Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)

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Research on the Design and Analysis of the Improved Algorithm for Industrial Linkage Based on Input-Output Technology

Authors
Shi Wang1, 2, 3, *, Norriza Hussin1, *, Jing Yang2, 3
1Faculty of Engineering, Built Environment and Information Technology, SEGi University, Kota Damansara, 47810, Malaysia
2Hainan Vocational University of Science and Technology, Haikou, 571126, China
3Hainan Free Trade Port Key Laboratory of International Shipping Development and Real Right Digitization, Haikou, 571126, China
*Corresponding author. Email: ws10121@126.com
*Corresponding author. Email: norriza@segi.edu.my
Corresponding Authors
Shi Wang, Norriza Hussin
Available Online 4 December 2023.
DOI
10.2991/978-94-6463-304-7_22How to use a DOI?
Keywords
Input-output technology; Improved algorithm; Industrial linkage; Hainan Free Trade Port
Abstract

The general measurement method of industrial linkage adopts the influence coefficient and the sensitivity coefficient to measure, and this method ignores the influence of the product structure of the current year when measuring the coefficient. In order to solve this problem, this research takes the Hainan Free Trade Port industry as an example, based on the input-output table of 42 sectors in the Hainan Free Trade Port in 2017, proposes an improved algorithm for measuring the degree of industrial linkage, derives the industrial influence coefficient and the sensitivity coefficient, and classifies and discusses the 42 industrial sectors in the Hainan Free Trade Port according to the relevant indices, evaluates the overall industrial linkage of the Hainan Free Trade Port and analyses the relationship between radiation and constraints of each industry. and analyses the relationship between the radiation and constraints of each industry. The conclusions drawn by the improved algorithm are more in line with reality, and the research results provide a theoretical basis for the adjustment and optimization of the industrial structure of the Hainan Free Trade Port. The empirical analysis results show that the improved algorithm for industrial linkage has the advantages of simple implementation and accurate calculation, and it is an effective method for analyzing industrial linkage.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
4 December 2023
ISBN
10.2991/978-94-6463-304-7_22
ISSN
2589-4900
DOI
10.2991/978-94-6463-304-7_22How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shi Wang
AU  - Norriza Hussin
AU  - Jing Yang
PY  - 2023
DA  - 2023/12/04
TI  - Research on the Design and Analysis of the Improved Algorithm for Industrial Linkage Based on Input-Output Technology
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 204
EP  - 213
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_22
DO  - 10.2991/978-94-6463-304-7_22
ID  - Wang2023
ER  -