Fashion Retail Research Articles

Disrupting the fashion retail journey: social media and GenZ's fashion consumption

PurposeThe aim of this paper is to assess the use of social media by Gen Z consumers and the ways they impact on and re-shape their fashion consumption journey. This generational approach uses the lens of uses and gratifications theory (UGT) to explore the customer fashion retail journey from the perspective of the Gen Z consumer.Design/methodology/approachThe research uses an exploratory approach in response to the relative lack of research in to GenZ consumers combined with a need to understand shopping journeys. Mixed methods were used with a first phase of interviews followed by a survey of 102 Gen Z students recruited online in the UK during the COVID-19 pandemic.FindingsThe study found that GenZ users of social media for shopping sought gratification from experiences derived from social relationships, entertainment and information. The need for immediate gratification was found in new information and meeting new people to maintain social relationships, learn about products and inform the shopping journey. Further, the research supported the importance of visual images in the affective gratification of shopping needs. Resale sites on social media were favoured for their low prices, information about previously owned fashion items and the opportunity to exercise sustainable fashion choices.Originality/valueThe research advances understanding of fashion shopping journeys through social media and online resale sites. It demonstrates that younger consumers, GenZ, shop through the gratification of experiences informed by their social networks and wider contacts. The linear stages of pre to post–purchase shopping are merged and looped as they exchange information about their shopping journey, from information gathering to post–purchase comments. The role of the brand to these knowledgeable consumers conducting their own resale trade is to facilitate access to and information about their products.

SWOT Analysis of Shein’s Marketing Strategy

Shein, a Chinese online retailer brand, ​​grew tremendously during the COVID-19 pandemic and becomes a phenomenal company. The company experienced rapid acceleration during the pandemic, reaching a peak in 2021. The paper examines the marketing aspects of Shein's success as an emerging online fashion retailer. Using the SWOT analysis method and incorporating evidence from media press and research, this paper studies the strength side of the company such as its affordable price, segmenting the right target market and successful marketing strategy, its weaknesses in terms of its delivery services, market opportunities created by the COVID-19 pandemic, as well as threats within the fast-fashion industry due to the fierce competitions and the company’s poor performance on ESG. The paper offers recommendations for increasing the transparency of the supply chain and workforce, establishing a sustainability plan, developing a premium version of the brand, and a shift in Shein's public image with Shein's desire to go public in 2022.

A Configurational Approach to Investigating the Relationship Between Organizational Culture and Organizational Effectiveness Using Fuzzy-Set Analysis

The theoretical literature on organizational culture strongly emphasizes the multifacetedness of the construct. Nevertheless, empirical research has tended to focus on independent culture dimensions rather than applying a holistic perspective that conceives organizational culture as a complex collective. We addressed this issue by investigating configurations of organizational culture using fuzzy set qualitative comparative analysis (fsQCA) within organizational units of two organizations. Across the two samples (1170 employees in 89 work units of a financial service provider and 998 employees in 49 work units of a fashion retailer), results indicated that culture dimensions do not operate in isolation, but jointly work together in achieving different effectiveness outcomes. The results further suggested that several cultural configurations can be equally effective in reaching the same outcome, and that a clan culture is most relevant for achieving low employee turnover, while a market-oriented culture is most relevant for achieving financial effectiveness. With respect to more specific configurations of cultural elements, the results showed some congruencies, but were mixed overall. The discussion focuses on theoretical implications and future directions for applying configurational, set-theoretic approaches to analyzing organizational culture.

