Women's Apparel Research Articles

Perceived Online Ethics for Brand Building of Women’s Apparel and Consumer Behavioral Intentions

Objectives: This research aims to explore the influence of Consumer Behavioral Intentions (CBI) on the ethical practices of online Women's Apparel (WA) sellers, specifically in relation to consumers’ purchasing and return behaviors. Additionally, it seeks to assess and consolidate existing findings on sustainable and ethical branding within the WA industry. The study identifies key factors that contribute to successful, eco-friendly fashion branding, while also highlighting prevalent ethical challenges in the sector. Methods: The research involves a synthesis of previous studies on sustainable and ethical branding in the WA industry. It examines various sources to create a comprehensive list of elements that support environmentally conscious branding. Ethical challenges within WA production, including working conditions, wages, and labor rights, are analyzed in the context of their impact on consumer behavior. Results: The study reveals that ethical branding significantly impacts consumer purchase and return intentions. It identifies poor working conditions, low wages, long hours, and restricted unionization rights as the primary ethical concerns within the WA sector. These issues have increased global scrutiny on WA industry practices, influencing both consumer perception and brand credibility. Conclusion: The findings underscore the importance of ethical practices in building credible and successful WA brands. Enhanced consumer awareness of environmental and ethical issues affects their buying decisions, urging WA brands to address these concerns. Addressing ethical dilemmas is crucial for sustaining the sector’s long-term success and aligns with the growing trend of consumer preference for sustainable and responsible brands.

Investigation in Understanding the Influence of Brand Preferences on Purchase Intention: Examples of Indonesian Women’s Apparel Brand

This study aims to investigate the factors influencing brand preferences in the purchase intention of Indonesian women’s apparel brands. The data were collected through a questionnaire distribution of 422 respondents from Indonesian women’s apparel brand consumers and processed with the Structural Equation Model - Partial Least Square (SEM-PLS). Brand preferences in selecting and purchasing women's apparel are influenced by satisfaction, extrinsic cues, and brand trust. On the contrary, intrinsic cues do not affect brand preferences in purchase intention because extrinsic cues can dominate more, consumers desire to save more time, and there are rapidly fast fashion trends. Moreover, brand preferences have a greater impact on purchase intention. Women's apparel brands can shape the brand preferences of their consumers based on the influencing factors to dominate the market competition. This study contributes to the literature on brand preferences in choosing women's fashion behavior. This is one of the pioneering studies to empirically examine the influence of cues and brands in the context of the desire of the Z generation to purchase women's apparel in an emerging market such as Indonesia.

AI-driven innovation in ethnic clothing design: an intersection of machine learning and cultural heritage

<abstract><p>This study delves into the innovative application of Artificial Intelligence (AI) and machine learning algorithms in the realm of ethnic fashion design, with a specific emphasis on the Miao women's apparel. We introduce an AI-powered approach that strategically bridges modern technology with traditional elements, denoting a significant stride in the field of fashion design. Our research underscores three major aspects: customization of body shape, fabric selection, and innovative design. An AI-driven statistical methodology was utilized to accurately adapt to the unique body characteristics of Miao women, demonstrating an application of machine learning in pattern recognition. Furthermore, the AI's capacity to analyze the fabric properties was harnessed to optimize material selection, creating a balance between aesthetics and comfort. The innovative use of the Multimodal Unsupervised Image-to-Image Translation (MUNIT) algorithm, an AI tool, generated diverse and trendy designs, thereby enriching the distinctiveness of ethnic apparel. Our study accentuates the synergistic blend of traditional crafting methods and modern technological applications, highlighting the role of AI in the sustainable development of ethnic fashion. Additionally, we also demonstrate the advantages of Made-to-Measure (MTM) approaches, emphasizing the importance of individual customization in contemporary fashion design. This research presents a pioneering exploration at the nexus of AI, pattern recognition, and ethnic fashion design, which has the potential to transform the future of the fashion industry.</p></abstract>

Influence of e-WOM on women's apparel purchase intention: a study on Myntra app

Influence of e-WOM on women's apparel purchase intention: a study on Myntra app

The Collective Working Body: Rethinking Apparel Workers' Health and Well-being during the COVID-19 Pandemic in Sri Lanka

