{"title":"Study on the Choice of Marine Leading Industries in Guangdong Province","authors":"Junjie Wang, Jian-hua Xiao","doi":"10.2991/febm-19.2019.19","DOIUrl":null,"url":null,"abstract":"Firstly, the cumulative method is used as the evaluation criterion, secondly, the structural deviation component and competitive deviation component in Esteban model are used as the evaluation index, and then the weight of each index is calculated by the entropy method for comprehensive evaluation. Finally, according to the principle that the comprehensive score is greater than 0.083, the leading marine industries in Guangdong Province are determined. This study provides a reference for the development of marine industry in Guangdong Province. Keywords—marine leading industry; Esteban model of dynamic deviation share; location entropy In 2018, the added value of the primary, secondary and tertiary industries of the marine industry in Guangdong Province was 32.85 billion yuan, 716.99 billion yuan and 1,182.75 billion yuan respectively. The marine leading industry is an industry that occupies an important proportion in the overall marine economy, has strong industrial linkages, has a fast growth rate, has a strong driving effect on the development of industries, and is in a dominant position in the industrial system. How to rationally choose the marine leading industry is an urgent problem to be solved. Wang Yujia used the SSM method to select the marine industry in Guangdong Province.[1] Yuxuan used SSM and location entropy to evaluate the marine industry. However, scholars have not noticed the insufficiency of SSM methods and data processing problems.[2] In this study, the resource allocation component is introduced in the SSM model, the dynamic SSM method is used to process the marine industry output value, and the cumulative method is used to determine the marine leading industry selection benchmark.[3] Therefore, the marine leading industry in Guangdong Province can be more accurately determined.","PeriodicalId":417272,"journal":{"name":"Proceedings of the Fourth International Conference on Economic and Business Management (FEBM 2019)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth International Conference on Economic and Business Management (FEBM 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/febm-19.2019.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Firstly, the cumulative method is used as the evaluation criterion, secondly, the structural deviation component and competitive deviation component in Esteban model are used as the evaluation index, and then the weight of each index is calculated by the entropy method for comprehensive evaluation. Finally, according to the principle that the comprehensive score is greater than 0.083, the leading marine industries in Guangdong Province are determined. This study provides a reference for the development of marine industry in Guangdong Province. Keywords—marine leading industry; Esteban model of dynamic deviation share; location entropy In 2018, the added value of the primary, secondary and tertiary industries of the marine industry in Guangdong Province was 32.85 billion yuan, 716.99 billion yuan and 1,182.75 billion yuan respectively. The marine leading industry is an industry that occupies an important proportion in the overall marine economy, has strong industrial linkages, has a fast growth rate, has a strong driving effect on the development of industries, and is in a dominant position in the industrial system. How to rationally choose the marine leading industry is an urgent problem to be solved. Wang Yujia used the SSM method to select the marine industry in Guangdong Province.[1] Yuxuan used SSM and location entropy to evaluate the marine industry. However, scholars have not noticed the insufficiency of SSM methods and data processing problems.[2] In this study, the resource allocation component is introduced in the SSM model, the dynamic SSM method is used to process the marine industry output value, and the cumulative method is used to determine the marine leading industry selection benchmark.[3] Therefore, the marine leading industry in Guangdong Province can be more accurately determined.