s activities at a higher level. Originality/value The findings of this integrated model suggest managerial guidelines for brand managers in this industry regarding how to maintain the brand-customer relationship through social media strategy and how they contribute to theory building in continuance intention of SNSs.

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