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...

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...

China Garment & Apparel: Industrial Sales Value: Delivery Value for Export: Year to Date data was reported at 375,787.380 RMB mn in Dec 2018. This records an increase from the previous number of 348,432.210 RMB mn for Nov 2018. China Garment & Apparel: Industrial Sales Value: Delivery Value for Export: Year to Date data is updated monthly, averaging 235,719.050 RMB mn from Jan 2012 (Median) to Dec 2018, with 84 observations. The data reached an all-time high of 516,773.050 RMB mn in Dec 2014 and a record low of 52,955.220 RMB mn in Feb 2018. China Garment & Apparel: Industrial Sales Value: Delivery Value for Export: Year to Date data remains active status in CEIC and is reported by China Textile Industry Association. The data is categorized under China Premium Database’s Textile Sector – Table CN.RSC: Textile Industry: Garment and Apparel.

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

UNIDO pub. Report on global level development of clothing industry value chain and its upgrading effects on developing countries - covers (1) transformations in production, trade and entrepreneurial strategies in the clothing industry during past decades (2) the global value chain: types of international economic networks, 'producer driven' and 'buyer driven' (3) change in global retailing: domination by large organizations and greater product specifications, competition between retailers and manufacturers (4) global sourcing in clothing (apparel) (5) effects of quotas, quota restrictions leading to internationalization (6) European and Japanese variations in clothing (apparel) sourcing networks (7) world market trends. Conclusions. Bibliography. Statistics, diagrams.

Microplastic pollution is one of the emerging global environmental issues. The fashion industry is a major source of microplastic pollution due to the massive consumption of synthetic fibres. Textile, garment, and footwear manufacturing contribute to the microplastic emission into sewage waters. Cities are major contributors to microplastic emissions and the implementers of microplastic control. It is important to compile the inventories of microplastic emissions of the fashion industry for cities, and fewer studies have investigated the inventories of microplastic emissions for key industries in cities. This study, for the first time, compiles microplastic emission inventories of the fashion industry for Chinese cities. The inventories are constructed using 21 cities and 4 production processes of the fashion industry. The socioeconomic data of the fashion industry in cities such as the output of industrial products and the gross output value of the fashion industry are included in the datasets as well. The dataset can provide transparent, comparable, and verifiable data support for the microplastic pollution prevention and control strategies in the fashion industry, and provide references for the construction of microplastic emission inventories for other key industries.

India GVA: Industry: Mfg: Textiles, Apparel & Leather Products data was reported at 3,215,702.525 INR mn in 2018. This records an increase from the previous number of 3,062,192.148 INR mn for 2017. India GVA: Industry: Mfg: Textiles, Apparel & Leather Products data is updated yearly, averaging 1,545,142.627 INR mn from Mar 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 3,215,702.525 INR mn in 2018 and a record low of 577,700.000 INR mn in 2005. India GVA: Industry: Mfg: Textiles, Apparel & Leather Products data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.AB003: NAS 2011-2012: Gross Value Added: by Industry: Current Price.

Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.

With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.

Why Choose Success.ai’s Ecommerce Store Data?

1. Verified Profiles for Precision Engagement

   • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.

2. Comprehensive Coverage of the APAC E-commerce Sector

   • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
   • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.

3. Continuously Updated Datasets

   • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
   • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.

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: Access business profiles for e-commerce professionals and organizations across APAC.
• Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
• Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
• Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

Key Features of the Dataset:

1. Comprehensive E-commerce Business Profiles

   • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
   • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.

2. Advanced Filters for Precision Campaigns

   • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
   • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.

3. Regional and Sector-specific Insights

   • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
   • Refine your marketing strategies and outreach efforts to align with market priorities.

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 Outreach

   • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
   • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.

3. Market Research and Competitive Analysis

   • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
   • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...

Snapshot img

Print On Demand Market Size 2025-2029

The print on demand market size is forecast to increase by USD 25.36 billion, at a CAGR of 25.6% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing popularity of customized merchandise as a branding tool. Businesses are leveraging print on demand services to create unique, personalized products, particularly in the apparel sector, where custom T-shirts are leading the charge. This trend is further fueled by the seamless integration of print on demand services with e-commerce platforms, enabling businesses to reach a wider customer base and streamline their operations. However, the market is not without challenges. The dynamic pricing of raw materials poses a significant obstacle for businesses, as fluctuations in the cost of essential inputs can significantly impact profitability.
Moreover, ensuring consistent quality across various orders and maintaining a steady supply chain are ongoing challenges that require careful attention and strategic planning. To capitalize on the opportunities presented by this market and navigate these challenges effectively, companies must stay agile, invest in advanced technology, and build strong relationships with their suppliers.

What will be the Size of the Print On Demand Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by shifting consumer preferences and advancements in technology. This dynamic industry caters to various sectors, including home decor, personalized products, and custom apparel. The ongoing unfolding of market activities is characterized by continuous improvements in printing quality and customer service. Production costs and lead times are subject to change as new technologies emerge, such as digital and sublimation printing. Customer lifetime value and environmental impact are increasingly important considerations for businesses in this market. Ethical sourcing and sustainable practices are gaining traction, as are marketing and advertising strategies that leverage email marketing and social media.

