Brief Introduction to Product Quality Supervision and Sampling Inspection Data by the State Administration for Market Regulation
Product quality supervision sampling inspection is a national supervisory activity conducted by national and local product quality supervision departments. It involves periodically drawing samples from the circulation field according to product quality supervision plans, inspecting the quality status of sampled enterprises and their products, releasing inspection bulletins on schedule, and implementing corresponding disciplinary measures against enterprises with unqualified products.
With China's rapid economic development and people's pursuit of high-quality living, product safety has garnered widespread attention. Quality supervision sampling inspection serves as an effective approach to control product quality. This mechanism holds three main significances:
- Advocating a Correct View of Quality. Quality reflects national culture and civic literacy, while directly impacting economic benefits.
- Establishing a Long-term Mechanism for Combating Counterfeits. Inspection results are publicly disclosed through media to strengthen exposure of substandard enterprises and operators. Strict rectification systems are enforced, with stricter penalties imposed on enterprises failing re-inspections.
- Enhancing International Competitiveness. As the world's second-largest economy and top exporter, China aims to break through international trade quality barriers by building a "quality highland" for export products.
The CnOpenData platform aggregates product quality supervision sampling inspection data from 32 provinces/municipalities and 2 special administrative regions released by the State Administration for Market Regulation, providing foundational support for researching China's dynamic product quality status and living standards.
Time Coverage
2017.09-2023.12
Field Description
Sample Data
Relevant Literature
- Liu Xiaolu and Li Honglin, 2015: "Ownership Bias in Product Quality Regulation," Economic Research Journal, No.7.
Data Update Frequency
Annual Update