The Fast Fashion Industry: Formulating the Future of Environmental Change

This Note focuses on the harmful environmental impacts the fast fashion industry has created, and continues to create, on our planet. In the 1960s, consumer attitude towards clothing shifted drastically when demand for new, disposable clothing skyrocketed. These choices led fashion retailers to give life to the environmentally detrimental breed of “fast fashion.” Moving production from a domestic to an international level, increasing the amount of clothing collections on a yearly basis, and lack of transparency in supply chain are just a few examples of the dangers this industry has created for our planet. The fast fashion industry in particular is one that has been overlooked for decades, now only in focus due to the almost irreparable harm it has caused on a transnational level. No clear, collective legal definition exists for “sustainability” in the fashion industry. This Note explores, analyzes and compares current and potential fashion-specific legislation, domestically and internationally, that has not only created definitions but policies going forward for collective action. This Note focuses on the “four c’s”: compliance, caliber, consumers and circularity. These “c’s” create a broad answer as to how some of this environmental damage can be stopped going forward. The solution lies in collective transparency as well as a circular economy. The growth of investment in companies who value environmental, social, and governance (ESG) standards has allowed consumers to change past behaviors toward a circular economy. It is vital that consumers invest in spaces they know are working towards a better future, in all aspects.

A Hyper-Personalized Product Recommendation System Focused on Customer Segmentation: An Application in the Fashion Retail Industry

Providing the right products, at the right place and time, according to their customer’s preferences, is a problem-seeking solution, especially for companies operating in the retail industry. This study presents an integrated product RS that combines various data mining techniques with this motivation. The proposed approach consists of the following steps: (1) customer segmentation; (2) adding the location dimension and determining the association rules; (3) the creation of product recommendations. We used the RFM technique for customer segmentation and the k-means clustering algorithm to create customer segments with customer-based RFM values. Then, the Apriori algorithm, one of the association rule mining algorithms, is used to create accurate rules. In this way, cluster-based association rules are created. Finally, product recommendations are presented with a rule-based heuristic algorithm. This is the first system that considers customers’ demographic data in the fashion retail industry in the literature. Furthermore, the customer location information is used as a parameter for the first time for the clustering phase of a fashion retail product RS. The proposed systematic approach is aimed at producing hyper-personalized product recommendations for customers. The proposed system is implemented on real-world e-commerce data and compared with the current RSs used according to well-known metrics and the average sales information. The results show that the proposed system provides better values.

The Value of Social Media Data in Fashion Forecasting

Problem definition: How to use social media to predict style color and jeans fit sales for a retailer. Academic/practical relevance: Neither retail practice nor the academic literature provides a method for using social media to predict style color and jeans fit sales for a retailer. We present and validate a systematic approach for doing that. Methodology: Demand forecasting in the fashion industry is challenging due to short product lifetimes, long manufacturing lead times, and constant innovation of fashion products. We investigate the value of social media information for color trends and jeans fit forecasting. We partner with three multinational retailers, two apparel and one footwear, and combine their proprietary data sets with web-crawled publicly available data on Twitter and the Google Search Volume Index. We implement a variety of machine learning models to develop forecasts that can be used in setting the initial shipment quantity for an item, arguably the most important decision for fashion retailers. Results: Our findings show that fine-grained social media information has significant predictive power in forecasting color and fit demands months in advance of the sales season, and therefore greatly helps in making the initial shipment quantity decision. The predictive power of including social media features, measured by the improvement of the out-of-sample mean absolute deviation over current practice ranges from 24% to 57%. Managerial implications: To our knowledge, this study is the first to explore and demonstrate the value of social media information in fashion demand forecasting in a way that is practical and operable for fashion retailers. With consistent results across all three retailers, we demonstrate the robustness of our findings over market and geographic heterogeneity, and different forecast horizons. Moreover, we discuss potential mechanisms that might be driving this significant predictive power. Our results suggest that changes in fashion demand are driven more by “bottom-up” changes in consumer preferences than by “top-down” influence from the fashion industry. Funding: This work was supported by Wharton School Fishman-Davidson Center for Service and Operations Management, the Wharton School Baker Retailing Center, and the Wharton School Risk Management Center Russell Ackoff Doctoral Student Fellowship. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1193 .

Jeans and their Fashionable Meanings: Revisiting Beverly Gordon's Cultural Conceptual Framework

Jeans and their Fashionable Meanings: Revisiting Beverly Gordon's Cultural Conceptual Framework

The Identification and Prioritization of Success Factors for Online Egyptian Fashion Retailers using the Analytic Hierarchy Process

The Identification and Prioritization of Success Factors for Online Egyptian Fashion Retailers using the Analytic Hierarchy Process

Omnichannel Fashion Retail in Indonesia: How it affects Marketing Performance?