This article contributes to debates on global apparel workers’ health and well-being through an examination of how Sri Lankan workers were affected and treated during the COVID-19 pandemic. Based on qualitative interviews in and around the Katunayake Export Processing Zone, the article takes the Sri Lankan apparel industry as a case study. It reconceptualises the “precarious working body” as a “collective body” in order to demonstrate how workers’ health was a matter of collective precariousness. Workers’ health was not only dependent on that of others around them inside densely populated factories, but was also shaped by systemic material and discursive practices that affected workers collectively. These material practices included labour control and incentive structures that prevented workers from seeking medical attention and taking leave when needed, which in turn led to the spread of the virus across factories. The discursive practices comprise the social stigma and devaluation of women apparel workers that facilitated the blaming of workers for spreading the virus and enabled their inhumane treatment during the pandemic response. We argue that conceiving of apparel workers as a “collective body” enables a recognition of the systemic forces that create ill health at work and that expose certain (but not all) working bodies to the risks of infection. KEYWORDS: labour regimes; social stigma; occupational health; apparel industry; COVID-19

Measurement and prediction of the international reputation of Chinese women’s apparel and accessories

Chinese women’s apparel and accessories have been often mentioned by other countries in history and nowadays, and the underlying culture along with these apparel and accessories contributes to this developing world to some extent. The assessment of the international reputation for these kinds of apparel and accessories is important for better understanding the worldwide cultural exchange, globalization, social development and so on; however, it remains unknown. This study presents a work with the overall objective to measure and predict the international reputation of Chinese women’s apparel and accessories. To reach this objective, the study first proposes a data mining procedure to use online query volume data from the Google Ngram corpus to construct a reputation index in order to measure the international reputation of Chinese women’s apparel and accessories. Then, by establishing a series of socio-economic and political determinants associated with the international reputation of Chinese women’s apparel and accessories, several forms of support vector machine based models are developed, aiming to predict their international reputation. There are two contributions out of this work: (1) presenting the first ever large-scale quantitative examination of the trend and measurement of the international reputation of Chinese women's apparel and accessories, which provides a new method to identify the dynamic transition of sociocultural development; (2) constructing a quantitative model to predict the international reputation of Chinese women's apparel and accessories, which generalizes an implication to understand the other sociocultural object and its impact factors.

An Empirical Study on Consumer Behaviour towards Online Shopping of Women Apparels in Kolhapur District

The internet revolution has redefined every business sector across the world especially online shopping and online shopping behavior of the people. The increased penetration of internet has fuelled the online retailing across the world and specifically in the emerging markets of developing countries like India. The Indian retailing market is evolving their business models into e-retailing models. The Indian industry of online retailing has crossed 20.5 Billion USD in the year 2017, and in 2018, it has crossed 25 billion USD and in 2021, there is expectation that it will increase up to 62 Billion USD. The Indian companies are facing challenges in identifying that what is driving the concept of the online shopping. Aim: This study is focused on behavior of customer on online shopping of women apparels, the various factors will be identifies that motivate the female shoppers to buy women apparels through online mode. Method: This study is descriptive and exploratory research as the primary data is collected through selfstructured questionnaire and analyzed that made to identify the customer behavior towards online shopping of women apparels. The structured questionnaire included Five Point Likert scale questions ranging from strongly agree to disagree. The respondents selected for this study are from Different taluk of Kolhapur like Chandgad, Bhudargad, Gadhinglaj, Ajara, Radhanagari, Shirol, shahuwadi, Hatkanangal etc. Due to times constraints, the convenience random sampling and cluster sampling method method had been used to collect the data and the total respondents selected for this study are 500. Anova test has been applied on collected data using SPSS Software to extract the various factors of customer’s behavior towards online shopping of women apparels. Conclusion: The findings of this paper will provide deep insights regarding online retailing and consumer behavior towards online shopping of Women Apparels to the small and big online International or National companies, Brands franchisee holder, retailers, Market strategy or policy makers.

WITHDRAWN: Women’s e-commerce clothing sentiment analysis by probabilistic model LDA using R-SPARK

In today's fields of education and literature, electronic commerce (e-commerce) is a well-known subject. Excellent research on e-commerce focuses predominantly on developing economies. Customer behavior analysis is gaining more prominence as consumers move from visiting retail shops to shopping online from the e-commerce view. In this article, review is taken into account in the case of sentiment analysis to evaluate, implement and analyse the most effective techniques. In numerous research ventures, including in the area of text classification and information retrieval, probabilistic models currently play a major role. Latent Semantic Analysis (LSA), Probabilistic Latent Semantic Indexing (PLSA) and Latent Dirichlet Allocation (LDA) represent probabilistic models. The LDA approach is used in this paper to define online feedback for sentiment analysis since the LDA approach is intended to address LSA and PLSA issues. Online shopping seems to become a central platform for shoppers with the development of e-commerce, and it is necessary to forecast the scale of e-commerce transactions. This paper is used to scan online data of women's apparel. By encouraging a more custom-made shopping experience, it will boost customer loyalty and sales, resulting in higher retention rates and viable improvement.

