Apparel and Footwear Market - Industry Analysis of Growth, Trends and Forecast to 2021

The market size of the global apparel and footwear industry in 2016 was USD XXX million and is forecast to register a CAGR of X% over the next five years, from 2016 to 2021, to reach a value of USD XXX million.

The market delivered another year of strong growth, despite weakness in key markets, such as Brazil, China and Russia. China’s apparel and footwear industry’s year-on-year growth has slowed down owing to an economic slowdown in the country. This slowdown in China has powered the US industry, indicating its significance in the global market.

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Key Trends
• Most of the growth in the apparel and footwear market is from developing economies, owing to the rising purchasing power among the Asian consumers, where the middle-class segment is expanding. These consumers are starting to view clothes as an extension and expression of their new lifestyle.
• In the United States, the segment of consumers over 55 years of age is growing faster than any other age group – both, in terms of their share of the total population and their expenditure for clothing.
• Worldwide, fashion consumers are becoming more environmentally-conscious.
• Young fashion customers use a number of digital platforms to get information on trends, share experiences, or compare prices. Up to 35% of shoppers indicate that they rely on endorsements on social networks.

Time Series Considered:
• Historic Period: 2012 to 2015
• Forecast Period- 2016 to 2021
• Base Year: 2016
• Forecast Year: 2021

Key Deliverables
• PESTLE Analysis (Overview): Macro market factors pertinent to the region.
• Market Definition: Main, as well as, associated/ancillary components constituting the market.
• Key Findings of the Study: Top headlines about market trends & numbers.

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Market Dynamics:
• Drivers: The key factors driving growth in the market.
• Restraints: Most relevant threats and restraints that hinder the growth of the market.
• Opportunities: Sectors of high-return or quick turnaround on investment.
• Market Concentration: Porter’s 5 Forces Analysis quantified by a comprehensive list of parameters.

Supply Chain Analysis.
• Competition
• Market Share Analysis: Top players in the market (by value and volume)
• Company Profiles: Pertinent details about leading, high growth, and innovation-motivated stakeholders with contact, operations, product/service offerings, financials and strategies & insights.

Research Methodology

The research process adopted for this entire study is a highly structured, two-stage process: size estimation of the review period, and the market engineering for the forecast period of the global, country and segment-level data that leads to the Data Generation Process (DGP) for the studied variables.

The size estimations are carried out through multiple bottom-up & top-down approaches. The bottom-up approach includes the examining of historical revenues of key players, studying the size of the applications, value and supply-chain analysis and end-user demand, which are then cross-validated by secondary and primary resources.

The top-down approach is an astute research process, where the global market sizing is carried out through the secondary research, validated by primary industry experts. In this report, for analyzing the future trends for the studied market during the forecast period, we have incorporated rigorous statistical and econometric methods, further scrutinized by secondary, primary sources and by our in-house experts, supported through our extensive data intelligence repository.

The market is studied holistically from both demand and supply-side perspectives. This is carried out to analyze both, end-user and producer behavior patterns, in the review period, which affect price, demand and consumption trends. As the study demands analyzing the long-term nature of the market, the identification of factors influencing the market is based on the fundamentality of the study market. Through secondary and primary research, endogenous & exogenous factors are identified and are transformed to quantitative data through data extraction, and further applied for inferential purposes.

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