Impact of Network Structures and Deep Learning on Financial Performance in Buyer-Supplier Networks

This study investigates the impact of network capabilities and deep learning techniques on companies' financial performance within buyer-supplier networks. It broadens the scope by incorporating network measures such as closeness and network constraint, whereas previous studies have primarily focused on suitable buyer-supplier relationships. The analysis evaluates the effects of these network measures on companies' financial performance metrics, including asset growth rate, return on assets, and more. In addition, this study explores the impact of extended networks on company performance using deep learning techniques. The results show that companies' network capabilities are positively associated with their financial performance, highlighting the critical role of network positions in driving success. Furthermore, the findings suggest that extending the network through deep learning offers significant benefits for companies.

Authors

Institutions

Publication Details

Journal
Journal of Global Information Management
Published
2025-03-08
DOI
https://doi.org/10.4018/jgim.370963
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Network Structures and Deep Learning on Financial Performance in Buyer-Supplier Networks

J S Kim, Seokwoo Song, Donghun Lee, Jae-Gon Kim et al.
Journal of Global Information Management
Supply Chain and Inventory Management
article

Impact of Network Structures and Deep Learning on Financial Performance in Buyer-Supplier Networks

J S Kim, Seokwoo Song, Donghun Lee, Jae-Gon Kim, Kwanho Kim
article en

Abstract

This study investigates the impact of network capabilities and deep learning techniques on companies' financial performance within buyer-supplier networks. It broadens the scope by incorporating network measures such as closeness and network constraint, whereas previous studies have primarily focused on suitable buyer-supplier relationships. The analysis evaluates the effects of these network measures on companies' financial performance metrics, including asset growth rate, return on assets, and more. In addition, this study explores the impact of extended networks on company performance using deep learning techniques. The results show that companies' network capabilities are positively associated with their financial performance, highlighting the critical role of network positions in driving success. Furthermore, the findings suggest that extending the network through deep learning offers significant benefits for companies.

Journal of Global Information ManagementVol. 33(1)
Weber State University (US), Incheon National University (KR), Dongguk University (KR), Advanced Institute of Convergence Technology (KR)
Openalex Percentile: Top 94%
Supply Chain and Inventory Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.