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Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm

City leading industries are the pillars of urban economic development and are constantly changing as urban economic development enters different stages. The weight setting of many factors in the existing leading industry selection methods and means is mainly set by humans, which is highly subjective...

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Detalles Bibliográficos
Autores principales: Lin, Junhang, Liu, Yong, Tang, Hua, Zeng, Huipeng, Li, Shiyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106485/
https://www.ncbi.nlm.nih.gov/pubmed/35571700
http://dx.doi.org/10.1155/2022/9337569
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author Lin, Junhang
Liu, Yong
Tang, Hua
Zeng, Huipeng
Li, Shiyuan
author_facet Lin, Junhang
Liu, Yong
Tang, Hua
Zeng, Huipeng
Li, Shiyuan
author_sort Lin, Junhang
collection PubMed
description City leading industries are the pillars of urban economic development and are constantly changing as urban economic development enters different stages. The weight setting of many factors in the existing leading industry selection methods and means is mainly set by humans, which is highly subjective and lacks dynamics, integrity, and quantification, and the accuracy of prediction results is not high. Therefore, starting from respecting objective data, the SSM selection method with both dynamic and quantifiable properties is introduced. Based on the SSM mathematical model and principles, 35 manufacturing industries in Guangzhou in 2015 and 2020 are selected as initial variables and stage variables, respectively, taking 35 corresponding industrial sectors in the province as reference variables at the same time point and using the SSM algorithm as an analytical tool to conduct an empirical analysis of the share deviation component, structural deviation component, and competitiveness deviation component of the 35 manufacturing industry sectors in Guangzhou. After drawing the Shift-share analysis chart, it was found that there are 12 industrial sectors most likely to become the city leading industries in Guangzhou, and 4 suggestions for the development planning of city leading industries were put forward; they are, respectively, ➀ accelerate traditional industries technological upgrading, ➁ focus on optimizing automobile manufacturing industry, ➂ promote leading industries independent innovation, and ➃ create leading industry sharing platform.
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spelling pubmed-91064852022-05-14 Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm Lin, Junhang Liu, Yong Tang, Hua Zeng, Huipeng Li, Shiyuan Comput Intell Neurosci Research Article City leading industries are the pillars of urban economic development and are constantly changing as urban economic development enters different stages. The weight setting of many factors in the existing leading industry selection methods and means is mainly set by humans, which is highly subjective and lacks dynamics, integrity, and quantification, and the accuracy of prediction results is not high. Therefore, starting from respecting objective data, the SSM selection method with both dynamic and quantifiable properties is introduced. Based on the SSM mathematical model and principles, 35 manufacturing industries in Guangzhou in 2015 and 2020 are selected as initial variables and stage variables, respectively, taking 35 corresponding industrial sectors in the province as reference variables at the same time point and using the SSM algorithm as an analytical tool to conduct an empirical analysis of the share deviation component, structural deviation component, and competitiveness deviation component of the 35 manufacturing industry sectors in Guangzhou. After drawing the Shift-share analysis chart, it was found that there are 12 industrial sectors most likely to become the city leading industries in Guangzhou, and 4 suggestions for the development planning of city leading industries were put forward; they are, respectively, ➀ accelerate traditional industries technological upgrading, ➁ focus on optimizing automobile manufacturing industry, ➂ promote leading industries independent innovation, and ➃ create leading industry sharing platform. Hindawi 2022-05-06 /pmc/articles/PMC9106485/ /pubmed/35571700 http://dx.doi.org/10.1155/2022/9337569 Text en Copyright © 2022 Junhang Lin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lin, Junhang
Liu, Yong
Tang, Hua
Zeng, Huipeng
Li, Shiyuan
Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title_full Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title_fullStr Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title_full_unstemmed Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title_short Empirical Analysis and Suggestions on the Selection of City Leading Industries based on SSM Algorithm
title_sort empirical analysis and suggestions on the selection of city leading industries based on ssm algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106485/
https://www.ncbi.nlm.nih.gov/pubmed/35571700
http://dx.doi.org/10.1155/2022/9337569
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