Success.ai’s Fashion & Apparel Data for Apparel, Fashion & Luxury Goods Professionals in Asia provides a robust dataset tailored for businesses seeking to connect with key players in Asia’s thriving fashion and luxury goods industries. Covering roles such as brand managers, designers, retail executives, and supply chain leaders, this dataset includes verified contact details, professional insights, and actionable business data.

With access to over 700 million verified global profiles and 130 million profiles focused on Asia, Success.ai ensures your outreach, marketing, and business development strategies are supported by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution positions you to succeed in Asia’s competitive and ever-growing fashion markets.

Why Choose Success.ai’s Fashion & Apparel Data?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of professionals in apparel, fashion, and luxury goods industries across Asia.
   • AI-driven validation ensures 99% accuracy, reducing bounce rates and enhancing communication efficiency.

2. Comprehensive Coverage of Asian Fashion Professionals

   • Includes profiles from major fashion hubs such as China, India, Japan, South Korea, and Southeast Asia.
   • Gain insights into regional consumer trends, emerging fashion markets, and luxury goods opportunities.

3. Continuously Updated Datasets

   • Real-time updates capture changes in leadership, market expansions, and product launches.
   • Stay aligned with evolving industry trends and capitalize on new opportunities effectively.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with professionals across the global fashion and apparel industries, with a focus on Asia.
• 130M+ Profiles in Asia: Gain detailed insights into professionals shaping the region’s fashion and luxury goods markets.
• Verified Contact Details: Access work emails, phone numbers, and business locations for precise targeting.
• Leadership Insights: Engage with designers, brand managers, and retail leaders driving Asia’s fashion trends.

Key Features of the Dataset:

1. Comprehensive Professional Profiles

   • Identify and connect with decision-makers in apparel design, luxury goods branding, retail operations, and supply chain management.
   • Target individuals leading innovation in sustainable fashion, fast fashion, and digital transformation.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (luxury goods, ready-to-wear, footwear), geographic location, or job function.
   • Tailor campaigns to align with specific market needs, such as emerging e-commerce platforms or regional fashion preferences.

3. Industry and Regional Insights

   • Leverage data on consumer behaviors, market growth, and regional trends in Asia’s fashion and luxury goods sectors.
   • Refine marketing strategies, product development, and partnership outreach based on actionable insights.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Brand Expansion

   • Design targeted campaigns to promote apparel, luxury goods, or retail solutions to fashion professionals in Asia.
   • Leverage multi-channel outreach, including email, phone, and social media, to maximize engagement.

2. Product Development and Consumer Insights

   • Utilize data on regional trends and consumer preferences to guide product development and marketing strategies.
   • Collaborate with brand managers and designers to tailor collections or launch new offerings aligned with market demands.

3. Partnership Development and Retail Collaboration

   • Build relationships with retail chains, luxury brands, and supply chain leaders seeking strategic alliances.
   • Foster partnerships that expand distribution channels, enhance brand visibility, or improve operational efficiencies.

4. Market Research and Competitive Analysis

   • Analyze trends in Asia’s fashion industry to refine business strategies, identify market gaps, and anticipate consumer demands.
   • Benchmark against competitors to stay ahead in the fast-paced fashion landscape.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality fashion and apparel data at competitive prices, ensuring strong ROI for your marketing, sales, and product development efforts.

2. Seamless Integration

   • Integrate verified data into CRM systems, analytics platforms, or marketing tools via APIs or downloadable formats, streamlining workfl...

In this study, 403 Chinese consumers generalizable to the broader population were surveyed on their motivations to shop for fashion apparel in both high street and e-commerce environments. Statistical analysis was undertaken through multiple T-Tests and MANOVA with the assistance of SPSS and G*Power.

To increase the profits of international brands, this paper presents the motivations of Chinese consumers to engage in fashion retail, building upon established theory in hedonic and utilitarian motivations. With China set to capture over 24% of the $212 billion fashion market, international brands need to understand the unique motivations of Chinese consumers in order to capitalise on the market. However, the motivations of Chinese people to engage in fashion retail are as yet undefined, limiting the ability for international fashion retailers to operate with prosperity in the Chinese market.