A study of women's apparel buying behavior with reference to Kolhapur district

A study of women's apparel buying behavior with reference to Kolhapur district

Consumer Preference and Satisfaction with Reference to Women Apparels at Max Store

The trend of fashion apparels is growing rapidly. Women consumers are spending more across products and are obsessive about trendy apparels. The study focuses to examine the consumer preference and satisfaction with reference to women apparel at Max store. Primary data is obtained from survey questionnaire using convenience sampling method. Hypothesis is framed to analyse if there is a significant influence of age and income on consumer preference and satisfaction towards women apparels at max store at A S Rao Nagar. Primary data is collected from 150 respondents using convenience sampling. Chi square test is used to analyze the data. Results have indicated that there is no significant influence of age and income on consumer preference and satisfaction.

Towards the Prediction of Aesthetic Requirements for Women's Apparel Product

Towards the Prediction of Aesthetic Requirements for Women's Apparel Product

Development of designs from traditional molela craft of Rajasthan for women apparels

Development of designs from traditional molela craft of Rajasthan for women apparels

Buying Behaviour of Adult Women on Key Factors Influencing Their Purchasing of Fashion Clothing

The apparel market in India is swiftly developing with a change in consumer tastes towards branded apparel. Indian apparel consumers have become highly brand conscious. The focus of this research was on women apparel buyers because women are becoming increasingly independent in making their choices due to their increased education levels, increased purchasing power, their relative freedom from parental or spouse intervention in exercising their shopping style. The main objective of the research was to find out if there was any significant difference on the overall shopping experience of apparels among and within the different groups of women respondents with respect certain demographical aspects such as age, education level, occupation, marital status, frequency of purchase and perceptual aspects such as perceived store atmosphere and perceived brand image that may influence the overall shopping experience of women apparel buyers are examined. In order to examine and compare the group differences between the respondents, a univariate GLM was used and to find where the differences lie between the individual groups, Fisher’s Least Significant Difference (LSD) post hoc test was carried out using IMB® SPSS Statistics®. It was found from the analysis that there is be a significant difference in the satisfaction among different age groups of women on the overall shopping experience of apparels buying and it was also found that there is be a significant difference on shopping experience among women in different professions.The findings of this research can be strategically implemented into apparel marketing scheme by apparel manufacturers and retailers.

E-Service Performance of Apparel E-Retailing Websites

This article takes a longitudinal approach to examine the evolution of e-retail sites in reference to service delivery performance. Using a content analysis approach, product-related e-service attributes currently available on women's apparel websites were identified and quantified in order to compare them to data collected in an earlier time frame. A Chi-square Goodness-of-Fit test was conducted to compare availability of e-service attributes in 2011 and 2016. The current retailers provided more product description/presentation attributes on their websites than in the 2011 research. However, they are still at an unsatisfactory level that need further improvement. This article offers practical insights for fashion websites in terms of the areas of strengths and weakness in e-service performance by exploring how e-service performance of apparel e-retailers has changed over the past five years.

Striking Beauties: Women Apparel Workers in the U.S. South, 1930-2000 by Michelle Haberland

Striking Beauties: Women Apparel Workers in the U.S. South, 1930-2000 by Michelle Haberland

Improving the Performance of CBIR on Islamic Women Apparels Using Normalized PHOG

The designs of Islamic women apparels is dynamically changing, which can be shown by emerging of online shops selling clothing with fast updates of newest models. Traditionally, buying the clothes online can be done by querying the keywords to the retrieval system. The approach has a drawback that the keywords cannot describe the clothes designs precisely. Therefore, a searching based on content–known as content-based image retrieval (CBIR)–is required. One of the features used in CBIR is the shape. This article presents a new normalization approach to the Pyramid Histogram of Oriented Gradients (PHOG) as a mean for shape feature extraction of women Islamic clothing in a retrieval system. We refer to the proposed approach as normalized PHOG (NPHOG). The Euclidean distance measured the similarity of the clothing. The performance of the system was evaluated by using 340 clothing images, comprised of four clothing categories, 85 images for each category: blouse-pants, long dress, outerwear, and tunic. The recall and precision parameters measured the retrieval performance; the Histogram of Oriented Gradients (HOG) and PHOG were the methods for comparison. The experiments showed that NPHOG improved the HOG and PHOG performance in three clothing categories.