Objectives: Mobile commerce is an appropriate omnichannel practice adoption for fashion retail. Omnichannel in the retail industry is currently becoming an innovation strategy to increase consumer interaction by integrating various sales channel services. Consumers' channel-switching behavior remains as one of the challenges in the retail industry. To deal with these challenges, providing multiple points of contact to interact with consumers that gain competitive advantage and improve marketing performance is required.Methodology: This study is a causal research with a 95% confidence interval in collecting and constructing the data structure to evaluate the cause-and-effect relationship of the variables. The primary data was obtained through a survey of 91 retail fashion consumers in Indonesia. Subsequently, the data was analyzed using structural equation modeling.Finding: Compared to the previous studies, the results of this study indicated that novelty, hedonic, and utilitarian motivations influence brand love through omnichannel customer experience. To improve brand love, companies need to improve customer experience.Conclusion: Based on the findings, the researchers felt one of the biggest flaws in the study was only collecting data on consumers of international clothing products whose physical stores have only been operating in Indonesia

Investigating the impact of body shape on garment fit

PurposeBody shape is a critical variable influencing consumers' garment choices (Zakaria, 2017), yet research investigating how UK females with varying body shapes evaluate and experience fit is limited. Moreover, while digital methods exist to classify female body shapes, application in a commercial setting is limited. To fill this gap within the literature, this study aims to understand the influence of body shape variation on garment fit evaluations of 30 UK females aged 18–34 years.Design/methodology/approachThis study conducts a physical garment try-on session whereby 30 UK females aged 18–34 years were body-scanned and categorised into a body shape, using the Female Figure Identification Technique method. Participants verbalised their fit experiences during a physical try-on session through semi-structured interviews to gain a deeper understanding of individuals' fit appraisals.FindingsThe findings demonstrate that UK females who share the same body shape classification experience the same issues when appraising dress fit, challenging Makhanya and Mabuza (2020) who found that body shape does not influence apparel fit satisfaction. The results shed light on the importance of body shape during the fit appraisal process.Research limitations/implicationsDespite the contribution, future research to improve the limitations should be addressed. First, although it was necessary to investigate a UK demographic to address research gaps, the finding of this study cannot be generalised to the entire UK female population nor to other areas of the world. Hence, future research should overcome this limitation by extending this study further to other countries, cultures and ethnicities.Practical implicationsThe findings of the present study shed light on the role of body shape in determining satisfactory clothing fit and how females' fit experiences will differ depending on their body shape classification. Thus, fashion retailers should use this insight to better inform their promotional strategies, not only making them more inclusive but also to help assist this particular consumer segment with their clothing decisions based on their body shape.Originality/valueThe present study provides an in-depth understanding of how females with the same body shape experience garment fit, contributing novel findings to the literature through a mixed-method inquiry previously lacking in this area, with a UK demographic which has not previously been explored.

Forecasting Offline Retail Sales in the COVID-19 Pandemic Period: A Case Study of a Complex Shopping Mall in South Korea

This study examines the case of a shopping mall in Seoul, South Korea, based on its offline retail sales data during the period of the enforcement of the COVID-19 pandemic social distancing policy. South Korea implemented strict social distancing, especially in retail categories where people eat out, due to the danger of spreading infectious disease. A total of 55 retail shops’ sales data were analyzed and classified into five categories: fashion, food and beverage (f&b), entertainment, cosmetics and sport. Autoregressive integrated moving average (ARIMA) and exponential smoothing (ETS) models were employed, and the autocorrelation (ACF) and partial autocorrelation (PACF) of each retail category’s sales data were analyzed. The mean absolute percentage error (MAPE) was used to determine the most suitable forecasting model for each retail category. In this way, the f&b and entertainment retail categories, in which people eat out, were found to have been significantly impacted, with their 2022 sales forecasted to be less than 80% of their 2018 and 2019 sales. The fashion retail category was also significantly impacted, slowly recovering sales in 2022. The cosmetics and sport retail categories were little impacted by the COVID-19 outbreak, with their retail sales having already recovered by 2022.