Success.ai’s Fashion & Apparel Data for Apparel, Fashion & Luxury Goods Professionals in North America offers a comprehensive dataset designed to help businesses connect with decision-makers and key professionals in the dynamic fashion and apparel industry. Covering roles such as designers, brand managers, retail executives, and supply chain leaders, this dataset provides verified contact details, professional insights, and actionable business data.

With access to over 700 million verified global profiles, including 130 million in North America, Success.ai ensures your marketing, outreach, and business development strategies are powered by accurate, continuously updated, and AI-validated information. Backed by our Best Price Guarantee, this solution is indispensable for thriving in North America’s competitive fashion market.

Why Choose Success.ai’s Fashion & Apparel Data?

1. Verified Contact Data for Targeted Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of professionals in apparel, fashion, and luxury goods industries.
   • AI-driven validation ensures 99% accuracy, improving communication efficiency and minimizing data gaps.

2. Comprehensive Coverage of North American Fashion Professionals

   • Includes profiles of professionals from major fashion hubs such as New York, Los Angeles, Chicago, and Miami.
   • Gain insights into regional trends, consumer preferences, and market opportunities in the fashion and luxury goods sectors.

3. Continuously Updated Datasets

   • Real-time updates capture changes in leadership, brand expansions, and market dynamics.
   • Stay aligned with evolving industry trends and seize new opportunities effectively.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful use of data.

Data Highlights:

• 700M+ Verified Global Profiles: Engage with apparel, fashion, and luxury goods professionals worldwide, with a focus on North America.
• 130M+ Profiles in North America: Gain verified contact details and actionable insights into the region’s top professionals.
• Contact Details: Access work emails, phone numbers, and business addresses for precision targeting.
• Leadership Insights: Connect with C-suite executives, brand managers, and designers driving innovation in the fashion industry.

Key Features of the Dataset:

1. Professional Profiles in Fashion and Apparel

   • Identify and connect with professionals responsible for product design, brand management, retail operations, and luxury goods marketing.
   • Target individuals leading creative initiatives, logistics, and digital transformation in the fashion industry.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (apparel, luxury goods, footwear), geographic location, or job function.
   • Tailor campaigns to align with specific market needs such as sustainable fashion, e-commerce, or retail expansion.

3. Regional Trends and Industry Insights

   • Leverage data on emerging fashion trends, consumer demands, and market growth in North America.
   • Refine marketing and product development strategies to align with audience expectations and market opportunities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Brand Outreach

   • Design targeted campaigns to promote apparel, luxury goods, or supply chain solutions to professionals in the fashion industry.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media.

2. Product Development and Innovation

   • Utilize insights into consumer preferences and fashion trends to guide product design and marketing strategies.
   • Collaborate with designers and brand managers to refine collections or launch new products.

3. Partnership Development and Collaboration

   • Build relationships with apparel brands, luxury retailers, and fashion designers exploring strategic alliances.
   • Foster partnerships that expand market reach, enhance brand visibility, or improve supply chain efficiency.

4. Market Research and Competitive Analysis

   • Analyze trends in North America’s fashion industry to refine business strategies, identify market gaps, and anticipate consumer demands.
   • Benchmark against competitors to stay ahead in the rapidly evolving fashion landscape.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality fashion and apparel data at competitive prices, ensuring strong ROI for your marketing, sales, and product development efforts.

2. Seamless Integration

   • Integrate verified fashion data into CRM systems, analytics platforms, or marketing tools via APIs or dow...

Fashion Retail Sales Dataset

Introduction The "Fashion Retail Sales" is a comprehensive collection of data representing sales transactions from a clothing store. This dataset provides valuable insights into the purchasing behavior of customers, the items they buy, the payment methods used, and their satisfaction levels with the products. It is a rich source of information for retail analysts, data scientists, and business owners looking to understand and optimize their clothing store's operations.