Assessment of Demographic Impact on Female Psychographics

The mall culture that got established since 2011 onwards was something urban India had never witnessed earlier. Retail-real estate synergy had started addressing an uptrend in the metros from 2012 onwards. Even, the consumer perception towards a mall has changed drastically over the past decade; from just considering a mall as an entertainment option to a complete shopping zone. Also, realizing the psychologically involved nature of women in shopping in comparison to their male counterparts, the current study aims at examining the relationship between the demographic variables and psychographic purchase behaviour of females shopping women apparels and accessories in the stores in Delhi malls. This study is based on empirical research conducted through a mall intercept survey in 6 malls in Delhi chosen purposely. It followed multi-stage sampling with a sample size of 100x6=600 female shoppers. The findings of this study are consistent and have been supported by previous studies. It revealed that demographical factors have an impact on the buying pattern of the respondents. The conclusion advocates that there exists a significant relationship between the demographical factors and the psychographic purchase behavior of the female shoppers. However, the relationship between age and psychographic purchase did not reach the level of statistical significance yet, the purchase behaviour varied with age.

Economics of vanity sizing

This paper examines the size charts of 54 American apparel retailers. Evidence reveals that sizes are inflated for women's apparel brands with moderately higher prices. Very expensive designer brands measure significantly smaller than lower priced brands for women's apparel. Brands that target young adult female consumers measure significantly smaller than their counterparts that target relatively older consumers.Evidence indicates little, if any, vanity sizing in men's or children's apparel.

Under Armour's Willful Digital Moves

In 2013, Under Armour had $2.3 billion in sales yet only $500 million came from its women's apparel, and the company was ready to expand into the female market segment. The “I Will What I Want” global women's marketing campaign was the largest Under Armour had ever run. Founder Keven Plank and his team launched the campaign on a multichannel platform, with social media at its core. The campaign's success surpassed what Plank had imagined, and he is left wondering where to take Under Armour's advertising and marketing next. This case has been used successfully in a marketing course and would be suited for any class with a focus on interactive media, technology, and multichannel marketing. Excerpt UVA-M-0910 Rev. Jul. 27, 2016 Under Armour's Willful Digital Moves Created in 1996, Under Armour, which first created breathable, wicking materials to replace sweaty cotton found in the shirts worn under football pads, was a brand built on a tough-guy and football image. In less than two decades, founder Kevin Plank took Under Armour from a business run out of his grandmother's basement in Washington, DC, to a global business with just less than $ 4billion in sales. By 2013, Under Armour had expanded to shorts, shoes, and even hats, and was already a success within the men's athletic-wear market, competing with powerhouses such as Nike and Adidas. Its marketing and advertisement had focused on targeting men by delivering technical apparel positioned as innovative and modern. In 2013, Under Armour had $ 2.3billion in sales yet only $ 500million came from its women's apparel. Plank was ready to expand into the female market segment. “I Will What I Want” Campaign In March 2013, Under Armour's rival, Adidas, ranked number two in the U.S. sportswear market, one spot in front of Under Armour, launched the “Unite All Originals” campaign targeting women using original artists popular on social media. The ad campaign garnered only 400,000 views on YouTube, did not help boost Adidas's sales, and was considered a failure. Despite Adidas's lack of success in targeting female athletes, in 2014 Plank and his team believed they could do better and decided to take the risk of targeting women with a campaign titled “I Will What I Want.” . . .

국내 여성복 업체의 환편니트 제품 생산현황 조사

The goal of this study is to provide basic data on developing circular knit basic pattern for women in their 20's. Production conditions of circular knit product pattern making among domestic women's apparel industry was researched, and collected data on sizes and ease amounts from woven and circular knit pattern were compared and analyzed. According to the result of the survey, product measurements adjusted to the actual body size fit for the brand's image were used, and the common problem among manufacturers and consumers regarding circular knit products turned out to be change in size and form due to stretching. For the basic pattern of circular knit, stretching quality was reflected in the woven basic pattern based on plain stitch(single knit) and then dart was removed and ease amount was reduced. The result of looking into size and ease amount about woven and circular knit torso & sleeve block shows that there is a significant difference among chest circumference, hip circumference, bi-shoulder length, interscye back, interscye front, scye depth, upper arm circumference and wrist circumference, and it was clear that circumference and width on the areas around the wrist tended to fit around the body more when circular knit was used instead of woven fabric.