Article: Supply chain information sharing and collaborative innovation based on social network analysis Journal: International Journal of Information Technology and Management (IJITM) 2026 Vol.25 No.1 pp.46 - 60 Abstract: In order to improve the completeness of supply chain information sharing and shorten the sharing time, a supply chain information sharing and collaborative innovation method based on social network analysis is proposed. Firstly, through dynamic programming and cost function optimisation, the optimal cluster of supply chain information is divided. Secondly, generate anonymous sequences of supply chain information through social network analysis and dynamic grouping strategies. Once again, establish a node reputation evaluation system that combines direct and indirect reputation to achieve secure sharing of supply chain information. Ultimately, leveraging social network analysis, the supply chain's information sharing mechanism is refined, fostering synergistic collaboration between resources and competencies. Additionally, network governance structures are crafted to enhance collaborative innovation within the supply chain. Empirical outcomes reveal that the proposed approach in this study achieves a 0.97 completeness rate for supply chain information sharing, concurrently reducing the duration required for information dissemination. Inderscience Publishers - linking academia, business and industry through research

Title: Supply chain information sharing and collaborative innovation based on social network analysis

Authors: Yiming Shen; Jingyi Qiu; Jie Mei; Xin Sun; Luyao Qu

Addresses: State Grid Jiangsu Tendering Co., Ltd., Nanjing, 210036, China ' State Grid Jiangsu Tendering Co., Ltd., Nanjing, 210036, China ' State Grid Jiangsu Tendering Co., Ltd., Nanjing, 210036, China ' State Grid Jiangsu Tendering Co., Ltd., Nanjing, 210036, China ' State Grid Jiangsu Tendering Co., Ltd., Nanjing, 210036, China

Abstract: In order to improve the completeness of supply chain information sharing and shorten the sharing time, a supply chain information sharing and collaborative innovation method based on social network analysis is proposed. Firstly, through dynamic programming and cost function optimisation, the optimal cluster of supply chain information is divided. Secondly, generate anonymous sequences of supply chain information through social network analysis and dynamic grouping strategies. Once again, establish a node reputation evaluation system that combines direct and indirect reputation to achieve secure sharing of supply chain information. Ultimately, leveraging social network analysis, the supply chain's information sharing mechanism is refined, fostering synergistic collaboration between resources and competencies. Additionally, network governance structures are crafted to enhance collaborative innovation within the supply chain. Empirical outcomes reveal that the proposed approach in this study achieves a 0.97 completeness rate for supply chain information sharing, concurrently reducing the duration required for information dissemination.

Keywords: social network analysis; SNA; supply chain; information sharing; collaborative innovation.

DOI: 10.1504/IJITM.2026.152450

International Journal of Information Technology and Management, 2026 Vol.25 No.1, pp.46 - 60

Received: 30 Jul 2024
Accepted: 07 Feb 2025
Published online: 20 Mar 2026 *

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Title: Supply chain information sharing and collaborative innovation based on social network analysis

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