Recently, the Social Responsibility Office of China National Textile and Apparel Council (China Textile Federation) held a research meeting on the sustainable development of China's textile and garment industry clusters in China Textile City (Keqiao District, Shaoxing City). The "Smart Governance to Promote the Sustainable Development of Industrial Clusters" project based on textile big data was initiated by the China Textile Federation. As the "Asia's largest professional textile fabric market", China Textile City is the first pilot industrial cluster in the industry. 

At the research meeting, Yan Yan, deputy director of the China Textile Information Center and deputy director of the China Textile Federation Social Responsibility Office, introduced the development goals and key tasks of the 13th Five-Year Plan of the industry, and emphasized the use of big data as a strategic resource to promote industrial smart governance and sustainable development. On the basis of summarizing the important achievements of the industrial cluster index work, Liu Hui, deputy director of the responsibility office of the China Textile Federation, analyzed the innovation of the research on the sustainable development index system. Zhang Juan, an assistant researcher at the Responsible Office of China Textile Federation, introduced the research progress and significance of the sustainable development index system in detail.

The research meeting was presided over by Wei Yinan, Director of Index Office of China Textile City Construction Management Committee, and Shou Lumin, Deputy Director of China Textile City Construction Management Committee, attended the meeting and delivered a speech, from the Investment Promotion Office, Index Office and other departments of China Textile City Construction Management Committee More than 40 people including representatives and Keqiao index collectors attended the meeting and had active exchanges.
 
Project introduction: How does big data promote innovation and sustainable development of textile industry cluster governance?
At the beginning of 2016, the Social Responsibility Office of China National Textile and Apparel Council, based on the five development concepts of innovation, coordination, green, openness and sharing, and based on the industry's 13th Five-Year Development Plan, built a Chinese textile and garment industry cluster based on industrial big data. Sustainable Development Indicator System. The sustainable development indicator system includes five first-level indicators, 13 second-level indicators and 35 third-level indicators, namely "three innovations", collaboration, ecological civilization, openness and sharing.
The index system of sustainable development of industrial clusters will be extended on the basis of the original statistical calibers of textile industry, textile and apparel industry, and fiber manufacturing industry, and the research scope will be expanded to all formats such as textile industry and textile wholesale and retail industry. A full number of market entities such as industrial and commercial households are included in the research scope to more comprehensively analyze the development status, driving forces, opportunities and challenges of the industry, and make predictions about future trends.
Comprehensive and authoritative big data is the basic guarantee for textile industry research. The research on the sustainable development index system of China's textile and garment industry strictly abides by the "Regulations on the Disclosure of Government Information of the People's Republic of China", makes full use of the current government open data such as industry and commerce, patents, trademarks, statistics and the open data of the textile industry e-commerce platform, using more than 6 million records Market subject data and more than 90 analysis models, multi-dimensional, comprehensive and accurate analysis and judgment of the vitality and innovation of industry market players, providing information services and decision-making support for cluster investment attraction, corporate investment site selection, etc.