Examining the role of consumer motivations to use voice assistants for fashion shopping: The mediating role of awe experience and eWOM

Artificial intelligence-enabled voice assistant services have received notable scholarly attention. Fashion retailers offer AI-based voice assistants to facilitate online shoppers. However, the consumer motivations to use digital voice assistants and their effect on the purchase intentions of online fashion shoppers are unexplored. To bridge this literature gap, this study presents a unique theoretical model grounded in the consumer innovativeness concept, broaden-and-built theory, and stimulus-organism-response model to explore the effect of motivated consumer innovativeness to use digital voice assistants on purchase intention and awe experience of online shoppers. The study used data collected from 538 users of digital voice assistants for online shopping of fashion products. Structural equation modeling analysis revealed that the functional, hedonic, social, and cognitive motivated consumer innovativeness for using voice assistants affects purchase intention and awe experience. Further, the awe experience mediates the relationship between motivated consumer innovativeness and purchase intention; and electronic word-of-mouth mediates the relationship between awe experience and purchase intention. The study theoretically contributes to the extant literature on consumer innovativeness, AI-based voice assistants, and fashion shopping. The findings offer insights to fashion retailers for improved use of voice assistants by online shoppers.

Aesthetic Labor in Religious Contexts: Women Encountering Modest Dress in the Workplace in the UK and Saudi Arabia

This article explores how UK women encounter religious dress and behavior codes in religious work contexts. It compares two very different case studies: women working at faith-based organizations in the UK and women working for secular organizations who travel for work to Saudi Arabia. Using 65 semi-structured interviews, participant wardrobe photographs, and observation in regional modest fashion retail, the article analyzes women workers’ experience in religious contexts as a form of aesthetic labor. It investigates the gendered and religious components which structure women’s different responses to workplace modesty codes. Detailing the additional aesthetic and emotional labor demanded of women in crafting modest professional appearances in religious contexts, the research reveals continuities in how workplace modesty requirements impact on women’s occupational performance and sense of self. The conclusion argues that religion-related workplace modesty codes constitute a religiously-inflected form of organizational aesthetics that may operate simultaneously with, but be experienced differently from, secular-driven organizational aesthetics. We find that religious dress codes are arbitrated by the avoidance of shame, an affect accompanying the government of modesty for all involved. We find that organizations benefit from, but do not recognize or recompense, the additional aesthetic labor that modesty demands of women.

Factors of Organizational Agility Mediated by Competitive Performance in Online Fashion Retailers

An organization is the formation of human relations work behavior efficiently and effectively to obtain personal satisfaction in carrying out their duties and providing certain environmental conditions to achieve goals. This study aimed to determine the effect of system quality, adoption of business intelligence, and flexibility of IT infrastructure mediated by organizational agility mediated by competitive performance on online fashion retailers so that it can be used as a reference in the field of science. Quantitative techniques were used in this study. The analysis of this study is a structural approach to the Equation Model (SEM) with the help of smart PLS. The results of this study are to indicate that the adoption of business intelligence is not able to affect organizational agility, system quality affects organizational agility, IT infrastructure flexibility affects organizational agility, competitive performance affects organizational agility, system quality affects competitive performance, adoption of business intelligence affects competitive performance, IT infrastructure flexibility affects competitive performance. Competitive performance is able to mediate the effect of system quality on organizational agility and IT infrastructure flexibility on organizational agility. Competitive performance is not able to mediate the adoption of business intelligence on organizational agility. This research contributes literature for further research conducted by other researchers.