Context In today's dynamic and competitive retail environment, understanding customer preferences and optimizing sales processes is crucial for the success of any clothing store. The "Fashion Retail Sales Dataset" has been meticulously curated to offer a diverse and realistic portrayal of customer interactions with the store. It encompasses data points such as customer reference IDs, purchased items, transaction amounts, purchase dates, review ratings, and payment methods. This dataset has been designed to simulate a real-world scenario and reflects the complexities of a clothing store's day-to-day operations.

Description The "Fashion Retail Sales Dataset" consists of six key columns:

• Customer Reference ID: This column contains unique identifiers for customers, enabling the tracking of individual buying patterns and preferences.
• Item Purchased: It provides information about the clothing items that customers have bought. This column includes a wide variety of clothing items, ranging from T-shirts and jeans to accessories like scarves and hats.
• Purchase Amount (USD): This column details the amount of money spent by each customer for their purchases. It may contain outliers, reflecting occasional high-value purchases.
• Date Purchase: The purchase date indicates when each transaction occurred, offering a temporal perspective on buying trends and seasonality.
• Review Rating: Customers' satisfaction levels are quantified using this column, with ratings ranging from 1 to 5. It is an essential metric for assessing product quality and customer experience.
• Payment Method: This column reveals the method used by customers to make payments, with options including 'Credit Card' and 'Cash'.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows six condensed maps of the distribution of plants producing the following: leather footwear, womens and childrens factory made clothing, synthetic textiles and silks, mens factory made clothing, cotton textiles, and rubber products. All data for these maps is for 1954 with the exception of the rubber products map which is for 1955. Each map is accompanied by a bar graph and pie chart. The bar graphs show the value of production by major categories of products. The pie charts show the percentage distribution of persons employed in each manufacturing industry by province.

The Measurable AI Temu & Fast Fashion E-Receipt Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan, Thailand, Malaysia, Vietnam, Indonesia, Singapore, Hong Kong, Phillippines) - EMEA (Spain, United Arab Emirates, Saudi, Qatar) - Latin America (Brazil, Mexico, Columbia, Argentina)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more - Email ID (can work out user overlap with peers and loyalty)

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

This dataset is about books. It has 1 row and is filtered where the book is Social innovation for business success : shared value in the apparel industry. It features 7 columns including author, publication date, language, and book publisher.

High Fashion Market Outlook

The global high fashion market size is set to witness a substantial growth, with projections indicating an increase from USD 134 billion in 2023 to approximately USD 275 billion by 2032, reflecting a commendable compound annual growth rate (CAGR) of around 8.2%. This growth is primarily driven by the increasing consumer inclination towards luxury and premium fashion products, a trend that is further amplified by the rising disposable incomes and evolving lifestyle preferences across the globe. The high fashion market is experiencing a dynamic transformation, fueled by technological advancements, increased online presence, and a burgeoning demand for personalized and unique fashion experiences.

A significant growth factor for the high fashion market is the continuous influence of social media and digital platforms, which have revolutionized the way consumers interact with fashion brands. Platforms like Instagram, TikTok, and Pinterest have significantly increased the visibility of high fashion brands, enabling them to reach a global audience instantly. Influencer marketing has become a potent tool for these brands, allowing them to create trends and engage with consumers on a deeper level. This digital shift has not only enhanced brand visibility but also driven sales by providing consumers with immediate access to fashion products and trends. Furthermore, the integration of augmented reality (AR) in online shopping experiences is also contributing to market growth by offering consumers a virtual try-before-you-buy experience.

Another pivotal growth driver is the rising awareness and demand for sustainable and ethical fashion. There is an increasing consumer shift towards brands that are committed to environmental sustainability, ethical labor practices, and the use of eco-friendly materials. This shift is compelling high fashion brands to adopt sustainable practices and materials, which not only helps them to cater to the changing consumer preferences but also gives them a competitive edge in the market. Many high fashion brands are launching eco-friendly collections and are transparent about their production processes, thereby appealing to the environmentally conscious consumers who are willing to pay a premium for sustainable products.

