Evaluating Fishing Capacity Based on DEA and Regression Analysis of China’s Offshore Fishery

• Published in: Journal of marine science and engineering 2021-12, Vol.9 (12), p.1402
• Main Authors: Liu, Shuang, Sun, Jia-Xin, Lyu, Chao, Chu, Ta-Jen, Zhang, He-Xu
• Format: Article
• Language: English
• Subjects: Algorithms; Annual; China offshore; Commercial fishing; Data envelopment analysis; data envelopment method; Efficiency; Evaluation; Fisheries; Fisheries management; Fishers; Fishery data; Fishery resources; Fishing; Fishing capacity; Fishing vessels; Forecasting; Goodness of fit; Learning algorithms; Linear programming; Machine learning; machine learning algorithm; Management decisions; Marine conservation; Marine fish; Marine fisheries; Mathematical analysis; Methods; Offshore; Polynomials; Regression analysis; Regression models; Statistical analysis; Sustainable development; Vessels
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse9121402

The analysis of offshore fishing capacity is of great significance and practical value to the sustainable utilization and conservation of marine fishery resources. Based on the 2004–2020 China Fishery Statistical Yearbook, data envelopment analysis (DEA) was applied for measuring fishing capacity using a number of fishing vessels, total power, total tonnage, and the number of professional fishermen as the input measures and the annual catch as the output measure. Capacity utilization had a calculated range from 80.7 to 100%, and its average is 93.5%. In the first four years of 2003–2007, the excess investment rate of fishing vessels, total tonnage, total power, and fishermen was low (