Link-Based Methodology for Industrial Structure Analysis: A Case Study of the Korean Transportation Logistics Industryopen access
- Authors
- Song, Ki-Han; Lee, Ha-Jeong; Suh, Wonho; Elkosantini, Sabeur; Lee, Seongkwan Mark
- Issue Date
- Jul-2025
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Keywords
- link-centric approach; network analysis; node centrality; transportation and logistics industry ecosystem
- Citation
- Applied Sciences (Switzerland), v.15, no.14, pp 1 - 15
- Pages
- 15
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences (Switzerland)
- Volume
- 15
- Number
- 14
- Start Page
- 1
- End Page
- 15
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/126286
- DOI
- 10.3390/app15147685
- ISSN
- 2076-3417
2076-3417
- Abstract
- We present a link-centric methodology for analyzing the formation of networks in the transportation and logistics industry, advancing beyond prior research based primarily on node centrality. We graphically represent the input–output table (I/O table) indicating inter-industry transactions and propose a methodology for identifying critical factors and major industries within the transportation and logistics industry by assuming the inter-industry transaction volume as the length of a link and analyzing the shortest distance between industries. Through this, we analyze the change factors within an industry and the significance of related industries. The connectivity between industries within transportation and logistics is evaluated based on the shortest distance, and the primary, secondary, and tertiary industries are classified through cluster analysis of the evaluation results. Based on an analysis of Korea’s input–output table, we derived potential industries linked to the transportation and logistics industry that were previously not identified in the results of existing node centrality indices. Additionally, our findings demonstrate that link-based network analysis offers a comparative advantage over node centrality analysis in examining the network structure of the transportation and logistics industry. We propose a new approach to understanding industrial ecosystems by presenting a methodology for industrial structure analysis based on links rather than nodes. © 2025 by the authors.
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