Heat transfer printing and phone case production remain popular applications, with a focus on color accuracy and customer satisfaction. On-demand printing enables businesses to offer a wide range of products, from canvas prints to white-label items, without holding inventory. E-commerce integration and order management systems streamline operations, while graphic design services and product photography help businesses create compelling offerings. Fulfillment services and inventory management systems ensure timely delivery, enhancing customer experience. Pricing strategies continue to evolve, with businesses leveraging pay-per-click (PPC) advertising and returns and exchanges policies to optimize revenue. Print resolution and file formats are crucial factors in maintaining high-quality output, while color profiles and shipping and logistics are essential components of a successful business model.

The print-on-demand landscape is constantly evolving, with new trends and applications emerging as consumer demands and technological advancements shape the industry.

How is this Print On Demand Industry segmented?

The print on demand industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.PlatformSoftwareServiceProductApparelHome decorDrinkwareOthersChannelD2CMarketplaceGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaEgyptKSAOmanUAEAPACChinaIndiaJapanSouth AmericaArgentinaBrazilRest of World (ROW)

By Platform Insights

The software segment is estimated to witness significant growth during the forecast period.

Print on demand software, including platforms like Printful, Spocket, and Gooten, offers businesses access to essential printing tools via a cloud network or on-premises setup. The globalization trend and expanding reach of IT, BFSI, and retail sectors necessitate a centralized system for managing print operations. The cloud facilitates access to extensive data sets, thereby reducing capital expenditure (CAPEX) for businesses. Print quality and customer service are crucial factors driving the adoption of print on demand solutions. Production costs and lead times are significantly reduced through digital printing technologies, such as sublimation and direct-to-garment printing. Canvas prints, home decor, and personalized products are popular offerings in this market.

E-commerce integration, white-label products, and order management systems enable seamless selling of print products online. Ethical sourcing and environmental impact are growi

Under Armour is an American sporting goods manufacturer, based in Baltimore, Maryland. The company has experienced substantial growth over the past decade, with its global net revenues amounting to approximately 5.7 billion U.S. dollars in the financial year ended March 31, 2024. Under Armour had revenues of less than one billion U.S. dollars as recently as 2009. The majority of Under Armour’s sales come from apparel, with the remainder coming from footwear and sporting equipment, and accessories. How does Under Armour compare to other companies within the sportswear and sporting goods industry? The global sportswear industry is a lucrative sector, which is forecast to keep expanding in the coming years. Nike and adidas are two of the world's leading athletic apparel companies and their brand values are on another level. Despite Under Armour being one of the largest sportswear and sporting goods manufacturers in the world, the company is still far behind these two industry giants. Puma, on the other hand, is a much closer competitor to UA and is possibly a better benchmark of where Under Armour currently stands within this industry. In 2022, the German sportswear company generated approximately 8.46 billion euros' worth of net sales.

In the financial year ended March 31, 2024, apparel sales accounted for the largest share of Under Armour’s worldwide revenue, accounting for approximately 66.5 percent of net sales. In the same year, footwear accounted for about a quarter of net sales. Footwear sales setting the pace Under Armour’s footwear segment sales rose sharply between 2015 and 2016, increasing by 333 million U.S. dollars worldwide, pushing annual revenue from this product category to more than one billion U.S. dollars for the first time. A similar evolution was recorded between the fiscal years of 2020 and 2021: while UA's shoe sales had dropped to below the billion dollar mark as a result of interruptions caused by the coronavirus pandemic, the company bounced back and set a new record for itself in 2021, at approximately 1.25 billion U.S. dollars' worth of global footwear sales. This number increased to a record 1.45 billion in 2023. The brand’s footwear line covers a wide range of sports and activities, but running shoes take the lead in terms of sales. Understanding the customers’ needs and wants Increasing sales from both its footwear and apparel units resulted in Under Armour’s global net sales exceeding five billion U.S. dollars for the first time in 2018. The company succeeded by responding to shifts in consumer preferences: a growing interest in performance products and the acknowledgement of the benefits of an active lifestyle. When Under Armour first launched in 1996, it focused on compression shirts for men, but the company has since expanded its reach to focus on athletic apparel needs of female athletes, women in general, as well as young people.

United States GDP: VA: PI: PI: Mfg: NG: Apparel, Leather & Allied Pdts data was reported at 101.847 2005=100 in 2011. This records an increase from the previous number of 99.924 2005=100 for 2010. United States GDP: VA: PI: PI: Mfg: NG: Apparel, Leather & Allied Pdts data is updated yearly, averaging 99.924 2005=100 from Dec 1977 (Median) to 2011, with 35 observations. The data reached an all-time high of 112.737 2005=100 in 1999 and a record low of 67.791 2005=100 in 1977. United States GDP: VA: PI: PI: Mfg: NG: Apparel, Leather & Allied Pdts data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A119: NIPA 2009: GDP by Industry: Value Added: Price Index.

