4.7 Article

Estimating the efficiency of complex marine systems in China's coastal regions using a network Data Envelope Analysis model

期刊

OCEAN & COASTAL MANAGEMENT
卷 139, 期 -, 页码 77-91

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ocecoaman.2017.02.005

关键词

Efficiency calculation; Marine complex system; Network DEA; Coastal China

资金

  1. Ministry of Education (MOE) Project of Key Research Institutes Of Humanities and Social Sciences in Universities [16JJD790021]
  2. Chinese National Natural Science Foundation [41671119]

向作者/读者索取更多资源

Marine economies have become the hotspot, while coastal social and ecological problems are gaining increasing attention worldwide. Previous studies have focused on the economic, social, and ecological efficiency of single and dual systems in a composite system, thus ignoring the impact of other subsystems. Drawing on the theory of system, this study constructs a ring structure of a coniplex marine system and then selects a corresponding decision-making unit on the basis of labor and capital circulation in each subsystem to calculate the efficiency of the chain structure using a network Data Envelope Analysis (DEA) model. The results revealed that while social-ecological-economic efficiency increased, social-economic-ecological and ecological-social-economic efficiencies remained stable. By contrast, economic-social-ecological and ecological-economic-social efficiencies showed a downward trend, whereas economic-ecological-social efficiency demonstrated varying changes. The overall efficiency of the chain is highly similar to that in the first stage, although there are differences in numerical values. The study also demonstrates that the network DEA results based on the theory of system do not deny those of previous studies, but contribute to the accuracy of efficiency calculation. The differences between the overall efficiency and that in the first stage indicate that previous studies have underestimated socioeconomic and socioecological efficiencies but overestimated ecological efficiency. (C) 2017 Elsevier Ltd. All rights reserved.

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