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Managing the offshore and coastal fisheries in Taiwan to achieve sustainable development using policy indicators

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  • Liu, Wen-Hong

Abstract

This study establishes an offshore and coastal fisheries policy indicator system to evaluate the performance of policies to achieve sustainable development in offshore and coastal fisheries. A modified Delphi method is used to establish this system, and the weights of indicators are calculated using the analytic hierarchy process (AHP) to aggregate indicators. Results show that ecological policies have not achieved their goals because production and catch per unit effort are decreasing. Indicators with respect to management efficiency have increased after the implementation of the buyback and off-fishing programs. However, net returns indicator, which is affected by increasing cost and production value, is stable. Due to inefficient management resulting from insufficient resources, indicators for the number of illegal fishing cases per year and the number of smuggled aquatic production incidents have increased. This shows that requirement for enhanced compliance is necessary. The objective for cultivating talents in fisheries has not been achieved because average wage for fishers is lower than the average civil wage, resulting in an increase in the hiring of foreign fishers.

Suggested Citation

  • Liu, Wen-Hong, 2013. "Managing the offshore and coastal fisheries in Taiwan to achieve sustainable development using policy indicators," Marine Policy, Elsevier, vol. 39(C), pages 162-171.
  • Handle: RePEc:eee:marpol:v:39:y:2013:i:c:p:162-171
    DOI: 10.1016/j.marpol.2012.11.001
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    Cited by:

    1. Read, Andrew D. & West, Ronald J. & Kelaher, Brendan P., 2015. "Using compliance data to improve marine protected area management," Marine Policy, Elsevier, vol. 60(C), pages 119-127.
    2. Anissa Frini & Sarah Benamor, 2018. "Making Decisions in a Sustainable Development Context: A State-of-the-Art Survey and Proposal of a Multi-period Single Synthesizing Criterion Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 341-385, August.

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