United States GDP: VA: PI: Mfg: NG: Apparel, Leather & Allied Pdts data was reported at 11.800 USD bn in 2011. This stayed constant from the previous number of 11.800 USD bn for 2010. United States GDP: VA: PI: Mfg: NG: Apparel, Leather & Allied Pdts data is updated yearly, averaging 21.400 USD bn from Dec 1977 (Median) to 2011, with 35 observations. The data reached an all-time high of 27.700 USD bn in 1994 and a record low of 11.800 USD bn in 2011. United States GDP: VA: PI: Mfg: NG: Apparel, Leather & Allied Pdts data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A116: NIPA 2009: GDP by Industry: Value Added: Current Price.

This statistic depicts the sales of the H&M Group worldwide from 2006 to 2024. In the fiscal year 2024, global net sales of the H&M Group amounted to about 234 billion Swedish kronor. H&MH&M offers a broad and varied range of fashion including collections for women, men, teenagers and children. The range also includes sportswear, underwear, shoes, accessories and cosmetics, as well as home textiles and decorations from H&M Home.Germany is H&M's largest market. In 2024, over 35 billion Swedish kronor were generated from that country alone. The company operates roughly 4,253 stores worldwide and employs approximately 97,710 people. H&M dropped out of the top ten most valuable apparel brands in the world as of 2023.H&M aims to be a more sustainable choice for today’s increasingly aware customers. To this end, H&M’s investments in social improvements and reduced environmental impact extend throughout the product life cycle – from responsible use of natural resources to ensuring good working conditions at suppliers’ factories. Sustainability work is thoroughly integrated into the business, not only because it is an investment in the customer offering,but also because it is vital to the group’s long-term growth and development. However, there have been questions raised as to how effective and trustworthy H&M's sustainability practices really are.

In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

United States GDP: VA: 2005p: PI: Mfg: NG: Apparel, Leather & Allied Pdts data was reported at 11.600 USD bn in 2011. This records a decrease from the previous number of 11.800 USD bn for 2010. United States GDP: VA: 2005p: PI: Mfg: NG: Apparel, Leather & Allied Pdts data is updated yearly, averaging 19.600 USD bn from Dec 1987 (Median) to 2011, with 25 observations. The data reached an all-time high of 26.600 USD bn in 1992 and a record low of 11.600 USD bn in 2011. United States GDP: VA: 2005p: PI: Mfg: NG: Apparel, Leather & Allied Pdts data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A117: NIPA 2009: GDP by Industry: Value Added: 2005 Price: Chain Linked.

United States GDP: VA: PI: Pvt: Mfg: NG: Apparel, Leather & Allied Pdts data was reported at 105.970 2009=100 in 2017. This records a decrease from the previous number of 107.902 2009=100 for 2016. United States GDP: VA: PI: Pvt: Mfg: NG: Apparel, Leather & Allied Pdts data is updated yearly, averaging 105.970 2009=100 from Dec 1997 (Median) to 2017, with 21 observations. The data reached an all-time high of 115.148 2009=100 in 1999 and a record low of 97.231 2009=100 in 2010. United States GDP: VA: PI: Pvt: Mfg: NG: Apparel, Leather & Allied Pdts data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A035: NIPA 2013: GDP by Industry: Annual: Value Added: Price Index.

Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data was reported at -0.330 EUR mn in 2023. This records a decrease from the previous number of -0.190 EUR mn for 2022. Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data is updated yearly, averaging -0.270 EUR mn from Dec 2006 (Median) to 2023, with 16 observations. The data reached an all-time high of 1.050 EUR mn in 2020 and a record low of -2.870 EUR mn in 2014. Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Lithuania LT: Foreign Direct Investment Income: Inward: Total: Manufacture of Textiles and Wearing Apparel data was reported at 17.110 EUR mn in 2023. This records a decrease from the previous number of 18.310 EUR mn for 2022. Lithuania LT: Foreign Direct Investment Income: Inward: Total: Manufacture of Textiles and Wearing Apparel data is updated yearly, averaging 16.540 EUR mn from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 19.470 EUR mn in 2021 and a record low of 4.640 EUR mn in 2008. Lithuania LT: Foreign Direct Investment Income: Inward: Total: Manufacture of Textiles and Wearing Apparel data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

LU: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data was reported at 70.000 EUR mn in 2023. This stayed constant from the previous number of 70.000 EUR mn for 2022. LU: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data is updated yearly, averaging 70.000 EUR mn from Dec 2012 (Median) to 2023, with 11 observations. The data reached an all-time high of 124.000 EUR mn in 2017 and a record low of 24.000 EUR mn in 2013. LU: Foreign Direct Investment Income: Outward: Total: Manufacture of Textiles and Wearing Apparel data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Luxembourg – Table LU.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market value, Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered. Collective investment institutions are not covered as direct investment enterprises. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions and positions are allocated according to the activity of the resident direct investor. Statistical unit: Enterprise.