Social media insights for non-luxury fashion SMEs in emerging markets: evidence from young consumers

PurposeThe study investigates the factors that influence young consumers (Gen Zs and Ys) in emerging markets to engage fashion ads of non-luxury fashion retail small- to medium-size enterprises (SMEs) on social media. Through a desk assessment of practice and the phenomenon's available evidence in the extant literature, four main drivers were delineated, reviewed and subsequently tested to influence young consumers' behavioural engagements of emerging markets' fashion SMEs' social media contents.Design/methodology/approachA non-probability sample of 1,150 respondents (Gen Y and Z combined) in Ghana, an emerging market, formed the sample for the study. The respondents assessed four empirically identified antecedents (sales campaigns, relevant sales-related information, catchy and inspiring product/brand photo/video and consumer-generated contents) that are likely to influence their behavioural engagement on social media platforms (Instagram, Facebook, WhatsApp and Twitter). SmartPLS (version 3.3.3) was employed to perform partial least square structural equation modelling.FindingsThe results showed that to engage fashion-related ads, particularly from non-luxury fashion SMEs, young consumers consider sales campaigns, cues from consumer-generated contents, as well as quality and inspiring videos and photos. Less attention is given to relevant sales-related information.Practical implicationsThe three significant drivers of engagement found in the current study provide managerial knowledge for non-luxury fashion SMEs in emerging markets. Videos and still pictures must be of high definition and quality. Short and long promotional campaigns may drive positive behavioural engagements. Interactivity between fashion SMEs and young consumers is encouraged as it precipitates the positive engagement behaviours enabled by social media. The study concludes with actionable recommendations for the non-luxury fashion SME sector in emerging economies.Originality/valueThe study is the first of its kind to ascertain what drives young consumers' engagement with non-luxury fashion SMEs on social media. It provides managerial insights and guidance to SMEs in emerging markets on effective social media fashion retailing targeted mainly at digital natives, the dominant generational cohorts on social media in most emerging economies.

Factors Influencing Online Shopping behavior of Online Fashion Retailers

The COVID-19 pandemic has changed online shopping behaviors, according to a survey of about 3,700 consumers in nine emerging and developed economies. As people embraced social distancing, they turned to online shopping more than ever before. The fluctuation of the COVID-19 pandemic and the ways it influences and modifies our shopping habits will likely continue into the foreseeable future. Without a doubt, the COVID-19 pandemic forced everyone to change the way they shop. Whether you were a fan of online shopping or in-store browsing, the pandemic altered routines in many obvious, and some not so obvious. Therefore to understand what now actually affects consumer purchase behavior when it comes to online shopping is key to success for many e-tailers especially for those online fashion retailers which is the main focus of this study.The purpose of this research is to study factors influencing online shopping behavior of online fashion retailers (apparel, fashion accessories, shoes). These factors include eight independent variables: Web design(WD), Reputation(RP), Web contend(WC), Brand effect(BR), Product(PD), Service(SV), Price(PR), and Promotion (PM), and one dependent variable: Online shopping behavior (OB). 437 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .027(.90), the model seems to fit well according to the descriptive measures of fit. On the contrary, CFI and TLI, which are incremental fit indices that compare the fit of our hypothesized model with that of a baseline model (i.e., a model with the worst fit), whose values are both greater than .90 (CFI = .981, TLI = .977) indicating an acceptable fit. More importantly almost all factors included in the model except Web contend (WC) i.e. Reputation(RP), Web design(WD), Brand effect(BR), Product(PD), Service(SV), Price(PR), and Promotion(PM) seem to significantly affect online shopping behavior of online fashion retailers due to their p-values are all less than .05.