Moreover, the high fashion market is being significantly influenced by globalization and urbanization. The expansion of global retail networks and the proliferation of fashion weeks across the world are making high fashion more accessible to a broader audience. Cities like Paris, Milan, and New York continue to be fashion capitals, setting global trends that are embraced worldwide. Additionally, emerging markets, particularly in Asia Pacific and Latin America, are witnessing a growing appetite for high-end fashion as middle-class populations expand and urbanization accelerates, leading to increased consumer spending capacity.

Fashion Berets have emerged as a noteworthy trend within the high fashion accessory segment, capturing the attention of both designers and consumers alike. These stylish headpieces, often associated with timeless elegance and a touch of European flair, are making a significant comeback. Fashion berets are being reimagined by luxury brands, incorporating modern materials and innovative designs that appeal to contemporary tastes. Their versatility allows them to be paired with a variety of outfits, from casual streetwear to sophisticated evening ensembles, making them a must-have accessory for fashion-forward individuals. As fashion berets continue to gain popularity, they are becoming a symbol of chic sophistication, adding a unique element to the high fashion landscape.

Regionally, the high fashion market is witnessing varied growth patterns. North America and Europe continue to dominate the market due to the presence of prominent fashion houses and a strong consumer base with high purchasing power. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by increasing urbanization and the rise of affluent middle-class consumers in countries like China, India, and Japan. Latin America and the Middle East & Africa are also witnessing steady growth, fueled by the improving economic conditions and increasing western influence on fashion trends. Each region presents unique opportunities and challenges, contributing to the diverse growth trajectory of the global high fashion market.

Product Type Analysis

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Global Articles of Apparel and Clothing Accessories of Furskin Market Size Value by Country, 2023 Discover more data with ReportLinker!

The North American textile fabrics industry, valued at approximately $99.82 billion in 2025, is projected to experience steady growth with a Compound Annual Growth Rate (CAGR) of 3.85% from 2025 to 2033. This growth is fueled by several key drivers. Increased demand for apparel and home textiles from a growing and increasingly affluent population is a significant factor. Furthermore, advancements in textile technology, particularly in sustainable and functional fabrics, are driving innovation and expanding application areas. The rise of e-commerce and fast fashion continues to influence market dynamics, although concerns surrounding sustainability and ethical sourcing are creating countervailing pressures. Strong performance in segments like clothing and household applications, coupled with the popularity of cotton and synthetic materials, contribute significantly to the overall market size. However, factors like fluctuating raw material prices and global economic uncertainty pose potential restraints. Competitive pressures from international manufacturers also necessitate continuous innovation and efficiency improvements within the industry. The leading players in this market, encompassing both large multinational corporations and smaller specialized firms, are strategically adapting their product lines and manufacturing processes to meet evolving consumer preferences and environmental concerns. The regional breakdown shows North America as a dominant market within the textile fabrics landscape. Considering the provided data and industry knowledge, we can reasonably estimate that the North American market encompasses a substantial portion – approximately 70% – of the overall market size, with the remaining share distributed across other regions globally. The United States, as the largest economy in North America, drives a significant portion of the regional demand, followed by Canada and Mexico. The growth trajectory within North America is expected to mirror the overall global trend, with consistent year-on-year increases driven by the factors outlined above. The segmentation across applications (clothing, industrial, household) and material types (cotton, jute, silk, synthetics, wool) will continue to influence market dynamics, with potential shifts driven by consumer preferences and technological advancements in material science and manufacturing processes. This report provides a detailed analysis of the North American textile fabrics industry, covering the period from 2019 to 2033. It leverages a robust data set, including historical data (2019-2024), an estimated year (2025), and a comprehensive forecast (2025-2033) to provide valuable insights for industry stakeholders. The report delves into market segmentation by application (clothing, industrial/technical applications, household applications), material type (cotton, jute, silk, synthetics, wool), and process (woven, non-woven), offering a granular understanding of market dynamics. Key search terms include: North America textile market, textile fabric industry trends, woven fabrics market, non-woven fabrics market, cotton textile market, synthetic textile market, textile industry growth, North American textile manufacturers. Recent developments include: February 2023: Huntsman Corporation (NYSE: HUN) announced that it has completed the sale of its Textile Effects division to Archroma, a portfolio company of SK Capital Partners. The agreed purchase price was USD 593 million in cash plus assumed pension liabilities. Huntsman expects the net after-tax cash proceeds to be approximately USD 540 million before customary post-closing adjustments., December 2022: India and Canada are negotiating a free trade agreement (FTA) to boost bilateral trade. The Indian textile industry has suggested various rules related to the agreement. The conditions of the proposed FTA will determine if it will help get more export orders. Currently, India’s apparel exports to Canada are negligible., August 2022: Huntsman Corporation, an American multinational manufacturer and marketer of chemical products, has announced that Archroma, a global leader in sustainable specialty chemicals and solutions and a portfolio company of the US-based private investment firm SK Capital Partners, has entered into a definitive agreement to acquire the Textile Effects business.. Key drivers for this market are: Increasing demand for clothing and accessories, Availability of raw materials at low prices for textile manufacturers. Potential restraints include: Increasing demand for clothing and accessories, Availability of raw materials at low prices for textile manufacturers. Notable trends are: Increasing demand for North America's apparels driving the market.