Believing in Analytics: Managers’ Adherence to Price Recommendations from a DSS

Problem definition: We study the adherence to the recommendations of a decision support system (DSS) for clearance markdowns at Zara, the Spanish fast fashion retailer. Our focus is on behavioral drivers of the decision to deviate from the recommendation, and the magnitude of the deviation when it occurs. Academic/practical relevance: A major obstacle in the implementation of prescriptive analytics is users’ lack of trust in the tool, which leads to status quo bias. Understanding the behavioral aspects of managers’ usage of these tools, as well as the specific biases that affect managers in revenue management contexts, is paramount for a successful rollout. Methodology: We use data collected by Zara during seven clearance sales campaigns to analyze the drivers of managers’ adherence to the DSS. Results: Adherence to the DSS’s recommendations was higher, and deviations were smaller, when the products were predicted to run out before the end of the campaign, consistent with the fact that inventory and sales were more salient to managers than revenue. When there was a higher number of prices to set, managers of Zara’s own stores were more likely to deviate from the DSS’s recommendations, whereas franchise managers did the opposite and showed a weak tendency to adhere more often instead. Two interventions aimed at shifting salience from inventory and sales to revenue helped increase adherence and overall revenue. Managerial implications: Our findings provide insights on how to increase voluntary adherence that can be used in any context in which a company wants an analytical tool to be adopted organically by its users. We also shed light on two common biases that can affect managers in a revenue management context, namely salience of inventory and sales, and cognitive workload. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.1166 .

Aesthetic labour and diversity on the shopfloor: the experiences of women workers in fashion retail

PurposeThis paper explores the workplace experiences of aesthetic labour among racially diverse frontline women workers in a fashion retail store.Design/methodology/approachThis qualitative study is based on an ethnographic study, drawing on findings from participant observation and interviews with frontline workers at a fashion retail store in the UK.FindingsThis paper explores how the embodiments of aesthetic labour are perpetually produced and commodified through the discipline of management in a fashion retail store. It challenges the notion of phenotypical Whiteness as the beauty standard within fashion retail and demonstrates how embodiments differ according to race. While White women are continuously scrutinised by their appearance, the aesthetic demands for women of colour tend to focus on speech and racialised bodies to provide “authentically” exotic experiences for customers. Additionally, this study highlights how the mobilisation of aesthetic labour can create work humiliation and work alienation.Research limitations/implicationsDespite this study being based on an ethnographic study at one British fashion retailer, this paper seeks to give voices to an underrepresented group by exploring the lived experiences of racially diverse women workers.Originality/valueThis paper contributes to the intersection between aesthetic labour and race from an embodiment perspective, exploring the workplace experiences of racially diverse women workers in fashion retail and how their various forms of embodiment are racialised and commodified.

Data Analytics Application in Fashion Retail SMEs (A Case Study in Caracas Fashion Store)

Data analytics plays a paramount role in maximizing productivity and profitability for businesses by deriving insights from pre-existing data to predict market trends and client habits to make better business decisions. In accordance with Industrial Revolution 4.0, most SMEs have begun to implement an e-commerce business model, thus, customer data is generated at an exponential rate, allowing SMEs to further develop their services for greater user satisfaction. However, the abundance of unsorted and ambiguous data leads to issues such as server overload and inefficient customer sales cycle tracking. This paper will explain the application of data analytics techniques and architectures to overcome these issues in a fashion retail SME, as well as the benefits and drawbacks of these solutions.
 

Snakes and Ladders: Unpacking the Personalisation-Privacy Paradox in the Context of AI-Enabled Personalisation in the Physical Retail Environment

Artificial intelligence (AI) is expected to bring to the physical retail environment the kind of mass personalisation that is already common in online commerce, delivering offers that are targeted to each customer, and that adapt to changes in the customer’s context. However, factors related to the in-store environment, the small screen where the offer is delivered, and privacy concerns, create uncertainty regarding how customers might react to highly personalised offers that are delivered to their smartphones while they are in a store. To investigate how customers exposed to this type of AI-enabled, personalised offer, perceive it and respond to it, we use the personalisation-privacy paradox lens. Case study data focused on UK based, female, fashion retail shoppers exposed to such offers reveal that they seek discounts on desired items and improvement of the in-store experience; they resent interruptions and generic offers; express a strong desire for autonomy; and attempt to control access to private information and to improve the recommendations that they receive. Our analysis also exposes contradictions in customers’ expectations of personalisation that requires location tracking. We conclude by drawing an analogy to the popular Snakes and Ladders game, to illustrate the delicate balance between drivers and barriers to acceptance of AI-enabled, highly personalised offers delivered to customers’ smartphones while they are in-store.