Forecast: Leather-Based or Leather Apparel Market Size Value in Germany 2023 - 2027 Discover more data with ReportLinker!

this graph was created in IbisWorld:

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It's no secret that our voracious buying habits are damaging the planet. The fashion industry is one of the greatest global polluters, according to OneGreenPlanet, and while structural changes are crucial in solving this problem (we're talking legislative changes here), little old you can do your part too.

In fact, individual consumer behaviour can have a huge impact. The Instagram account 1 million women reported that if everyone in the UK didn't buy new clothes 'for one day, the emissions saved would be equivalent to driving a car around the world 8,640 times'.

And there are worthwhile alternative options to buying new - namely, looking after what you have and shopping second-hand. However, sometimes the need for 'new' prevails, and when it does, why not try hiring clothes?

Already the norm in the US with websites like Rent The Runway, fashion rental platforms are increasingly making their way across the pond. And, its unsurprising since the sharing economy is growing rapidly and is projected to be valued at £269 billion by 2025, according to Forbes.

Be it a wedding guest dress, a Christmas party ensemble, a holiday-perfect wardrobe or a fashion-week ready handbag, some items or events feel like they are not worth investing in, and thats where dress hire comes in.

Though fashion rental isn't without its downsides, we already rent our homes, cars and even our dogs, and our clothes are next.

Articles of Apparel and Clothing Accessories of Furskin Market Size Value Per Capita in Mexico, 2023 Discover more data with ReportLinker!

Raising environmental awareness and product development are two separate and costly investments that many small and medium-sized fashion businesses cannot afford to achieve sustainability. Therefore, there is a need to decide which factors more significantly impact consumer loyalty and purchase intention toward eco-friendly fashion. Thus, the study employs a mixed-methods approach to research how customers' perception about product-service quality and their environmental awareness and pro-environmental behavior impact purchase intention and customer loyalty toward eco-friendly fashion products among Vietnamese Gen Z's. Most interviewees acknowledged that their primary source of knowledge for eco-friendly fashion was social media. The qualitative results further show that the knowledge and attitude toward eco-friendly fashion practices are insufficient to convince young customers to afford eco-friendly fashion products. The quantitative results show that while customer-related factors play a more significant role in stimulating purchase intention, only product-service quality factors impact loyalty. Hence, the study suggests that businesses should prioritize improving service and product quality rather than funding green marketing when targeting the Vietnamese Gen Z. Government should prioritize financial and technological support for fashion firms to develop high-quality eco-friendly fashion to ensure the availability of products in the market.

Forecast: Leather Apparel Market Size Value in the UK 2022 - 2026 Discover more data with ReportLinker!

Leather-Based or Leather Apparel Market Size Value in Greece, 2022 Discover more data with ReportLinker!

Context

The Customer Shopping Preferences Dataset offers valuable insights into consumer behavior and purchasing patterns. Understanding customer preferences and trends is critical for businesses to tailor their products, marketing strategies, and overall customer experience. This dataset captures a wide range of customer attributes including age, gender, purchase history, preferred payment methods, frequency of purchases, and more. Analyzing this data can help businesses make informed decisions, optimize product offerings, and enhance customer satisfaction. The dataset stands as a valuable resource for businesses aiming to align their strategies with customer needs and preferences. It's important to note that this dataset is a Synthetic Dataset Created for Beginners to learn more about Data Analysis and Machine Learning.

Content

This dataset encompasses various features related to customer shopping preferences, gathering essential information for businesses seeking to enhance their understanding of their customer base. The features include customer age, gender, purchase amount, preferred payment methods, frequency of purchases, and feedback ratings. Additionally, data on the type of items purchased, shopping frequency, preferred shopping seasons, and interactions with promotional offers is included. With a collection of 3900 records, this dataset serves as a foundation for businesses looking to apply data-driven insights for better decision-making and customer-centric strategies.

Dataset Glossary (Column-wise)

• Customer ID - Unique identifier for each customer
• Age - Age of the customer
• Gender - Gender of the customer (Male/Female)
• Item Purchased - The item purchased by the customer
• Category - Category of the item purchased
• Purchase Amount (USD) - The amount of the purchase in USD
• Location - Location where the purchase was made
• Size - Size of the purchased item
• Color - Color of the purchased item
• Season - Season during which the purchase was made
• Review Rating - Rating given by the customer for the purchased item
• Subscription Status - Indicates if the customer has a subscription (Yes/No)
• Shipping Type - Type of shipping chosen by the customer
• Discount Applied - Indicates if a discount was applied to the purchase (Yes/No)
• Promo Code Used - Indicates if a promo code was used for the purchase (Yes/No)
• Previous Purchases - The total count of transactions concluded by the customer at the store, excluding the ongoing transaction
• Payment Method - Customer's most preferred payment method
• Frequency of Purchases - Frequency at which the customer makes purchases (e.g., Weekly, Fortnightly, Monthly)

Structure of the Dataset

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Acknowledgement

This dataset is a synthetic creation generated using ChatGPT to simulate a realistic customer shopping experience. Its purpose is to provide a platform for beginners and data enthusiasts, allowing them to create, enjoy, practice, and learn from a dataset that mirrors real-world customer shopping behavior. The aim is to foster learning and experimentation in a simulated environment, encouraging a deeper understanding of data analysis and interpretation in the context of consumer preferences and retail scenarios.

Cover Photo by: Freepik

Thumbnail by: Clothing icons created by Flat Icons - Flaticon

A dataset of fashion keywords, including their definitions, synonyms, antonyms, search volume and costs.

Leather Apparel Market Size Value in Germany, 2021 Discover more data with ReportLinker!

Online shopping for customized garments has become the fastest-growing field of the Chinese eBusiness market. Most consumers not only limit themselves to buying standardized garments but also want to buy garments customized to their preferences. This phenomenon has pushed the fashion textile and apparel industry to change its supply chain operations to meet the customization demand. Besides, the fashion textile and apparel industry also want to study how different channel factors will affect consumers' perceived value and further influence consumers' purchasing decisions. We initiated this study and empirically tested more than 200 experienced consumers. This study collaborated with a fashion textile and apparel company that aims to implement customized product lines soon. Based on the perceived value theory and risk management theory, we investigated whether product involvement and channel identification on supply chain design will affects potential customized product consumers' purchasing decisions. The findings reveal that channel recognition affects consumer decisions by having a positive impact on their perceived value. The perceived risk and shopping channel involvement of consumers have a negative impact on their perceived values and channel selections. In addition, product involvement has a moderating effect on the relationship between channel's perceived risk, perceived values, and channel selections as well.